diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/TAGS | 2572 | ||||
| -rw-r--r-- | python/analytics/__init__.py | 3 | ||||
| -rw-r--r-- | python/analytics/option.py | 5 | ||||
| -rw-r--r-- | python/analytics/portfolio.py | 4 | ||||
| -rw-r--r-- | python/exploration/portfolio_example.py | 36 | ||||
| -rw-r--r-- | python/exploration/portfolio_var.py | 2 | ||||
| -rw-r--r-- | python/exploration/swaption_calendar_spread.py | 93 | ||||
| -rw-r--r-- | python/exploration/tranches.py | 7 | ||||
| -rw-r--r-- | python/graphics.py | 28 | ||||
| -rw-r--r-- | python/notebooks/Option Trades.ipynb | 846 | ||||
| -rw-r--r-- | python/tests/test_scenarios.py | 6 |
11 files changed, 2388 insertions, 1214 deletions
diff --git a/python/TAGS b/python/TAGS index 19eea624..75a85491 100644 --- a/python/TAGS +++ b/python/TAGS @@ -9,8 +9,39 @@ class Daemon:Daemon5,93 def restart(self):restart112,2386 def run(self):run117,2464 +globeop_reports.py,854 +def get_monthly_pnl(group_by = ['identifier']):get_monthly_pnl15,288 +def get_portfolio(report_date = None):get_portfolio24,871 +def curr_port_PNL(date = datetime.date.today(), asset_class='Subprime'):curr_port_PNL36,1488 +def trade_performance():trade_performance44,1934 +def get_net_navs():get_net_navs82,3689 +def alloc(alloc = 'pnl'):alloc95,4348 +def pnl_alloc_plot(df):pnl_alloc_plot123,5588 +def cap_alloc_plot_pie(df):cap_alloc_plot_pie144,6143 +def avg_turnover():avg_turnover157,6581 +def num_bond_by_strat():num_bond_by_strat168,7187 +def num_bond_trades():num_bond_trades175,7518 +def shift_cash(date, amount, df, strat):shift_cash183,7915 +def cap_alloc_plot_bar(df):cap_alloc_plot_bar189,8157 +def calc_trade_performance_stats():calc_trade_performance_stats207,8726 +def get_rmbs_pos_df(date = None):get_rmbs_pos_df230,9649 + GHquad.h,0 +bbg_index_quotes.py,835 +securities = {}securities5,103 +sql_str = (f"INSERT INTO bbg_index_quotes VALUES({','.join(['%s'] * 8)}) "sql_str17,558 +start_date = datetime.date.today() - datetime.timedelta(days=7) ## one weeek of overlapstart_date19,670 +conn = dbconn('serenitasdb')conn20,758 + d = retrieve_data(session, securities.keys(), fields=["TICKER", "VERSION"])d22,829 + ticker_mapping = {v['TICKER']: securities[k] + (v['VERSION'],)ticker_mapping23,909 + securities = [f"{e['TICKER']} {pcs} Curncy" for e in d.values()]securities26,1062 + d2 = retrieve_data(session, securities, fields=["PX_LAST"],d227,1135 + start_date=start_date)start_date28,1203 + ticker = k.split()[0]ticker31,1322 + index = "EU"index34,1466 + index = "XO"index36,1536 + test_igoption.py,409 index = Index.from_name("ig", 27, "5yr",index3,54 trade_date = datetime.date(2016, 11, 18))trade_date4,95 @@ -19,79 +50,64 @@ strike = 80strike7,224 payer = Swaption(index, exercise_date, strike, strike_is_price = False)payer8,236 receiver = Swaption(index, exercise_date, strike, "receiver", strike_is_price = False)receiver13,377 -markit_red.py,386 -def request_payload(payload):request_payload7,113 -def download_report(report):download_report17,498 -def update_redcodes(conn, fname):update_redcodes33,1023 -def update_redindices(fname):update_redindices53,2025 - report_list = ['REDEntity', 'REDObligation', 'REDEntityDelta', 'REDObligationDelta',report_list74,3139 - fname = download_report("REDIndexCodes")fname77,3350 +markit_red.py,277 +def request_payload(payload):request_payload8,143 +def download_report(report):download_report22,626 +def update_redcodes(conn, fname):update_redcodes37,1132 +def update_redindices(fname):update_redindices59,2265 + fname = download_report("REDIndexCodes")fname80,3379 -option_trades_et.py,1281 -serenitasdb = dbengine('serenitasdb')serenitasdb16,379 -def get_dfs(index="IG"):get_dfs18,418 -def calendar_spread():calendar_spread24,632 -def put_spread(index = "IG"):put_spread35,1013 -def swaption_analysis():swaption_analysis44,1364 -def beta_calc():beta_calc49,1546 -def build_swaption(index, series, expiry, strike, ref, trade_date, t_range= None, spread_range = None):build_swaption62,1961 - def aux(row, index, swap):aux77,2699 -def calc_delta_pnl(index, series, ref, trade_date, notional, t_range, spread_range):calc_delta_pnl96,3419 -def find_mapped_pv(bought, sold, date):find_mapped_pv121,4358 -def result_fill(df, date):result_fill155,5782 -def plot_color_map(df, val_date):plot_color_map167,6182 -def build_vol_surface_functions(date = datetime.date(2017, 2, 23), index = 'IG', series = '27'):build_vol_surface_functions187,7018 -def vol_from_surface(row, f, g):vol_from_surface212,8513 -def calc_and_plot(bought, sold, traded_price, week, lowerbound, upperbound, deltaPNL=None):calc_and_plot218,8692 -def full_analysis():full_analysis233,9176 -def manual_index_update(index, date): #index as Index Objectmanual_index_update270,10265 -def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name='shiftedcmap'):shiftedColorMap284,10767 +parse_gs_exchange.py,577 +class ParseError(Exception):ParseError10,176 +def parse_email(email, fwd_index):parse_email13,215 +def clean_df(all_df):clean_df85,3114 + fwd_index = []fwd_index104,3913 + swaption_quotes = {}swaption_quotes105,3932 + index_df = pd.DataFrame(fwd_index)index_df113,4211 + index_df = index_df.drop_duplicates(['quotedate', 'index', 'series', 'expiry'])index_df114,4250 + swaption_quotes = clean_df(swaption_quotes)swaption_quotes116,4370 + swaption_quotes = swaption_quotes.set_index(['quotedate', 'index', 'series', 'expiry'])swaption_quotes117,4418 -externalmarksbackfill.py,273 -def runAllFill():runAllFill15,301 -def runSingleFill(f):runSingleFill21,458 -def get_CUSIPs():get_CUSIPs50,1582 -def get_BVAL():get_BVAL56,1779 -def pop_BVAL_to_database(df):pop_BVAL_to_database73,2534 -def get_globs():get_globs86,3010 -settings = {settings98,3550 +yieldcurve.py,1499 +def load_curves(currency="USD", date=None):load_curves25,929 +def get_curve(effective_date, currency="USD"):get_curve44,1694 +def getMarkitIRData(effective_date=datetime.date.today(),getMarkitIRData66,2554 +def get_futures_data(date=datetime.date.today()):get_futures_data82,3306 +def rate_helpers(currency="USD", MarkitData=None, evaluation_date=None):rate_helpers89,3615 +def get_dates(date, currency="USD"):get_dates133,5679 +def roll_yc(yc, forward_date):roll_yc149,6473 +def YC(helpers=None, currency="USD", MarkitData=None, evaluation_date=None):YC155,6783 +def jpYC(effective_date, currency="USD", MarkitData=None):jpYC165,7261 +def ql_to_jp(ql_yc):ql_to_jp184,8049 +def build_curves(currency="USD"):build_curves194,8502 + helpers = rate_helpers("USD")helpers235,10603 + ts = YC(helpers)ts236,10637 + cal = calendar_from_name('USA')cal237,10658 + p1 = Period('1M')p1238,10694 + p2 = Period('2M')p2239,10716 + p3 = Period('3M')p3240,10738 + p6 = Period('6M')p6241,10760 + p12 = Period('12M')p12242,10782 + sched = Schedule.from_rule(ts.reference_date, ts.reference_date + Period('5Y'), Period('3M'), cal)sched243,10806 + days = [pydate_from_qldate(d) for d in sched]days244,10909 + f3 = [ts.forward_rate(d, d + p3, Actual360(), 0).rate for d in sched]f3245,10959 + f6 = [ts.forward_rate(d, d + p6, Actual360(), 0).rate for d in sched]f6246,11033 + f2 = [ts.forward_rate(d, d + p2, Actual360(), 0).rate for d in sched]f2247,11107 -parse_gs_exchange.py,553 -def get_msgs(email_address='ghorel@lmcg.com', count=None):get_msgs11,197 -def parse_email(email, fwd_index):parse_email26,902 -def clean_df(all_df):clean_df96,3720 -def insert_data(swaption_quotes, index_df):insert_data115,4528 - fwd_index = []fwd_index135,5374 - swaption_quotes = {}swaption_quotes136,5393 - swaption_quotes = clean_df(swaption_quotes)swaption_quotes141,5590 - index_df = pd.DataFrame(fwd_index)index_df142,5638 - index_df = index_df.drop_duplicates(['quotedate', 'index', 'series', 'expiry'])index_df143,5677 - -yieldcurve.py,1416 -def get_curves(currency="USD", date=None):get_curves24,915 -_USD_curves = get_curves("USD")_USD_curves42,1603 -_EUR_curves = get_curves("EUR")_EUR_curves43,1635 -def getMarkitIRData(effective_date = datetime.date.today(),getMarkitIRData45,1668 -def get_futures_data(date = datetime.date.today()):get_futures_data60,2375 -def rate_helpers(currency="USD", MarkitData=None):rate_helpers67,2686 -def get_dates(date, currency="USD"):get_dates109,4709 -def roll_yc(yc, forward_date):roll_yc125,5507 -def YC(helpers = None, currency="USD", MarkitData=None):YC131,5798 -def jpYC(effective_date, currency="USD", MarkitData=None):jpYC138,6114 -def ql_to_jp(ql_yc):ql_to_jp157,6902 -def build_curves(currency="USD"):build_curves167,7355 - ts = YC()ts207,9435 - cal = calendar_from_name('USA')cal208,9449 - p1 = Period('1Mo')p1209,9485 - p2 = Period('2Mo')p2210,9508 - p3 = Period('3Mo')p3211,9531 - p6 = Period('6Mo')p6212,9554 - p12 = Period('12Mo')p12213,9577 - sched = Schedule(ts.reference_date, ts.reference_date+Period('5Yr'), Period('3Mo'), cal)sched214,9602 - days = [pydate_from_qldate(d) for d in sched]days215,9695 - f3 = [ts.forward_rate(d, d+p3, Actual360(), 0).rate for d in sched]f3216,9745 - f6 = [ts.forward_rate(d, d+p6, Actual360(), 0).rate for d in sched]f6217,9817 - f2 = [ts.forward_rate(d, d+p2, Actual360(), 0).rate for d in sched]f2218,9889 +bbg_cds_quotes.py,935 +logger = logging.getLogger('bbg_quotes')logger9,209 +fh = logging.FileHandler(filename=os.path.join(os.environ['LOG_DIR'], 'bbg_quotes.log'))fh10,250 +formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')formatter11,339 +workdate = datetime.date.today()workdate16,505 +serenitasdb = dbconn('serenitasdb')serenitasdb17,538 +index_list = get_index_list(serenitasdb, workdate)index_list18,574 +basket_ids = get_basketids(serenitasdb, index_list, workdate)basket_ids19,625 +bbg_tickers = set(get_bbg_tickers(serenitasdb, basket_ids, workdate))bbg_tickers20,687 +securities = [f'{ticker} Curncy' for ticker in bbg_tickers]securities22,788 +fields = ['UPFRONT_RUNNING_SPREAD', 'UPFRONT_BID', 'UPFRONT_ASK', 'CDS_RECOVERY_RT']fields23,848 +r = {}r25,934 +sql_str = f"INSERT INTO cds_quotes VALUES({','.join(['%s'] * 8)})"sql_str31,1184 +def build_tuple(k, v, workdate, source):build_tuple33,1252 db.py,499 class InfDateAdapter:InfDateAdapter11,278 @@ -99,26 +115,34 @@ class InfDateAdapter:InfDateAdapter11,278 def getquoted(self):getquoted14,364 def nan_to_null(f, _NULL=AsIs('NULL'),nan_to_null22,653 def dbconn(dbname):dbconn32,945 -def dbengine(dbname):dbengine43,1282 -def with_connection(dbname):with_connection53,1719 - def decorator(f):decorator54,1748 - def with_connection_(*args, **kwargs):with_connection_56,1800 -def query_db(conn, sqlstr, params=None, one=True):query_db68,2154 +def dbengine(dbname):dbengine43,1308 +def with_connection(dbname):with_connection55,1803 + def decorator(f):decorator56,1832 + def with_connection_(*args, **kwargs):with_connection_58,1884 +def query_db(conn, sqlstr, params=None, one=True):query_db70,2238 + +backpopulate.py,449 +p = Path('/home/serenitas/CorpCDOs/Tranche_data/CDS')p4,58 +quotefiles = (f for f in p.iterdir() if f.is_file())quotefiles5,112 +tenors = ['6m', '1y', '2y', '3y', '4y', '5y', '7y', '10y']tenors6,165 +conn = dbconn('serenitasdb')conn7,224 +sql_str = "INSERT INTO cds_quotes VALUES({})".format(",".join(["%s"] * 8))sql_str8,253 +tickers = ['CT659914', 'CT391460', 'CT391464', 'CT391468', 'CT391472',tickers10,329 +def convert(s):convert13,448 -backpopulate.py,342 -col =["CY316528", "CY316534", "CY316540", "CY316546", "CY316552", "CY316558", "CY316564", "CY316570"]col4,49 -df = df[df.index.isin(pd.date_range(df.index[0], pd.Timestamp('2016-03-31'), freq=bus_day))]df6,152 -sql_str = "INSERT INTO cds_quotes VALUES({})".format(",".join(["%s"] * 8))sql_str8,246 -conn = dbconn('serenitasdb')conn9,321 +mark_backtest.py,152 +def calc_mark_diff(asset_class = 'Subprime'):calc_mark_diff4,45 + def closest(x):closest30,1357 + def remove_max_min(x):remove_max_min51,2174 tests/test_scenarios.py,514 -class TestSenarios(unittest.TestCase):TestSenarios10,287 - option_delta = Index.from_tradeid(874)option_delta11,326 - option1 = BlackSwaption.from_tradeid(7, option_delta)option112,369 - option2 = BlackSwaption.from_tradeid(8, option_delta)option213,427 - portf = Portfolio([option1, option2, option_delta])portf14,485 - date_range = pd.bdate_range(option_delta.trade_date, pd.Timestamp('2017-05-17') - BDay(), freq = '5B')date_range15,541 - def test_portfolio(self):test_portfolio17,649 +class TestSenarios(unittest.TestCase):TestSenarios10,293 + option_delta = Index.from_tradeid(874)option_delta11,332 + option1 = BlackSwaption.from_tradeid(7, option_delta)option112,375 + option2 = BlackSwaption.from_tradeid(8, option_delta)option213,433 + portf = Portfolio([option1, option2, option_delta])portf14,491 + date_range = pd.bdate_range(option_delta.trade_date, pd.Timestamp('2017-05-17') - BDay(), freq = '5B')date_range15,547 + def test_portfolio(self):test_portfolio17,655 tests/test_swaption.py,1230 class TestPutCallParity(unittest.TestCase):TestPutCallParity9,150 @@ -129,24 +153,24 @@ class TestPutCallParity(unittest.TestCase):TestPutCallParity9,150 def test_parity(self):test_parity16,397 def test_parity_black(self):test_parity_black26,927 def test_calibration(self):test_calibration36,1473 - def test_hy(self):test_hy44,1747 -class TestBreakeven(unittest.TestCase):TestBreakeven54,2140 - exercise_date = datetime.date(2017, 3, 15)exercise_date56,2181 - hyindex = Index.from_name("hy", 27, "5yr",hyindex57,2228 - trade_date=datetime.date(2016, 11, 16))trade_date58,2275 - hystrike = 102.5hystrike60,2372 - igindex = Index.from_name("ig", 27, "5yr",igindex62,2394 - trade_date=datetime.date(2016, 11, 18))trade_date63,2441 - igstrike = 80igstrike65,2537 - def test_hypayer(self):test_hypayer67,2556 - def test_hyreceiver(self):test_hyreceiver73,2786 - def test_igpayer(self):test_igpayer80,3070 - def test_igreceiver(self):test_igreceiver86,3288 + def test_hy(self):test_hy44,1748 +class TestBreakeven(unittest.TestCase):TestBreakeven54,2141 + exercise_date = datetime.date(2017, 3, 15)exercise_date56,2182 + hyindex = Index.from_name("hy", 27, "5yr",hyindex57,2229 + trade_date=datetime.date(2016, 11, 16))trade_date58,2276 + hystrike = 102.5hystrike60,2373 + igindex = Index.from_name("ig", 27, "5yr",igindex62,2395 + trade_date=datetime.date(2016, 11, 18))trade_date63,2442 + igstrike = 80igstrike65,2538 + def test_hypayer(self):test_hypayer67,2557 + def test_hyreceiver(self):test_hyreceiver73,2790 + def test_igpayer(self):test_igpayer80,3078 + def test_igreceiver(self):test_igreceiver86,3303 tests/test_yieldcurve.py,207 -class TestYieldCurve(unittest.TestCase):TestYieldCurve10,232 - def assertListAlmostEqual(self, list1, list2, places = 7):assertListAlmostEqual12,274 - def test_bloomberg(self):test_bloomberg17,475 +class TestYieldCurve(unittest.TestCase):TestYieldCurve10,233 + def assertListAlmostEqual(self, list1, list2, places = 7):assertListAlmostEqual12,275 + def test_bloomberg(self):test_bloomberg17,476 tests/test_cds.py,345 class TestUpfront(unittest.TestCase):TestUpfront12,246 @@ -156,13 +180,25 @@ class TestUpfront(unittest.TestCase):TestUpfront12,246 def test_cdsone(self):test_cdsone21,537 def test_annuity(self):test_annuity43,1672 -tests/test_dates.py,392 -class TestStartDate(unittest.TestCase):TestStartDate9,117 - def test_previous_twentieth(self):test_previous_twentieth11,158 - def test_previous_twentieth_timestamp(self):test_previous_twentieth_timestamp21,706 -class TestEndDate(unittest.TestCase):TestEndDate31,1260 - def test_enddate(self):test_enddate32,1298 - def test_enddate_pre2015(self):test_enddate_pre201542,1811 +tests/test_swap_index.py,107 +class UsdLiborSwap(unittest.TestCase):UsdLiborSwap8,176 + def test_creation(self):test_creation9,215 + +tests/test_dates.py,668 +class TestStartDate(unittest.TestCase):TestStartDate10,166 + def test_previous_twentieth(self):test_previous_twentieth12,207 + def test_previous_twentieth_timestamp(self):test_previous_twentieth_timestamp22,755 +class TestEndDate(unittest.TestCase):TestEndDate32,1309 + def test_enddate(self):test_enddate33,1347 + def test_enddate_pre2015(self):test_enddate_pre201543,1860 +class TestEndDateC(unittest.TestCase):TestEndDateC57,2624 + roll_date_c = lambda d, t: TDate_to_pydate(end_dates(pydate_to_TDate(d), t))roll_date_c58,2663 + def test_enddate(self):test_enddate60,2745 + def test_enddate_pre2015(self):test_enddate_pre201570,3266 + +tests/.ropeproject/config.py,90 +def set_prefs(prefs):set_prefs5,45 +def project_opened(project):project_opened110,4652 tests/test_index.py,1159 class TestPickle(unittest.TestCase):TestPickle12,219 @@ -185,6 +221,48 @@ class TestForwardIndex(unittest.TestCase):TestForwardIndex58,2130 def test_forward_pv(self):test_forward_pv66,2426 def test_forward_pv(self):test_forward_pv72,2726 +tests/test_upfront_cds.py,2424 +def snac_pv(spread, term_date, fixed_coupon=0.01, recovery=0.4, ts=YC()):snac_pv23,1037 +def jpmorgan_curves(trade_date, value_date, start_date, end_date, spread, recovery=0.4):jpmorgan_curves45,2479 + settings = Settings()settings54,2880 + yield_helpers = rate_helpers()yield_helpers56,2955 + ts = YC(helpers = yield_helpers)ts57,2990 + tenor = Period(5, Years)tenor58,3027 + trade_date = datetime.date(2009, 5, 21)trade_date59,3056 + stepin_date = trade_date + datetime.timedelta(days=1)stepin_date60,3100 + value_date = datetime.date(2009, 5, 26)value_date61,3158 + term_date = datetime.date(2019, 6, 20)term_date62,3202 + start_date = datetime.date(2009, 3, 20)start_date63,3245 + spread = 0.001spread64,3289 + sc_data = sc.inspect()['data']sc_data66,3408 + hazard_rate = math.log(1 + sc_data[0][1])hazard_rate67,3443 + contingent_leg = ContingentLeg(start_date, term_date, 10000000)contingent_leg68,3489 + fee_leg = FeeLeg(start_date, term_date, True, 10000000, 0.01)fee_leg69,3557 + flat_curve = FlatHazardRate(0, WeekendsOnly(), hazard_rate, Actual365Fixed())flat_curve71,3624 + cds_schedule = Schedule(Date.from_datetime(trade_date), Date.from_datetime(term_date),cds_schedule72,3706 + cds_trade = CreditDefaultSwap.from_upfront(BUYER, 10000000, 0., 0.01, cds_schedule, Following, Actual360(),cds_trade75,3919 + protection_start = Date.from_datetime(trade_date) + 1,protection_start76,4031 + last_period_day_counter = Actual360(True))last_period_day_counter77,4133 + isda_pricer = IsdaCdsEngine(flat_curve, 0.4, ts, accrual_bias=AccrualBias.HalfDayBias,isda_pricer78,4223 + forwards_in_coupon_period = ForwardsInCouponPeriod.Piecewise)forwards_in_coupon_period79,4314 + cds_trade2 = CreditDefaultSwap(BUYER, 10000000, spread, cds_schedule, Following, Actual360(),cds_trade283,4472 + protection_start = Date.from_datetime(trade_date) + 1,protection_start84,4570 + last_period_day_counter = Actual360(True))last_period_day_counter85,4660 + h = 0.00168276528775h87,4786 + flat_curve2 = FlatHazardRate(0, WeekendsOnly(), h, Actual365Fixed())flat_curve288,4811 + isda_pricer2 = IsdaCdsEngine(flat_curve2, 0.4, ts)isda_pricer289,4884 + +tests/test_sabr_quantlib.py,720 +strikes = np.array([50, 55, 57.5, 60, 62.5, 65, 67.5, 70, 75, 80, 85])strikes7,257 +pvs = np.array([53.65, 37.75, 31.55, 26.45, 22.25, 18.85, 16.15, 13.95, 10.55,pvs8,328 +option_date = Settings().instance().evaluation_date + Period(3, Months)option_date10,461 +forward = SimpleQuote(58.71e-4)forward11,533 +strikes = np.array([50, 55, 57.5, 60, 62.5, 65, 67.5, 70, 75, 80, 85, 90, 95, 100]) * 1e-4strikes12,565 +vol = np.array([28.5, 31.6, 33.7, 36.1, 38.7, 41.5, 44.1,vol13,656 +vol_quotes = [SimpleQuote(q) for q in vol]vol_quotes15,780 +section = SabrInterpolatedSmileSection(option_date, forward, strikes, False,section17,824 + is_beta_fixed=True)is_beta_fixed19,988 + database_consistency.py,248 engine = create_engine('postgresql://et_user@debian/ET')engine6,99 data12 = pd.merge(data1, data2, left_index=True, right_index=True)data1221,1249 @@ -211,15 +289,17 @@ class TestPickle(unittest.TestCase):TestPickle9,201 def test_legs(self):test_legs25,794 pyisda/pyisda/credit_index.pxd,92 -cdef class CurveList:CurveList8,230 -cdef class CreditIndex(CurveList):CreditIndex14,401 +cdef class CurveList:CurveList8,210 +cdef class CreditIndex(CurveList):CreditIndex16,449 pyisda/pyisda/logging.pxd,0 -pyisda/pyisda/date.pxd,191 +pyisda/pyisda/date.pxd,364 cdef long dcc(str day_count) except -1dcc7,206 -cpdef TDate pydate_to_TDate(c_datetime.date d)pydate_to_TDate47,1597 -cpdef c_datetime.date TDate_to_pydate(TDate d)TDate_to_pydate49,1645 +cpdef TDate pydate_to_TDate(c_datetime.date d)pydate_to_TDate50,1790 +cpdef c_datetime.date TDate_to_pydate(TDate d)TDate_to_pydate52,1838 +cdef void _roll_date(TDate d, double* tenors, int n_dates, TDate* output) nogil_roll_date54,1886 +cdef TDate _previous_twentieth(TDate d) nogil_previous_twentieth55,1966 pyisda/pyisda/__init__.py,0 @@ -232,15 +312,20 @@ def set_logging_file(str file_name, TBoolean append = True):set_logging_file15 def log_message(str msg):log_message22,554 def flush():flush27,679 -pyisda/pyisda/date.pyx,246 -cpdef TDate pydate_to_TDate(c_datetime.date d):pydate_to_TDate7,137 -cpdef c_datetime.date TDate_to_pydate(TDate d):TDate_to_pydate10,250 -cdef long dcc(str day_count) except -1:dcc15,434 -def dcc_tostring(long day_count):dcc_tostring25,738 +pyisda/pyisda/date.pyx,593 +cpdef TDate pydate_to_TDate(c_datetime.date d):pydate_to_TDate13,250 +cpdef c_datetime.date TDate_to_pydate(TDate d):TDate_to_pydate16,363 +cdef long dcc(str day_count) except -1:dcc23,600 +def dcc_tostring(long day_count):dcc_tostring33,904 +cdef TDate _previous_twentieth(TDate d) nogil:_previous_twentieth41,1112 +def previous_twentieth(d):previous_twentieth64,1671 +cdef TMonthDayYear next_twentieth(TDate d) nogil:next_twentieth68,1794 +cdef void _roll_date(TDate d, double* tenors, int n_dates, TDate* output) nogil:_roll_date86,2235 +def roll_date(d, tenor):roll_date122,3355 pyisda/pyisda/cdsone.pyx,198 -def upfront_charge(date, value_date, benchmark_start_date, stepin_date,upfront_charge6,120 -def spread_from_upfront(date, value_date, benchmark_start_date, stepin_date,spread_from_upfront68,2806 +def upfront_charge(date, value_date, benchmark_start_date, stepin_date,upfront_charge6,116 +def spread_from_upfront(date, value_date, benchmark_start_date, stepin_date,spread_from_upfront69,2787 pyisda/pyisda/legs.pyx,837 cdef class ContingentLeg:ContingentLeg7,218 @@ -259,80 +344,93 @@ cdef class FeeLeg:FeeLeg75,2818 def accrued(self, today):accrued189,7477 def __dealloc__(self):__dealloc__204,7783 -pyisda/pyisda/curve.pyx,2494 - FOLLOW = <long>'F'FOLLOW30,1013 - PREVIOUS = <long>'P'PREVIOUS31,1036 - NONE = <long>'N'NONE32,1061 - MODIFIED = <long>'M'MODIFIED33,1082 -cdef class Curve(object):Curve38,1225 - def __getstate__(self):__getstate__40,1252 - def __setstate__(self, bytes state):__setstate__48,1565 - def from_bytes(cls, object state):from_bytes56,1818 - def __hash__(self):__hash__71,2339 - def inspect(self):inspect81,2701 - def to_series(self, bint forward=True):to_series97,3264 - def __iter__(self):__iter__122,4284 - def __len__(self):__len__129,4518 - def __deepcopy__(self, memo):__deepcopy__132,4587 - def forward_hazard_rates(self):forward_hazard_rates139,4799 - def base_date(self):base_date170,6045 - def __forward_zero_price(self, d2, d1=None):__forward_zero_price173,6133 -cdef fArray_to_list(TRatePt* fArray, int fNumItems):fArray_to_list195,6864 -cdef class YieldCurve(Curve):YieldCurve202,7071 - def __init__(self, date, str types,__init__231,8033 - def __getstate__(self):__getstate__287,10210 - def __setstate__(self, bytes state):__setstate__301,10800 - def from_bytes(cls, object state):from_bytes315,11291 - def __hash__(self):__hash__338,12075 - def from_discount_factors(cls, base_date, list dates, double[:] dfs, str day_count_conv):from_discount_factors355,12731 - discount_factor = Curve.__forward_zero_pricediscount_factor372,13591 - def dates(self):dates375,13655 - def expected_forward_curve(self, forward_date):expected_forward_curve381,13795 -cdef void tweak_curve(TCurve* sc, TCurve* sc_tweaked, double epsilon,tweak_curve405,14857 -cdef class SpreadCurve(Curve):SpreadCurve428,15597 - def __init__(self, today, YieldCurve yc, start_date, step_in_date,__init__449,16235 - survival_probability = Curve.__forward_zero_pricesurvival_probability512,19213 - def __getstate__(self):__getstate__514,19268 - def __setstate__(self, bytes state):__setstate__528,19833 - def from_bytes(cls, bytes state):from_bytes541,20276 - def __hash__(self):__hash__562,21009 - def from_flat_hazard(cls, base_date, double rate, Basis basis=CONTINUOUS,from_flat_hazard579,21640 - def tweak_curve(self, double epsilon, bint multiplicative=True,tweak_curve605,22610 - def par_spread(self, today, step_in_date, start_date, end_dates,par_spread647,24064 - def ticker(self):ticker694,26106 -def fill_curve(SpreadCurve sc, TDate[:] end_dates):fill_curve701,26274 +pyisda/pyisda/curve.pyx,2697 + FOLLOW = <long>'F'FOLLOW32,1096 + PREVIOUS = <long>'P'PREVIOUS33,1119 + NONE = <long>'N'NONE34,1144 + MODIFIED = <long>'M'MODIFIED35,1165 +cdef class Curve(object):Curve44,1373 + def __getstate__(self):__getstate__46,1400 + def __setstate__(self, bytes state):__setstate__54,1713 + def from_bytes(cls, object state):from_bytes62,1966 + def __hash__(self):__hash__77,2487 + def inspect(self):inspect87,2849 + def to_series(self, bint forward=True):to_series103,3412 + def __iter__(self):__iter__131,4549 + def __len__(self):__len__138,4783 + def __deepcopy__(self, dict memo):__deepcopy__141,4852 + def forward_hazard_rates(self):forward_hazard_rates149,5097 + def base_date(self):base_date180,6343 + def __forward_zero_price(self, d2, d1=None):__forward_zero_price183,6431 +cdef fArray_to_list(TRatePt* fArray, int fNumItems):fArray_to_list205,7162 +cdef class YieldCurve(Curve):YieldCurve212,7369 + def __init__(self, date, str types,__init__241,8331 + def __getstate__(self):__getstate__297,10508 + def __setstate__(self, bytes state):__setstate__308,10967 + def __deepcopy__(self, dict memo):__deepcopy__321,11441 + def from_bytes(cls, object state):from_bytes329,11721 + def __hash__(self):__hash__352,12505 + def from_discount_factors(cls, base_date, list dates, double[:] dfs, str day_count_conv):from_discount_factors369,13161 + discount_factor = Curve.__forward_zero_pricediscount_factor386,14021 + def dates(self):dates389,14085 + def expected_forward_curve(self, forward_date):expected_forward_curve395,14225 +cdef void tweak_curve(TCurve* sc, TCurve* sc_tweaked, double epsilon,tweak_curve419,15287 +cdef class SpreadCurve(Curve):SpreadCurve442,16027 + def __init__(self, today, YieldCurve yc, start_date, step_in_date,__init__464,16700 + survival_probability = Curve.__forward_zero_pricesurvival_probability570,21409 + def __getstate__(self):__getstate__572,21464 + def __setstate__(self, bytes state):__setstate__585,22071 + def __deepcopy__(self, dict memo):__deepcopy__602,22797 + def from_bytes(cls, bytes state):from_bytes613,23296 + def __hash__(self):__hash__639,24277 + def from_flat_hazard(cls, base_date, double rate, Basis basis=CONTINUOUS,from_flat_hazard655,24970 + def tweak_curve(self, double epsilon, bint multiplicative=True,tweak_curve681,25940 + def par_spread(self, today, step_in_date, start_date, end_dates,par_spread726,27588 + def ticker(self):ticker773,29630 + def recovery_rates(self):recovery_rates777,29703 +cdef TCurve* _fill_curve(TCurve* sc, TDate* end_dates, int n_dates):_fill_curve786,30061 pyisda/pyisda/curve.pxd,527 - CONTINUOUS = 5000CONTINUOUS179,7643 - DISCOUNT_RATE = 512DISCOUNT_RATE180,7665 - SIMPLE_BASIS = 0SIMPLE_BASIS181,7689 - ANNUAL_BASIS = 1ANNUAL_BASIS182,7710 - DISCOUNT_FACTOR = -2DISCOUNT_FACTOR183,7731 -cdef class Curve:Curve194,7987 -cdef class YieldCurve(Curve):YieldCurve197,8043 -cdef class SpreadCurve(Curve):SpreadCurve200,8103 -cdef fArray_to_list(TRatePt* fArray, int fNumItems)fArray_to_list203,8158 -cdef void tweak_curve(TCurve* sc, TCurve* sc_tweaked, double epsilon,tweak_curve205,8211 + CONTINUOUS = 5000CONTINUOUS193,8215 + DISCOUNT_RATE = 512DISCOUNT_RATE194,8237 + SIMPLE_BASIS = 0SIMPLE_BASIS195,8261 + ANNUAL_BASIS = 1ANNUAL_BASIS196,8282 + DISCOUNT_FACTOR = -2DISCOUNT_FACTOR197,8303 +cdef class Curve:Curve208,8559 +cdef class YieldCurve(Curve):YieldCurve211,8615 +cdef class SpreadCurve(Curve):SpreadCurve214,8675 +cdef fArray_to_list(TRatePt* fArray, int fNumItems)fArray_to_list218,8773 +cdef void tweak_curve(TCurve* sc, TCurve* sc_tweaked, double epsilon,tweak_curve220,8826 -pyisda/pyisda/credit_index.pyx,1227 -cdef class CurveList:CurveList19,682 - def __init__(self, list curves, double[:] weights=None):__init__22,763 - def __getitem__(self, str ticker):__getitem__46,1603 - def items(self):items61,2086 - def curves(self):curves74,2463 - def curves(self, list l):curves91,2942 -cdef class CreditIndex(CurveList):CreditIndex110,3466 - def __init__(self, start_date, maturities, list curves, double[:] weights=None):__init__111,3501 - def __dealloc__(self):__dealloc__143,5276 - def pv_vec(self, step_in_date, value_date, YieldCurve yc, double recovery_rate):pv_vec153,5656 - def accrued(self):accrued202,7872 - def pv(self, step_in_date, value_date, maturity, YieldCurve yc not None,pv208,8039 - def theta(self, step_in_date, value_date, maturity, YieldCurve yc not None,theta235,9287 - def duration(self, step_in_date, value_date, maturity, YieldCurve yc not None):duration266,10738 - def maturities(self):maturities301,11839 - def tweak_portfolio(self, double epsilon, maturity, inplace=True):tweak_portfolio310,12038 -cdef pair[TContingentLeg,TFeeLeg] get_legs(TDate maturity,get_legs351,13281 -cdef double pv(unordered_map[string,shared_ptr[TCurve]]& curves,pv385,14798 +pyisda/pyisda/credit_index.pyx,1813 +cdef TFeeLeg* copyFeeLeg(TFeeLeg* leg) nogil:copyFeeLeg31,1229 +cdef TContingentLeg* copyContingentLeg(TContingentLeg* leg) nogil:copyContingentLeg43,1753 +cdef class CurveList:CurveList49,1999 + def __init__(self, list curves not None, double[:] weights=None, trade_date=None):__init__52,2058 + def __getitem__(self, str ticker):__getitem__99,3713 + def items(self):items115,4252 + def weights(self):weights129,4710 + def tickers(self):tickers138,5032 + def trade_date(self):trade_date147,5321 + def trade_date(self, d):trade_date151,5418 + def curves(self):curves155,5506 + def curves(self, list l not None):curves173,6050 + def __reduce__(self):__reduce__201,7075 +cdef class CreditIndex(CurveList):CreditIndex206,7256 + def __init__(self, start_date, maturities, list curves, double[:] weights=None,__init__207,7291 + def __dealloc__(self):__dealloc__225,8182 + def __reduce__(self):__reduce__262,9846 + def __hash__(self):__hash__267,10051 + def pv_vec(self, step_in_date, value_date, YieldCurve yc, double recovery_rate):pv_vec298,11366 + def accrued(self):accrued349,13600 + def pv(self, step_in_date, value_date, maturity, YieldCurve yc not None,pv354,13736 + def theta(self, step_in_date, value_date, maturity, YieldCurve yc not None,theta385,14997 + def duration(self, step_in_date, value_date, maturity, YieldCurve yc not None):duration433,16989 + def maturities(self):maturities482,18677 + def tweak_portfolio(self, double epsilon, maturity, bint inplace=True):tweak_portfolio491,18877 + def survival_matrix(self, TDate[:] schedule):survival_matrix501,19313 +cdef pair[TContingentLeg_ptr,TFeeLeg_ptr] get_legs(TDate maturity,get_legs557,20951 +cdef double pv(vector[shared_ptr[TCurve]]& curves,pv580,21929 pyisda/pyisda/version.pyx,28 def version():version4,71 @@ -464,36 +562,36 @@ def affected_indices(company_id):affected_indices6,92 def create_newindices(recordslist, lastdate, nissuers):create_newindices18,525 def update_indexmembers(newids, company_id):update_indexmembers40,1428 -bbg_helpers.py,2232 +bbg_helpers.py,2233 logger = logging.getLogger(__name__)logger8,115 BBG_IP = ['192.168.9.61', '192.168.9.65', '192.168.0.10', '192.168.0.12']BBG_IP10,153 def init_bbg_session(ip_list, port=8194):init_bbg_session13,244 def append_overrides(request, d):append_overrides36,993 def event_loop(session, request):event_loop46,1326 def get_pythonvalue(e):get_pythonvalue59,1809 -def field_array_todf(field):field_array_todf67,2079 -def process_historical_msg(msg):process_historical_msg74,2342 -def process_reference_msg(msg):process_reference_msg80,2594 -def process_intraday_tick_msg(msg):process_intraday_tick_msg97,3296 -def retrieve_data(session, securities, fields=[], overrides={},retrieve_data101,3427 - testdate = pd.datetime(2013, 1, 1)testdate184,6653 - hist_securities = ['CADUSD Curncy', "EURUSD Curncy"]hist_securities185,6692 - hist_fields = ['PX_LAST']hist_fields186,6749 - securities = ['004421BW2 Mtge', '75157EAE2 Mtge', 'XS0295516776 Mtge']securities187,6779 - fields = ['CUR_CPN', 'START_ACC_DT']fields188,6854 - hist_data = retrieve_data(session, securities, hist_fields, start_date=testdate,hist_data190,6941 - frequency="MONTHLY")frequency191,7030 - overrides={'SETTLE_DT': testdate}overrides192,7085 - ref_data = retrieve_data(session, securities, fields, overrides=overrides)ref_data193,7127 - struct_data = retrieve_data(session, securities, ["HIST_CASH_FLOW"])struct_data194,7210 - spx_ndx_monthly = retrieve_data(session, ["SPX Index","NDX Index"],spx_ndx_monthly195,7287 - fields=["PX_LAST"],fields196,7363 - start_date=datetime.date(2012, 1, 1),start_date197,7423 - options={'periodicityAdjustment': 'ACTUAL'},options198,7501 - frequency="MONTHLY")frequency199,7586 - trace_data = retrieve_data(session, "BNCMT 2007-1 A5@TRAC Mtge",trace_data200,7647 - start_date=datetime.datetime(2016, 5, 18, 9),start_date201,7720 - end_date=datetime.datetime(2017, 5, 18, 9))end_date202,7801 +def field_array_todf(field):field_array_todf71,2173 +def process_historical_msg(msg):process_historical_msg78,2436 +def process_reference_msg(msg):process_reference_msg84,2688 +def process_intraday_tick_msg(msg):process_intraday_tick_msg101,3390 +def retrieve_data(session, securities, fields=[], overrides={},retrieve_data105,3521 + testdate = pd.datetime(2013, 1, 1)testdate188,6766 + hist_securities = ['CADUSD Curncy', "EURUSD Curncy"]hist_securities189,6805 + hist_fields = ['PX_LAST']hist_fields190,6862 + securities = ['004421BW2 Mtge', '75157EAE2 Mtge', 'XS0295516776 Mtge']securities191,6892 + fields = ['CUR_CPN', 'START_ACC_DT']fields192,6967 + hist_data = retrieve_data(session, securities, hist_fields, start_date=testdate,hist_data194,7054 + frequency="MONTHLY")frequency195,7143 + overrides={'SETTLE_DT': testdate}overrides196,7198 + ref_data = retrieve_data(session, securities, fields, overrides=overrides)ref_data197,7240 + struct_data = retrieve_data(session, securities, ["HIST_CASH_FLOW"])struct_data198,7323 + spx_ndx_monthly = retrieve_data(session, ["SPX Index","NDX Index"],spx_ndx_monthly199,7400 + fields=["PX_LAST"],fields200,7476 + start_date=datetime.date(2012, 1, 1),start_date201,7536 + options={'periodicityAdjustment': 'ACTUAL'},options202,7614 + frequency="MONTHLY")frequency203,7699 + trace_data = retrieve_data(session, "BNCMT 2007-1 A5@TRAC Mtge",trace_data204,7760 + start_date=datetime.datetime(2016, 5, 18, 9),start_date205,7833 + end_date=datetime.datetime(2017, 5, 18, 9))end_date206,7914 send_email.py,473 SCOPES = 'https://www.googleapis.com/auth/gmail.modify'SCOPES15,270 @@ -510,12 +608,22 @@ def main():main62,2055 GHquad.c,56 void GHquad(int n, double* Z, double* w) {GHquad7,167 -download_emails.py,285 -def ListMessagesWithLabels(service, user_id, label_ids=[]):ListMessagesWithLabels17,326 -def labels_dict(service, user_id):labels_dict48,1698 -def get_msg(service, user_id, msg_id):get_msg65,2278 -def msg_content(msg):msg_content72,2566 -def update_emails():update_emails87,3158 +download_emails.py,534 +def ListMessagesWithLabels(service, user_id, label_ids=[]):ListMessagesWithLabels21,445 +def ListHistory(service, user_id, label_id=None, start_history_id=10000):ListHistory52,1817 +def labels_dict(service, user_id):labels_dict89,3376 +class GmailMessage(EmailMessage):GmailMessage106,3956 + _service = get_gmail_service()_service107,3990 + def msgdict(self):msgdict109,4026 + def send(self):send112,4125 + def from_id(cls, msg_id, user_id='me'):from_id122,4474 +def save_emails(update=True):save_emails135,5032 + +debug_forward_price.py,219 +hy28 = Index.from_name("hy", 28, "5yr")hy283,58 +hy28_forward = ForwardIndex(hy28, datetime.date(2017, 8, 16))hy28_forward4,98 +r = []r6,178 + hy28_forward = ForwardIndex(hy28, excercise_date)hy28_forward10,398 marks_to_HY.py,5400 def monthlySpreadDiff(index="IG", tenor="5yr"):monthlySpreadDiff16,435 @@ -594,16 +702,14 @@ difference4 = difference4.set_index('source', append = True)difference4181,839 meanmarkchange= difference4.groupby(level = ['monthend_date', 'source'])['spread'].mean().unstack(level = -1)meanmarkchange182,8458 StdDevmarkchange = difference4.groupby(level = ['monthend_date', 'source'])['spread'].std().unstack(level = -1)StdDevmarkchange183,8568 -cds_curve.py,775 -def get_singlenames_quotes(indexname, date):get_singlenames_quotes22,673 -def build_curve(r, today_date, yc, start_date, step_in_date, value_date, end_dates):build_curve28,891 -def build_curves_dist(quotes, args, workers=4):build_curves_dist43,1577 -def build_curves(quotes, args):build_curves50,1860 -def get_singlenames_curves(index_type, series, trade_date):get_singlenames_curves53,1961 -def all_curves_pv(curves, today_date, jp_yc, start_date, step_in_date, value_date, maturities):all_curves_pv70,2756 -serenitas_engine = dbengine('serenitasdb')serenitas_engine90,3783 -def calibrate_portfolio(index_type, series, tenors=['3yr', '5yr', '7yr', '10yr'],calibrate_portfolio92,3827 - df = calibrate_portfolio("HY", 25, ['3yr', '5yr', '7yr', '10yr'])df163,7153 +cds_curve.py,502 +def all_curves_pv(curves, today_date, jp_yc, start_date, step_in_date, value_date, maturities):all_curves_pv11,221 +def calibrate_portfolio(index_type, series, tenors=['3yr', '5yr', '7yr', '10yr'],calibrate_portfolio32,1249 + parser = argparse.ArgumentParser()parser50,1962 + args = parser.parse_args()args54,2204 + conn = dbconn('serenitasdb')conn56,2279 + start_date = Nonestart_date66,2631 + df = calibrate_portfolio(index, series, ['3yr', '5yr', '7yr', '10yr'],df68,2658 cds_rebook.py,333 def get_outstanding_positions(engine):get_outstanding_positions7,148 @@ -612,49 +718,56 @@ def rebook(engine, secid, lastdate, already_rebooked):rebook31,1141 def rebook_everything(engine):rebook_everything49,1961 engine = create_engine("postgresql://dawn_user@debian/dawndb")engine59,2338 -dawn_utils.py,111 -def create_trigger_function(conn):create_trigger_function5,80 -def create_triggers():create_triggers34,1110 +dawn_utils.py,363 +def create_trigger_function(db):create_trigger_function6,100 +def create_triggers(db):create_triggers42,1466 +def load_counterparties(engine):load_counterparties51,1815 +def load_trades(engine, schema=None):load_trades70,3153 +def load_trades_futures(engine, schema=None):load_trades_futures100,4798 +def load_wires(engine, schema=None):load_wires135,6686 -parse_emails.py,2740 - level=logging.WARNING,level14,332 - format='%(asctime)s %(message)s')format15,375 -def list_imm_dates(date):list_imm_dates17,430 -def makedf(r, indextype, quote_source):makedf25,610 -def parse_quotedate(fh, date_received):parse_quotedate54,1727 -def parse_refline(line):parse_refline71,2387 -def parse_baml(fh, indextype, series, quotedate, *args):parse_baml83,2842 -def parse_baml_block(fh, indextype):parse_baml_block108,3667 -def parse_ms_block(fh, indextype):parse_ms_block124,4132 -def parse_nomura_block(fh, indextype):parse_nomura_block149,4950 -def parse_sg_block(fh, indextype, expiration_dates):parse_sg_block172,5763 -def parse_gs_block(fh, indextype):parse_gs_block200,6856 -def parse_ms(fh, indextype, *args):parse_ms229,7675 -def parse_nomura(fh, indextype, *args):parse_nomura239,8004 - def aux(line, fh, indextype, option_stack):aux241,8066 -def parse_sg(fh, indextype, expiration_dates):parse_sg257,8675 -def parse_gs(fh, indextype, series, quotedate, ref):parse_gs267,8984 -subject_baml = re.compile("(?:Fwd:){0,2}(?:BAML )?(\w{2})([0-9]{1,2})\s")subject_baml289,9942 -subject_ms = re.compile("[^$]*\$\$ MS CDX OPTIONS: (IG|HY)(\d{2})[^-]*- REF[^\d]*([\d.]+)")subject_ms290,10016 -subject_nomura = re.compile("(?:Fwd:)?CDX (IG|HY)(\d{2}).*- REF:[^\d]*([\d.]+)")subject_nomura291,10108 -subject_gs = re.compile("GS (IG|HY)(\d{2}) 5y.*- Ref [^\d]*([\d.]+)")subject_gs292,10189 -subject_sg = re.compile("SG OPTIONS - CDX (IG|HY) S(\d{2}).* REF[^\d]*([\d.]+)")subject_sg293,10259 -def parse_email(email):parse_email295,10341 -def write_todb(swaption_stack, index_data):write_todb332,12239 -def get_email_list(date):get_email_list354,13126 -def pickle_drop_date(date):pickle_drop_date368,13537 - data_dir = os.path.join(os.getenv("DATA_DIR"), "swaptions")data_dir377,13841 - emails = [f for f in os.scandir(data_dir) if f.is_file()]emails378,13905 - swaption_stack = {}swaption_stack379,13967 - index_data = pd.DataFrame()index_data380,13991 - already_uploaded = pickle.load(fh)already_uploaded383,14074 - already_uploaded = {}already_uploaded385,14151 - index_data = index_data.append(fwd_index)index_data399,14683 - swaption_stack = pd.concat(swaption_stack, names=['quotedate', 'index', 'series'])swaption_stack408,15052 - swaption_stack = swaption_stack.reset_index()swaption_stack409,15139 - swaption_stack = swaption_stack.drop_duplicates(['quotedate', 'index', 'series', 'expiry', 'strike'])swaption_stack410,15189 - index_data = index_data.reset_index()index_data411,15295 - index_data = index_data.drop_duplicates(['quotedate', 'index', 'series', 'expiry'])index_data412,15337 +parse_emails.py,3053 + level=logging.WARNING,level16,379 + format='%(asctime)s %(message)s')format17,422 +def list_imm_dates(date):list_imm_dates19,477 +def makedf(r, indextype, quote_source):makedf27,657 +def parse_quotedate(fh, date_received):parse_quotedate55,1740 +def parse_refline(line):parse_refline72,2400 +def parse_baml(fh, indextype, series, quotedate, *args):parse_baml84,2855 +def parse_baml_block(fh, indextype):parse_baml_block110,3723 +def parse_ms_block(fh, indextype):parse_ms_block126,4188 +def parse_nomura_block(fh, indextype):parse_nomura_block158,5298 +def parse_sg_block(fh, indextype, expiration_dates):parse_sg_block181,6111 +def parse_gs_block(fh, indextype):parse_gs_block209,7204 +def parse_ms(fh, indextype, *args):parse_ms238,8023 +def parse_nomura(fh, indextype, *args):parse_nomura250,8416 + def aux(line, fh, indextype, option_stack):aux252,8478 +def parse_sg(fh, indextype, expiration_dates):parse_sg268,9087 +def parse_gs(fh, indextype, series, quotedate, ref):parse_gs278,9396 +subject_baml = re.compile("(?:Fwd:){0,2}(?:BAML )?(\w{2})([0-9]{1,2})\s")subject_baml301,10391 +subject_ms = re.compile("[^$]*\$\$ MS CDX OPTIONS: (IG|HY)(\d{2})[^-]*- REF[^\d]*([\d.]+)")subject_ms302,10465 +subject_nomura = re.compile("(?:Fwd:)?CDX (IG|HY)(\d{2}).*- REF:[^\d]*([\d.]+)")subject_nomura303,10557 +subject_gs = re.compile("GS (IG|HY)(\d{2}) 5y.*- Ref [^\d]*([\d.]+)")subject_gs304,10638 +subject_sg = re.compile("SG OPTIONS - CDX (IG|HY) S(\d{2}).* REF[^\d]*([\d.]+)")subject_sg305,10708 +def parse_email(email, date_received):parse_email307,10790 +def write_todb(swaption_stack, index_data):write_todb345,12712 + def gen_sql_str(query, table_name, columns):gen_sql_str346,12756 +def get_email_list(date):get_email_list370,13887 +def pickle_drop_date(date):pickle_drop_date384,14298 + data_dir = os.path.join(os.getenv("DATA_DIR"), "swaptions")data_dir393,14600 + emails = [f for f in os.scandir(data_dir) if f.is_file()]emails394,14664 + swaption_stack = {}swaption_stack395,14726 + index_data = pd.DataFrame()index_data396,14750 + already_uploaded = pickle.load(fh)already_uploaded399,14833 + already_uploaded = {}already_uploaded401,14910 + date_received = datetime.datetime.strptime(date_received, "%Y-%m-%d %H-%M-%S")date_received404,15011 + index_data = index_data.append(fwd_index)index_data417,15594 + swaption_stack = pd.concat(swaption_stack, names=['quotedate', 'index', 'series'])swaption_stack426,15963 + swaption_stack = swaption_stack.reset_index()swaption_stack427,16050 + swaption_stack = swaption_stack.drop_duplicates(['quotedate', 'index', 'series', 'expiry', 'strike'])swaption_stack428,16100 + swaption_stack = swaption_stack.set_index(['quotedate', 'index', 'series', 'expiry'])swaption_stack429,16206 + index_data = index_data.reset_index()index_data430,16296 + index_data = index_data.drop_duplicates(['quotedate', 'index', 'series', 'expiry'])index_data431,16338 populate_risk_numbers.py,404 basedir = "/home/share/CorpCDOs"basedir5,65 @@ -665,20 +778,17 @@ def convert(s):convert33,1066 def populate_risk(basedir, db):populate_risk36,1124 basedir = "/home/share/CorpCDOs"basedir62,2593 -saga.py,39 -def saga_option(x, y):saga_option1,0 - -pnl_explain.py,951 -def get_daycount(identifier, engine = dbengine("dawndb")):get_daycount7,112 -def pnl_explain(identifier, start_date = None, end_date = None,pnl_explain21,580 -def pnl_explain_list(id_list, start_date = None, end_date = None, engine = dbengine("dawndb")):pnl_explain_list101,5037 -def compute_tranche_factors(df, attach, detach):compute_tranche_factors105,5273 -def cds_explain(index, series, tenor, attach = np.nan, detach = np.nan,cds_explain114,5789 -def cds_explain_strat(strat, start_date, end_date, engine = dbengine("dawndb")):cds_explain_strat187,9770 - engine = dbengine("dawndb")engine216,11313 - subprime_list = get_list_range(engine, '2015-09-30', '2015-10-31', 'Subprime')subprime_list224,11647 - df_subprime = pnl_explain_list(subprime_list[['identifier', 'strategy']].to_records(index=False),df_subprime225,11730 - df_subprime = pd.concat(df_subprime, names=['identifier', 'strategy', 'date'])df_subprime227,11903 +pnl_explain.py,949 +def get_daycount(identifier, engine=dbengine("dawndb")):get_daycount7,112 +def pnl_explain(identifier, start_date = None, end_date = None,pnl_explain21,578 +def pnl_explain_list(id_list, start_date = None, end_date = None, engine = dbengine("dawndb")):pnl_explain_list101,5033 +def compute_tranche_factors(df, attach, detach):compute_tranche_factors105,5269 +def cds_explain(index, series, tenor, attach = np.nan, detach = np.nan,cds_explain114,5785 +def cds_explain_strat(strat, start_date, end_date, engine = dbengine("dawndb")):cds_explain_strat187,9766 + engine = dbengine("dawndb")engine216,11309 + subprime_list = get_list_range(engine, '2015-09-30', '2015-10-31', 'Subprime')subprime_list224,11643 + df_subprime = pnl_explain_list(subprime_list[['identifier', 'strategy']].to_records(index=False),df_subprime225,11726 + df_subprime = pd.concat(df_subprime, names=['identifier', 'strategy', 'date'])df_subprime227,11899 script_calibrate_tranches.py,605 n_int = 500n_int4,69 @@ -718,33 +828,48 @@ def get_mailinglist(name):get_mailinglist14,315 msg_alternative = MIMEMultipart('alternative')msg_alternative54,2237 name = " " + namename56,2309 -client.py,76 -def run():run10,119 - logger = logging.getLogger('intex')logger33,952 +client.py,236 +def run():run9,149 + logger = logging.getLogger('intex')logger31,903 + formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')formatter32,943 + sh = logging.StreamHandler(sys.stdout)sh35,1119 -position.py,769 -def get_list(engine, workdate=None, asset_class=None, include_unsettled=True):get_list11,239 -def get_list_range(engine, begin, end, asset_class=None):get_list_range25,1065 -def backpopulate_marks(begin_str='2015-01-15', end_str='2015-07-15'):backpopulate_marks38,1832 -def update_securities(engine, session, workdate):update_securities58,3135 -def init_fx(session, engine, startdate):init_fx76,4068 -def update_fx(engine, session, currencies):update_fx85,4551 -def populate_cashflow_history(engine, session, workdate=None):populate_cashflow_history103,5247 - engine = create_engine('postgresql://dawn_user@debian/dawndb')engine147,7627 - workdate = pd.Timestamp(sys.argv[1])workdate149,7718 - workdate = pd.datetime.today()workdate151,7773 +position.py,1541 +def get_list(engine, workdate=None, asset_class=None, include_unsettled=True):get_list14,290 +def get_list_range(engine, begin, end, asset_class=None):get_list_range28,1116 +def backpopulate_marks(begin_str='2015-01-15', end_str='2015-07-15'):backpopulate_marks41,1883 +def update_securities(engine, session, workdate):update_securities61,3186 +def init_fx(session, engine, startdate):init_fx80,4136 +def update_fx(conn, session, currencies):update_fx89,4619 +def init_swap_rates(conn, session, tenors=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30],init_swap_rates107,5279 +def init_swaption_vol(session,init_swaption_vol123,6031 +def split_tenor_expiry(ticker, vol_type='N'):split_tenor_expiry136,6550 +def insert_swaption_vol(data, conn, source, vol_type="N"):insert_swaption_vol146,6865 +def update_swaption_vol(conn, session,update_swaption_vol166,7830 +def update_swap_rates(conn, session,update_swap_rates205,9479 +def populate_cashflow_history(engine, session, workdate=None):populate_cashflow_history218,10109 + serenitas_conn = psycopg2.connect(database="serenitasdb",serenitas_conn263,12506 + user="serenitas_user",user264,12568 + host="debian")host265,12629 + dawn_engine = create_engine('postgresql://dawn_user@debian/dawndb')dawn_engine266,12682 + dawn_conn = dawn_engine.raw_connection()dawn_conn267,12754 + workdate = pd.Timestamp(sys.argv[1])workdate269,12825 + workdate = pd.datetime.today()workdate271,12880 -load_globeop_report.py,645 -def get_globs(fname, years=['2013', '2014', '2015', '2016']):get_globs8,119 -def valuation_reports():valuation_reports20,654 -def pnl_reports():pnl_reports43,1565 -def ts(s):ts61,2258 -def monthly_pnl_bycusip(df, strats):monthly_pnl_bycusip64,2297 - df_val = pd.read_hdf('globeop.hdf', 'valuation_report')df_val73,2679 - df_pnl = pd.read_hdf('globeop.hdf', 'pnl')df_pnl74,2739 - subprime_strats = ['MTG_GOOD', 'MTG_RW', 'MTG_IO','MTG_THRU', 'MTG_B4PR']subprime_strats76,2874 - clo_strats = ['CLO_BBB', 'CLO_AAA', 'CLO_BB20']clo_strats77,2952 - df_monthly = monthly_pnl_bycusip(df_pnl, subprime_strats)df_monthly82,3101 +load_globeop_report.py,851 +def get_globs(fname, years=['2013', '2014', '2015', '2016', '2017']):get_globs9,148 +def read_valuation_report(f):read_valuation_report21,703 +def valuation_reports():valuation_reports42,1493 +def read_pnl_report(f):read_pnl_report50,1910 +def pnl_reports():pnl_reports58,2257 +def read_cds_report(f, old_report=False):read_cds_report69,2695 +def cds_reports():cds_reports103,4463 +def monthly_pnl_bycusip(df, strats):monthly_pnl_bycusip113,4851 + df_val = pd.read_hdf('globeop.hdf', 'valuation_report')df_val121,5213 + df_pnl = pd.read_hdf('globeop.hdf', 'pnl')df_pnl122,5273 + subprime_strats = ['MTG_GOOD', 'MTG_RW', 'MTG_IO','MTG_THRU', 'MTG_B4PR']subprime_strats124,5410 + clo_strats = ['CLO_BBB', 'CLO_AAA', 'CLO_BB20']clo_strats125,5488 + df_monthly = monthly_pnl_bycusip(df_pnl, subprime_strats)df_monthly130,5637 markit/cds.py,238 logger = logging.getLogger(__name__)logger10,161 @@ -759,12 +884,12 @@ logger = logging.getLogger(__name__)logger9,129 def download_facility(workdate, payload):download_facility11,169 def insert_facility(conn, workdate):insert_facility18,531 def download_marks(conn, workdate, payload):download_marks39,1422 -def update_facility(conn, workdate, payload):update_facility59,2410 +def update_facility(conn, workdate, payload):update_facility59,2414 markit/rates.py,90 -def downloadMarkitIRData(download_date=datetime.date.today(),downloadMarkitIRData12,219 +def downloadMarkitIRData(download_date=datetime.date.today(),downloadMarkitIRData14,255 -markit/__main__.py,1328 +markit/__main__.py,1330 parser = argparse.ArgumentParser()parser20,529 group = parser.add_mutually_exclusive_group(required=True)group21,564 help="download markit loan data")help23,680 @@ -782,26 +907,35 @@ historical = Truehistorical33,1196 logger = logging.getLogger('markit')logger48,1606 fh = logging.FileHandler(filename=log_file)fh49,1643 formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')formatter50,1687 - payload={'LEGALENTITY': 'lmcg',payload56,1868 - payload = {'user': 'GuillaumeHorel',payload72,2412 - serenitasdb = dbconn('serenitasdb')serenitasdb83,2852 - engine = create_engine('postgresql://serenitas_user@debian/serenitasdb')engine87,2983 + payload = {'LEGALENTITY': 'lmcg',payload56,1868 + payload = {'user': 'GuillaumeHorel',payload72,2418 + serenitasdb = dbconn('serenitasdb')serenitasdb83,2858 + engine = create_engine('postgresql://serenitas_user@debian/serenitasdb')engine87,2989 + +markit/.ropeproject/config.py,90 +def set_prefs(prefs):set_prefs5,45 +def project_opened(project):project_opened110,4652 markit/utils.py,38 def default_date():default_date4,61 -markit/import_quotes.py,734 -logger = logging.getLogger(__name__)logger11,169 -def convert(x):convert13,207 - ['EU' + str(s) for s in range(19, 28)]index_list23,526 -DOC_CLAUSE_MAPPING14 = {'Full Restructuring': 'MM14',DOC_CLAUSE_MAPPING1425,579 -DOC_CLAUSE_MAPPING = {'Full Restructuring': 'MM',DOC_CLAUSE_MAPPING29,752 -def get_markit_bbg_mapping(database, basketid_list, workdate):get_markit_bbg_mapping33,913 -def get_basketids(database, index_list, workdate):get_basketids58,2251 -def get_current_tickers(database, workdate):get_current_tickers67,2534 -def insert_cds(database, workdate):insert_cds71,2715 -def insert_index(engine, workdate=None):insert_index105,4513 -def insert_tranche(engine, workdate=None):insert_tranche144,6770 +markit/import_quotes.py,807 +logger = logging.getLogger(__name__)logger12,197 +def convert(x):convert14,235 +def get_index_list(database, workdate):get_index_list20,333 +DOC_CLAUSE_MAPPING14 = {'Full Restructuring': 'MM14',DOC_CLAUSE_MAPPING1429,679 +DOC_CLAUSE_MAPPING = {'Full Restructuring': 'MM',DOC_CLAUSE_MAPPING33,852 +def get_markit_bbg_mapping(database, basketid_list, workdate):get_markit_bbg_mapping37,1013 +def get_bbg_tickers(database, basketid_list, workdate):get_bbg_tickers62,2363 +def get_basketids(database, index_list, workdate):get_basketids70,2698 +def get_current_tickers(database, workdate):get_current_tickers77,2953 +def insert_cds(database, workdate):insert_cds82,3186 +def insert_index(engine, workdate=None):insert_index113,4858 +def insert_tranche(engine, workdate=None):insert_tranche150,7026 + +exchange.py,164 +def get_account(email_address):get_account5,108 +def get_msgs(account=None, email_address='ghorel@lmcg.com', count=None, path=['GS', 'Swaptions'],get_msgs13,496 calibrate_tranches.py,1441 n_int = 500n_int10,147 @@ -844,42 +978,96 @@ sentinel={}sentinel93,3479 table_rows = table.findAll('tr')table_rows105,3844 fields = row.findAll('td')fields107,3928 -calibrate_swaption.py,464 -serenitas_engine = dbengine('serenitasdb')serenitas_engine9,206 -def get_data(index, series, date = datetime.date.min):get_data11,250 -def get_data_latest():get_data_latest26,967 -def calib(option, ref, strike, pay_bid, pay_offer, rec_bid, rec_offer):calib43,1751 -def calibrate(index_type=None, series=None, date=None, nproc=4, latest=False):calibrate64,2459 - parser = argparse.ArgumentParser()parser86,3527 - args = parser.parse_args()args92,3964 +collateral_calc.py,524 +DAILY_DIR = Path(os.environ["DAILY_DIR"])DAILY_DIR10,236 +def download_files(d=None):download_files12,279 +def download_emails():download_emails37,1266 +def sg_collateral(d):sg_collateral47,1656 +def ms_collateral(d):ms_collateral70,2853 +def send_email(account, df_ms, df_sg):send_email83,3330 + d = (pd.Timestamp.today() - BDay()).normalize()d102,4000 + df_ms = ms_collateral(d - BDay())df_ms104,4074 + df_sg = sg_collateral(d)df_sg105,4112 + account = get_account('ghorel@lmcg.com')account106,4141 -backfill_index.py,589 -engine = create_engine('postgresql://serenitas_user@debian/serenitasdb')engine2,54 -metadata = MetaData(bind = engine)metadata5,148 -index_quotes = Table('index_quotes', metadata, autoload=True)index_quotes6,183 -series=[9]series8,283 -tenor = ['3yr', '5yr', '7yr']tenor10,333 -index_type ='HY'index_type11,363 - index = "{0}{1}".format(index_type.lower(), s)index15,418 - stmt = index_quotes.delete().where((index_quotes.c.index==index_type) &stmt16,473 - df = pd.read_excel('/home/share/CorpCDOs/index historical.xlsx', "{0} {1}".format(index, t))df20,724 +calibrate_swaption.py,503 +serenitas_engine = dbengine('serenitasdb')serenitas_engine11,259 +def get_data(index, series, date=datetime.date.min):get_data13,303 +def get_data_latest():get_data_latest24,936 +def calib(option, ref, strike, pay_bid, pay_offer, rec_bid, rec_offer):calib37,1653 +def MaybePool(nproc):MaybePool59,2366 +def calibrate(index_type=None, series=None, date=None, nproc=4, latest=False):calibrate62,2434 + parser = argparse.ArgumentParser()parser86,3596 + args = parser.parse_args()args92,4027 + +backfill_index.py,335 +serenitasdb = dbconn('serenitasdb')serenitasdb3,76 +series=[18]series7,171 +tenor = ['5yr', '7yr', '10yr']tenor9,222 +index_type ='IG'index_type10,253 + index = "{0}{1}".format(index_type.lower(), s)index14,308 + df = pd.read_excel('/home/share/CorpCDOs/index historical.xlsx', "{0} {1}".format(index, t))df15,363 flask-run.py,57 mod = importlib.import_module(sys.argv[1])mod8,164 +rmbs/CRT_data.py,99 +def get_CRT_notional():get_CRT_notional10,159 +def calc_CRT_notional():calc_CRT_notional36,1221 + +rmbs/marketing.py,118 +def ver_one():ver_one6,87 +def plot_strat():plot_strat29,1253 +def wavg(group, avg_name, weight_name):wavg54,2014 + +load_refentity.py,529 +parser = etree.XMLParser(remove_blank_text=True)parser6,100 +def todict(xml, uselist=set()):todict9,183 +def dispatch_parsing(col, uselist):dispatch_parsing27,768 +def insert_refentity(fname):insert_refentity36,1012 +def parse_prospectus(xml):parse_prospectus62,2292 +def insert_refobligation(fname):insert_refobligation65,2379 +def get_date(f):get_date105,4687 + base_dir = Path('/home/serenitas/CorpCDOs/Tranche_data/RED_reports/Deltas')base_dir113,4921 + f = base_dir / download_report(report)[0]f115,5061 + +markit_tranche_quotes.py,726 +params = {"username": "serenitasreports",params8,88 +r = requests.get("https://quotes.markit.com/reports/runReport",r14,299 + params=params)params15,363 +f = io.StringIO(r.text)f17,396 +index_mapping = {'ITRAXX-Europe': 'EU',index_mapping21,478 +def get_latest_quote_id(db):get_latest_quote_id31,982 +def convert_float(s):convert_float37,1157 +serenitasdb = dbconn('serenitasdb')serenitasdb40,1215 +runningdict1 = {0: 500, 3:100, 7:100, 15: 25}runningdict142,1252 +runningdict2 = {0: 500, 3:500, 7:500, 10:100, 15:100, 30:100}runningdict243,1298 +markit_id = get_latest_quote_id(serenitasdb)markit_id44,1360 +headers = [h.lower() for h in next(f).split(",")]headers46,1406 +count = 0count47,1456 + xmltotab.py,213 ns = '{urn:schemas-microsoft-com:office:spreadsheet}'ns4,35 doc = etree.parse('/home/share/guillaume/grid1_1cz1rlvt.xml')doc6,90 tree = doc.getroot()tree7,152 csvwriter = csv.writer(fh)csvwriter10,210 -task_runner.py,77 -def run():run12,210 - logger = logging.getLogger('intex')logger36,1066 +task_runner.py,75 +def run():run9,172 + logger = logging.getLogger('intex')logger32,934 + +tasks.py,356 +def build_portfolios(workdate, dealname, reinvflag):build_portfolios8,124 +def build_scenarios(workdate, dealname, reinvflag):build_scenarios15,472 +class Rpc(object):Rpc22,818 + def __init__(self, fun, args):__init__23,837 + def __str__(self):__str__27,921 + def __call__(self):__call__30,1025 + def from_json(cls, s):from_json34,1107 -tasks.py,148 -def build_portfolio(workdate, dealname, reinvflag):build_portfolio5,82 -def build_scenarios(workdate, dealname, reinvflag):build_scenarios13,531 +graphics.py,227 +def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name='shiftedcmap'):shiftedColorMap5,78 +def plot_time_color_map(df, spread_shock, attr="pnl", path=".", color_map=cm.RdYlGn, index='IG'):plot_time_color_map57,1854 adj_index_price.py,639 index='HY'index4,86 @@ -892,7 +1080,7 @@ index_quotes= Table('index_quotes', metadata, autoload=True)index_quotes11,312 r = factors.ix[i].indexfactor/factors.ix[i+1].indexfactorr28,1248 stmt = index_quotes.update().where((index_quotes.c.date==bindparam('b_date')) &stmt34,1562 -intex/intex_scenarios.py,1335 +intex/intex_scenarios.py,1343 logger = logging.getLogger(__name__)logger16,196 pattern1 = re.compile("REINVEST\[\w+::REINV_TBA(\d)\]\[DEAL,(\d+)\]=.*$")pattern118,234 pattern2 = re.compile("(STANDARD_VAR\[)\w+(::#REINV_END,\d+\]=)(\d.*$)")pattern220,325 @@ -904,14 +1092,14 @@ pattern9 = re.compile("(?P<a>SEVERITY\[\w+,\d+\]=)mkt\(70\)")pattern926,671 global_reinvfloatpercentage = 84global_reinvfloatpercentage29,785 global_reinvfixedpercentage = 16global_reinvfixedpercentage30,818 def get_reinv_assets(conn, dealname, workdate):get_reinv_assets32,852 -def get_recovery(conn, dealname, workdate, defaultrecovery = 50):get_recovery42,1183 -def get_reinvenddate(conn, dealname):get_reinvenddate58,1844 -def generate_scenarios(workdate, dealname, conn):generate_scenarios69,2217 - workdate = sys.argv[1]workdate229,10433 - workdate = str(datetime.date.today())workdate231,10474 - dealnames = sys.argv[2:]dealnames233,10546 - dealnames = [d.split(".")[0] for d indealnames235,10589 - ET = dbconn('etdb')ET239,10834 +def get_recovery(conn, dealname, workdate, defaultrecovery=50):get_recovery42,1205 +def get_reinvenddate(conn, dealname, workdate):get_reinvenddate58,1868 +def generate_scenarios(workdate, dealname, conn):generate_scenarios69,2258 + workdate = sys.argv[1]workdate231,10580 + workdate = str(datetime.date.today())workdate233,10621 + dealnames = sys.argv[2:]dealnames235,10693 + dealnames = [d.split(".")[0] for d indealnames237,10736 + ET = dbconn('etdb')ET241,10981 intex/__init__.py,0 @@ -921,113 +1109,233 @@ def convertToNone(s):convertToNone14,240 def insert_new_cusip(conn, line):insert_new_cusip17,310 def upload_cusip_data(conn, filename):upload_cusip_data38,1327 def upload_deal_data(conn, filename):upload_deal_data100,4288 - workdate = sys.argv[1]workdate182,8597 - workdate = str(datetime.date.today())workdate184,8638 - files = [os.path.join(os.environ['DATA_DIR'], "Indicative_" + workdate, f) for f infiles185,8684 - cusip_files = [f for f in files if "TrInfo" in f]cusip_files187,8861 - deal_files = [f for f in files if "TrInfo" not in f]deal_files188,8915 + workdate = sys.argv[1]workdate183,8568 + workdate = str(datetime.date.today())workdate185,8609 + files = [os.path.join(os.environ['DATA_DIR'], "Indicative_" + workdate, f) for f infiles186,8655 + cusip_files = [f for f in files if "TrInfo" in f]cusip_files188,8832 + deal_files = [f for f in files if "TrInfo" not in f]deal_files189,8886 intex/__main__.py,150 logger = logging.getLogger('intex')logger6,110 workdate = sys.argv[1]workdate10,212 workdate = str(datetime.date.today())workdate12,245 -intex/load_intex_collateral.py,359 -logger = logging.getLogger(__name__)logger11,212 -fields = ['Asset Name', 'Issuer', 'Contributed Balance', 'Asset Maturity Date',fields13,250 -def convertToNone(s):convertToNone21,759 -def windows1252_encoder(fh):windows1252_encoder24,814 -def upload_data(conn, dealnames, workdate):upload_data28,922 -def intex_data(conn, workdate):intex_data136,6670 +intex/.ropeproject/config.py,90 +def set_prefs(prefs):set_prefs5,45 +def project_opened(project):project_opened110,4652 + +intex/load_intex_collateral.py,249 +logger = logging.getLogger(__name__)logger12,237 +fields = ['Asset Name', 'Issuer', 'Contributed Balance', 'Asset Maturity Date',fields14,275 +def upload_data(conn, workdate):upload_data22,809 +def intex_data(conn, workdate):intex_data142,7121 intex/common.py,53 def sanitize_float(intex_float):sanitize_float3,11 analytics/__init__.py,0 -analytics/option.py,2486 -def calib(S0, fp, exercise_date, exercise_date_settle,calib30,756 -def memoize(f):memoize38,1087 - def cached_f(*args, **kwargs):cached_f40,1117 -def ATMstrike(index, exercise_date):ATMstrike51,1400 -class BlackSwaption(ForwardIndex):BlackSwaption70,1923 - __slots__ = ['_forward_yc', '_T', '_G', '_strike', 'option_type',__slots__72,1983 - def __init__(self, index, exercise_date, strike, option_type="payer",__init__75,2122 - def from_tradeid(cls, trade_id, index=None):from_tradeid88,2588 - def exercise_date(self):exercise_date105,3395 - def exercise_date(self, d):exercise_date109,3484 - def strike(self):strike116,3732 - def strike(self, K):strike123,3898 - def atm_strike(self):atm_strike134,4335 - def moneyness(self):moneyness142,4575 - def direction(self):direction146,4660 - def direction(self, d):direction153,4809 - def intrinsic_value(self):intrinsic_value162,5065 - def __hash__(self):__hash__167,5283 - def pv(self):pv172,5471 - def pv(self, val):pv186,6018 - def handle(x):handle196,6395 - def reset_pv(self):reset_pv208,6689 - def pnl(self):pnl212,6764 - def delta(self):delta222,7100 - def T(self):T237,7582 - def gamma(self):gamma244,7754 - def theta(self):theta257,8091 - def vega(self):vega265,8262 - def DV01(self):DV01274,8463 - def breakeven(self):breakeven284,8722 - def __repr__(self):__repr__299,9320 - def __str__(self):__str__327,10943 -class Swaption(BlackSwaption):Swaption330,11028 - __slots__ = ["_cache", "_Z", "_w"]__slots__331,11059 - def __init__(self, index, exercise_date, strike, option_type="payer",__init__332,11098 - def __hash__(self):__hash__338,11351 - def pv(self):pv343,11437 - def pv(self, val):pv377,13031 - def handle(x):handle381,13129 - def __setpv_black(self, val):__setpv_black397,13522 - pv_black = property(None, __setpv_black)pv_black407,13903 -def compute_vol(option, strike, mid):compute_vol410,13950 -class VolatilitySurface(ForwardIndex):VolatilitySurface419,14135 - def __init__(self, index_type, series, tenor='5yr', trade_date=datetime.date.today()):__init__420,14174 - def vol(self, T, moneyness, surface_id):vol444,15500 - def list(self, source=None, option_type=None, model=None):list448,15665 - def __iter__(self):__iter__458,16043 - def plot(self, surface_id):plot461,16106 - def __getitem__(self, surface_id):__getitem__472,16544 +analytics/db.py,47 +_engine = dbengine('serenitasdb')_engine2,32 + +analytics/option.py,4190 +def calib(S0, fp, exercise_date, exercise_date_settle,calib36,938 +def memoize(f):memoize44,1269 + def cached_f(*args, **kwargs):cached_f46,1299 +def ATMstrike(index, exercise_date):ATMstrike57,1582 +class BlackSwaption(ForwardIndex):BlackSwaption76,2105 + __slots__ = ['_forward_yc', '_T', '_G', '_strike', 'option_type',__slots__78,2165 + def __init__(self, index, exercise_date, strike, option_type="payer",__init__81,2304 + def __setstate__(self, state):__setstate__94,2793 + def from_tradeid(cls, trade_id, index=None):from_tradeid100,2963 + def exercise_date(self):exercise_date117,3770 + def exercise_date(self, d):exercise_date121,3859 + def strike(self):strike132,4311 + def strike(self, K):strike139,4477 + def atm_strike(self):atm_strike150,4914 + def moneyness(self):moneyness158,5154 + def direction(self):direction163,5333 + def direction(self, d):direction170,5482 + def intrinsic_value(self):intrinsic_value179,5738 + def __hash__(self):__hash__184,5956 + def pv(self):pv189,6144 + def tail_prob(self):tail_prob203,6690 + def pv(self, val):pv216,7239 + def handle(x):handle226,7616 + def reset_pv(self):reset_pv238,7910 + def pnl(self):pnl242,7985 + def delta(self):delta252,8321 + def T(self):T267,8803 + def gamma(self):gamma274,8978 + def theta(self):theta287,9315 + def vega(self):vega295,9486 + def DV01(self):DV01304,9687 + def breakeven(self):breakeven314,9946 + def __repr__(self):__repr__329,10544 + def __str__(self):__str__357,12167 +class Swaption(BlackSwaption):Swaption360,12252 + __slots__ = ["_cache", "_Z", "_w"]__slots__361,12283 + def __init__(self, index, exercise_date, strike, option_type="payer",__init__362,12322 + def __hash__(self):__hash__368,12575 + def pv(self):pv373,12661 + def pv(self, val):pv407,14255 + def handle(x):handle411,14353 + def __setpv_black(self, val):__setpv_black427,14746 + pv_black = property(None, __setpv_black)pv_black437,15127 +def _get_keys(df, models=["black", "precise"]):_get_keys439,15173 +class QuoteSurface():QuoteSurface450,15641 + def __init__(self, index_type, series, tenor='5yr', trade_date=datetime.date.today()):__init__451,15663 + def list(self, source=None):list473,16855 +class VolSurface(QuoteSurface):VolSurface483,17272 + def __init__(self, index_type, series, tenor='5yr', trade_date=datetime.date.today()):__init__484,17304 + def __getitem__(self, surface_id):__getitem__488,17488 + def vol(self, T, moneyness, surface_id):vol502,18293 + def plot(self, surface_id):plot506,18448 +def _compute_vol(option, strike, mid):_compute_vol521,18985 +def _calibrate(index, quotes, option_model, option_type):_calibrate530,19233 +class ModelBasedVolSurface(VolSurface):ModelBasedVolSurface548,19951 + def __init__(self, index_type, series, tenor='5yr', trade_date=datetime.date.today()):__init__549,19991 + def list(self, source=None, option_type=None):list561,20645 + def __getitem__(self, surface_id):__getitem__570,20992 + def plot(self, surface_id):plot586,21798 +class BlackSwaptionVolSurface(ModelBasedVolSurface):BlackSwaptionVolSurface599,22337 +class SwaptionVolSurface(ModelBasedVolSurface):SwaptionVolSurface602,22400 +def _forward_annuity(expiry, index):_forward_annuity606,22481 +class ProbSurface(QuoteSurface):ProbSurface616,22934 + def __init__(self, index_type, series, tenor='5yr', trade_date=datetime.date.today()):__init__618,22968 + def __getitem__(self, surface_id):__getitem__623,23229 + def tail_prob(self, T, strike, surface_id):tail_prob658,25280 + def plot(self, surface_id):plot662,25443 +class MyInterp:MyInterp678,26047 + def __init__(self, T, f):__init__679,26063 + def __call__(self, x, y):__call__684,26170 +def calib_sabr(x, option, strikes, pv, beta):calib_sabr693,26486 +class SABRVolSurface(VolSurface):SABRVolSurface704,26814 + def __init__(self, index_type, series, tenor='5yr',__init__705,26848 + def list(self, source=None, option_type=None):list714,27226 + def __getitem__(self, surface_id):__getitem__723,27544 analytics/portfolio.py,1022 -serenitasdb = dbengine('serenitasdb')serenitasdb8,185 -def portf_repr(method):portf_repr10,224 - def f(*args):f11,248 -class Portfolio:Portfolio31,1084 - def __init__(self, trades):__init__32,1101 - def pnl(self):pnl52,1874 - def pnl_list(self):pnl_list56,1955 - def pv(self):pv60,2038 - def pv_list(self):pv_list64,2117 - def reset_pv(self):reset_pv67,2184 - def trade_date(self):trade_date72,2278 - def trade_date(self, d):trade_date76,2360 - def mark(self, source_list=[], option_type=None, model="black", surface_id=None):mark85,2653 - def ref(self):ref113,4119 - def ref(self, val):ref120,4300 - def spread(self):spread134,4798 - def spread(self, val):spread141,4991 - def delta(self):delta155,5504 - def gamma(self):gamma162,5745 - def dv01(self):dv01166,5860 - def theta(self):theta170,5943 - def _todf(self):_todf173,6014 - __repr__ = portf_repr('string')__repr__192,6948 - _repr_html_ = portf_repr('html')_repr_html_194,6985 +serenitasdb = dbengine('serenitasdb')serenitasdb8,174 +def portf_repr(method):portf_repr10,213 + def f(*args):f11,237 +class Portfolio:Portfolio31,1073 + def __init__(self, trades):__init__32,1090 + def pnl(self):pnl47,1791 + def pnl_list(self):pnl_list51,1872 + def pv(self):pv55,1955 + def pv_list(self):pv_list59,2034 + def reset_pv(self):reset_pv62,2101 + def trade_date(self):trade_date67,2195 + def trade_date(self, d):trade_date71,2277 + def mark(self, source_list=[], option_type=None, model="black", surface_id=None):mark80,2570 + def ref(self):ref106,3886 + def ref(self, val):ref113,4067 + def spread(self):spread127,4565 + def spread(self, val):spread134,4758 + def delta(self):delta148,5271 + def gamma(self):gamma155,5512 + def dv01(self):dv01159,5627 + def theta(self):theta163,5710 + def _todf(self):_todf166,5781 + __repr__ = portf_repr('string')__repr__185,6696 + _repr_html_ = portf_repr('html')_repr_html_187,6733 + +analytics/black.py,268 +def d1(F, K, sigma, T):d16,114 +def d2(F, K, sigma, T):d29,207 +def d12(F, K, sigma, T):d1213,316 +def cnd_erf(d):cnd_erf22,524 +def black(F, K, T, sigma, payer=True):black27,684 +def Nx(F, K, sigma, T):Nx35,968 +def bachelier(F, K, T, sigma):bachelier38,1065 -analytics/black.py,184 -def d1(F, K, sigma, T):d15,85 -def d2(F, K, sigma, T):d28,178 -def d12(F, K, sigma, T):d1212,287 -def cnd_erf(d):cnd_erf21,495 -def black(F, K, T, sigma, payer=True):black26,655 +analytics/sabr.py,899 +def sabr_lognormal(alpha, rho, nu, F, K, T):sabr_lognormal7,178 +def sabr_normal(alpha, rho, nu, F, K, T):sabr_normal19,653 +def sabr(alpha, beta, rho, nu, F, K, T):sabr37,1399 + underlying = Index.from_name("IG", 28, "5yr")underlying64,2521 + exercise_date = datetime.date(2017, 9, 20)exercise_date66,2602 + option = BlackSwaption(underlying, exercise_date, 70)option67,2650 + strikes = np.array([50, 55, 57.5, 60, 62.5, 65, 67.5, 70, 75, 80, 85])strikes69,2711 + pvs = np.array([44.1, 25.6, 18.9, 14, 10.5, 8.1, 6.4, 5, 3.3, 2.2, 1.5]) * 1e-4pvs70,2787 + strikes = np.array([50, 55, 57.5, 60, 62.5, 65, 67.5, 70, 75, 80, 85, 90, 95, 100])strikes72,2874 + pvs = np.array([53.65, 37.75, 31.55, 26.45, 22.25, 18.85, 16.15, 13.95, 10.55,pvs73,2963 + def calib(x, option, strikes, pv, beta):calib76,3108 + prog = least_squares(calib, (0.3, 0.5, 0.3),prog87,3469 + +analytics/.ropeproject/config.py,90 +def set_prefs(prefs):set_prefs5,45 +def project_opened(project):project_opened110,4652 + +analytics/tranche_functions.py,1895 +def wrapped_ndpointer(*args, **kwargs):wrapped_ndpointer11,367 + def from_param(cls, obj):from_param13,445 +libloss = np.ctypeslib.load_library("lossdistrib", os.path.join(libloss19,640 +def GHquad(n):GHquad112,4022 +def stochasticrecov(R, Rtilde, Z, w, rho, porig, pmod):stochasticrecov116,4102 +def fitprob(Z, w, rho, p0):fitprob122,4398 +def BCloss_recov_dist(defaultprob, issuerweights, recov, rho, Z, w, Ngrid=101, defaultflag=False):BCloss_recov_dist127,4574 +def BCloss_recov_trunc(defaultprob, issuerweights, recov, rho, K, Z, w, Ngrid=101, defaultflag=False):BCloss_recov_trunc137,5131 +def lossdistrib_joint(p, pp, w, S, Ngrid=101, defaultflag=False):lossdistrib_joint149,5772 +def lossdistrib_joint_Z(p, pp, w, S, rho, Ngrid=101, defaultflag=False, nZ=500):lossdistrib_joint_Z189,6954 +def joint_default_averagerecov_distrib(p, S, Ngrid=101):joint_default_averagerecov_distrib246,8597 +def adjust_attachments(K, losstodate, factor):adjust_attachments277,9510 +def trancheloss(L, K1, K2):trancheloss284,9710 +def trancherecov(R, K1, K2):trancherecov287,9796 +def tranche_cl(L, R, cs, K1, K2, scaled=False):tranche_cl290,9891 +def tranche_pl(L, cs, K1, K2, scaled=False):tranche_pl303,10390 +def tranche_pv(L, R, cs, K1, K2):tranche_pv315,10771 +def credit_schedule(tradedate, tenor, coupon, yc, enddate=None):credit_schedule318,10874 +def cds_accrued(tradedate, coupon):cds_accrued336,11677 +def dist_transform(q):dist_transform347,12087 +def dist_transform2(q):dist_transform2362,12501 +def compute_pv(q, strike):compute_pv376,12902 +def average_recov(p, R, Ngrid):average_recov383,13104 + n_issuers = 100n_issuers411,14110 + p = np.random.rand(n_issuers)p412,14130 + R = np.random.rand(n_issuers)R413,14164 + Rbar = joint_default_averagerecov_distrib(p, 1-R, 1001)Rbar414,14198 + Rbar_slow = average_recov(p, R, 1001)Rbar_slow415,14258 + +analytics/index_data.py,926 +def insert_quotes():insert_quotes15,350 +def get_index_quotes(index=None, series=None, tenor=None, from_date=None, years=3):get_index_quotes48,2099 + def make_str(key, val):make_str56,2443 + def make_params(args):make_params72,2977 +def index_returns(df=None, index=None, series=None, tenor=None, from_date=None, years=3, per=1):index_returns89,3673 +def get_singlenames_quotes(indexname, date):get_singlenames_quotes129,5434 +def build_curve(r, tenors, currency="USD"):build_curve135,5652 +def build_curves(quotes, args):build_curves149,6222 +def build_curves_dist(quotes, args, workers=4):build_curves_dist152,6323 +def _get_singlenames_curves(index_type, series, trade_date):_get_singlenames_curves160,6629 +def get_singlenames_curves(index_type, series, trade_date):get_singlenames_curves168,7003 +def get_tranche_quotes(index_type, series, tenor, date=datetime.date.today()):get_tranche_quotes175,7329 + +analytics/tranche_basket.py,1697 +class TrancheBasket(BasketIndex):TrancheBasket18,633 + def __init__(self, index_type: str, series: int, tenor: str, *,__init__19,667 + def tranche_factors(self):tranche_factors66,3027 + def _get_quotes(self, spread=None):_get_quotes69,3127 + def _snacpv(self, spread, coupon, recov):_snacpv82,3747 + def default_prob(self):default_prob88,4035 + def tranche_legs(self, K, rho, complement=False, shortened=0):tranche_legs92,4243 + def tranche_pvs(self, protection=False, complement=False, shortened=0):tranche_pvs115,5337 + def index_pv(self, discounted=True, shortened=0):index_pv135,6036 + def expected_loss(self, discounted=True, shortened=0):expected_loss157,6935 + def expected_loss_trunc(self, K, rho=None, shortened=0):expected_loss_trunc171,7406 + def probability_trunc(self, K, rho=None, shortened=0):probability_trunc188,8112 + def recovery_rates(self):recovery_rates202,8651 + def tranche_durations(self, complement=False):tranche_durations205,8750 + def _row_names(self):_row_names214,9120 + def tranche_thetas(self, complement=False, shortened=4, method='ATM'):tranche_thetas219,9312 + def tranche_fwd_deltas(self, complement=False, shortened=4, method='ATM'):tranche_fwd_deltas228,9795 + def tranche_deltas(self, complement=False):tranche_deltas239,10208 + def build_skew(self, skew_type="bottomup"):build_skew261,11131 + def aux(rho, obj, K, quote, spread, complement):aux265,11275 + def map_skew(self, index2, method="ATM", shortened=0):map_skew298,12825 + def aux(x, index1, el1, index2, el2, K2, shortened):aux299,12884 + def aux2(x, index1, index2, K2, shortened):aux2308,13292 analytics/scenarios.py,403 def run_swaption_scenarios(swaption, date_range, spread_shock, vol_shock,run_swaption_scenarios11,264 @@ -1036,67 +1344,120 @@ def _aux(portf, curr_vols, params, vs):_aux56,1849 def MaybePool(nproc):MaybePool62,2068 def run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock,run_portfolio_scenarios65,2136 -analytics/index.py,2582 -engine = dbengine('serenitasdb')engine23,665 -def g(index, spread, exercise_date, forward_yc=None, pv=0.):g25,700 -def _key_from_index(index):_key_from_index43,1571 -class Index(object):Index49,1755 - __slots__ = ['fixed_rate', 'notional', '_start_date', '_end_date',__slots__51,1830 - def __init__(self, start_date, end_date, recovery, fixed_rate,__init__58,2321 - def __hash__(self):__hash__95,3711 - def start_date(self):start_date99,3824 - def end_date(self):end_date103,3897 - def start_date(self, d):start_date107,3975 - def end_date(self, d):end_date113,4184 - def spread(self):spread119,4386 - def direction(self):direction125,4535 - def direction(self, d):direction132,4687 - def _update(self):_update140,4931 - def spread(self, s):spread157,5847 - def flat_hazard(self):flat_hazard165,6061 - def pv(self):pv171,6225 - def pv(self, val):pv175,6333 - def accrued(self):accrued181,6567 - def days_accrued(self):days_accrued186,6721 - def clean_pv(self):clean_pv190,6804 - def price(self):price194,6923 - def price(self, val):price198,6990 - def ref(self):ref220,8081 - def ref(self, val):ref227,8225 - def DV01(self):DV01234,8370 - def theta(self):theta242,8565 - def IRDV01(self):IRDV01253,9013 - def rec_risk(self):rec_risk272,9585 - def jump_to_default(self):jump_to_default285,9965 - def risky_annuity(self):risky_annuity290,10125 - def trade_date(self):trade_date294,10220 - def trade_date(self, d):trade_date301,10421 - def reset_pv(self):reset_pv329,11657 - def pnl(self):pnl334,11798 - def notify(self):notify344,12241 - def observe(self, obj):observe348,12325 - def mark(self):mark351,12389 - def from_name(cls, index=None, series=None, tenor=None, trade_date=datetime.date.today(),from_name367,13090 - def from_tradeid(cls, trade_id):from_tradeid417,15492 - def __repr__(self):__repr__438,16351 -class ForwardIndex(object):ForwardIndex483,18901 - __slots__ = ['index', 'forward_date', 'exercise_date_settle', 'df',__slots__484,18929 - def __init__(self, index, forward_date):__init__487,19104 - def from_name(cls, index_type, series, tenor, forward_date,from_name499,19558 - def forward_annuity(self):forward_annuity505,19826 - def forward_pv(self):forward_pv509,19909 - def forward_spread(self):forward_spread513,19982 - def ref(self):ref517,20069 - def ref(self, val):ref521,20135 - def __hash__(self):__hash__524,20189 - def _update(self, *args):_update527,20313 +analytics/cms_spread.py,907 +def CMS_spread(T_alpha, X, beta, gamma):CMS_spread32,1322 +def f(v, X, S_alpha_beta, S_alpha_gamma, mu_beta, mu_gamma, T_alpha, rho):f36,1416 +def h(v, X, S_alpha_beta, mu_beta, sigma_alpha_beta, T_alpha):h47,2017 +def get_fixings(conn, tenor1, tenor2, fixing_date=None):get_fixings52,2239 +def build_spread_index(tenor1, tenor2):build_spread_index74,3113 +def get_swaption_vol_data(source="ICPL", vol_type=VolatilityType.ShiftedLognormal,get_swaption_vol_data81,3413 +def get_swaption_vol_surface(date, vol_type):get_swaption_vol_surface100,4097 +def get_swaption_vol_matrix(date, data, vol_type=VolatilityType.ShiftedLognormal):get_swaption_vol_matrix105,4356 +def quantlib_model(date, spread_index, yc, cap, rho, maturity, mean_rev=0.,quantlib_model124,5226 +def plot_surf(surf, tenors):plot_surf146,6310 +def globeop_model(date, spread_index, yc, strike, rho, maturity,globeop_model152,6489 + +analytics/index.py,2689 +def g(index, spread, exercise_date, forward_yc=None, pv=None):g24,688 +class Index(object):Index52,1980 + __slots__ = ['fixed_rate', 'notional', '_start_date', '_end_date',__slots__54,2055 + def __init__(self, start_date, end_date, recovery, fixed_rate,__init__62,2598 + def __hash__(self):__hash__97,4009 + def __getstate__(self):__getstate__100,4108 + def __setstate__(self, state):__setstate__103,4203 + def start_date(self):start_date109,4369 + def end_date(self):end_date113,4442 + def start_date(self, d):start_date117,4520 + def end_date(self, d):end_date123,4729 + def spread(self):spread129,4931 + def direction(self):direction135,5080 + def direction(self, d):direction142,5232 + def _update(self):_update150,5476 + def spread(self, s):spread167,6392 + def flat_hazard(self):flat_hazard175,6606 + def pv(self):pv181,6770 + def pv(self, val):pv185,6878 + def accrued(self):accrued191,7112 + def days_accrued(self):days_accrued196,7266 + def clean_pv(self):clean_pv200,7349 + def price(self):price204,7468 + def price(self, val):price208,7535 + def ref(self):ref230,8626 + def ref(self, val):ref237,8770 + def DV01(self):DV01244,8915 + def theta(self):theta252,9110 + def IRDV01(self):IRDV01263,9558 + def rec_risk(self):rec_risk282,10163 + def jump_to_default(self):jump_to_default295,10543 + def risky_annuity(self):risky_annuity300,10703 + def trade_date(self):trade_date304,10798 + def trade_date(self, d):trade_date311,10999 + def reset_pv(self):reset_pv327,11687 + def pnl(self):pnl332,11828 + def notify(self):notify342,12271 + def observe(self, obj):observe346,12355 + def mark(self):mark349,12416 + def factor(self):factor364,13074 + def version(self):version372,13270 + def from_name(cls, index=None, series=None, tenor=None, trade_date=datetime.date.today(),from_name380,13475 + def from_tradeid(cls, trade_id):from_tradeid435,16138 + def __repr__(self):__repr__464,17433 +class ForwardIndex(object):ForwardIndex509,19983 + __slots__ = ['index', 'forward_date', 'exercise_date_settle', 'df',__slots__510,20011 + def __init__(self, index, forward_date, observer=True):__init__513,20186 + def from_name(cls, index_type, series, tenor, forward_date,from_name526,20680 + def forward_annuity(self):forward_annuity532,20948 + def forward_pv(self):forward_pv536,21031 + def forward_spread(self):forward_spread540,21104 + def ref(self):ref544,21191 + def ref(self, val):ref548,21257 + def __hash__(self):__hash__551,21311 + def _update(self, *args):_update554,21435 + +analytics/utils.py,471 +tenor_t = CategoricalDtype(['3yr', '5yr', '7yr', '10yr'], ordered=True)tenor_t10,289 +def GHquad(n):GHquad12,362 +def previous_twentieth(d):previous_twentieth17,485 +def next_twentieth(d):next_twentieth26,689 +def third_wednesday(d):third_wednesday35,894 +def next_third_wed(d):next_third_wed41,1099 +def roll_date(d, tenor, nd_array=False):roll_date48,1251 + def kwargs(t):kwargs51,1380 +def build_table(rows, format_strings, row_format):build_table94,3058 + +analytics/basket_index.py,1693 +def make_index(t, d, args):make_index16,452 +class BasketIndex(CreditIndex):BasketIndex22,603 + def __init__(self, index_type: str, series: int, tenors: List[str], *,__init__30,776 + def __reduce__(self):__reduce__64,2796 + def __hash__(self):__hash__69,2951 + def aux(v):aux70,2975 + def _query_version(self, i):_query_version80,3319 + def factor(self):factor86,3488 + def cumloss(self):cumloss90,3563 + def version(self):version94,3639 + def _get_quotes(self):_get_quotes97,3701 + trade_date = property(CreditIndex.trade_date.__get__)trade_date100,3742 + def trade_date(self, d: pd.Timestamp):trade_date103,3824 + def pv(self, maturity=None, epsilon=0., coupon=None):pv110,4119 + def coupon_leg(self, maturity=None):coupon_leg131,5038 + def protection_leg(self, maturity=None):protection_leg134,5143 + def spread(self, maturity=None, coupon=None):spread137,5234 + def duration(self, maturity=None):duration143,5510 + def theta(self, maturity=None, coupon=None):theta154,5988 + def coupon(self, maturity=None):coupon183,7332 + def tweak(self, *args):tweak189,7526 +class MarkitBasketIndex(BasketIndex):MarkitBasketIndex216,8549 + def __init__(self, index_type: str, series: int, tenors: List[str], *,__init__217,8587 + def _get_quotes(self):_get_quotes230,9434 + ig28 = BasketIndex("IG", 28, ["3yr", "5yr", "7yr", "10yr"])ig28234,9543 + settings = Settings()settings237,9727 + cds_schedule = Schedule.from_rule(settings.evaluation_date, Date.from_datetime(ig28.maturities[-1]),cds_schedule239,9754 + sp = ig28.survival_matrix(cds_schedule.to_npdates().view('int') + 134774)sp241,9962 -analytics/utils.py,255 -def GHquad(n):GHquad8,179 -def previous_twentieth(d):previous_twentieth13,302 -def next_twentieth(d):next_twentieth22,506 -def roll_date(d, tenor, nd_array=False):roll_date31,711 -def build_table(rows, format_strings, row_format):build_table71,2362 +.ropeproject/config.py,90 +def set_prefs(prefs):set_prefs5,45 +def project_opened(project):project_opened110,4652 templates/template-2014-05-19.html,0 @@ -1132,54 +1493,26 @@ templates/template-2015-04-20.html,0 templates/template-2014-04-16.html,0 -test_pickle.py,246 -USD_rates = pd.read_sql_table("usd_rates", dbengine("serenitasdb"),USD_rates22,792 - index_col='effective_date')index_col23,860 -def build_curves():build_curves24,918 -def get_curves(date=None):get_curves54,2451 +exploration/beta_trade.py,690 +def calc_returns(index_list=['HY', 'IG'], save_feather=False):calc_returns19,389 +def calc_betas(returns=None, spans=[5, 20], index_list=['HY', 'IG']):calc_betas30,917 +def plot_betas(betas=None):plot_betas40,1313 +def calc_realized_vol(returns=None):calc_realized_vol50,1577 +def spreads_ratio(series=list(range(22, 29)), index=['IG', 'HY'], tenor='5yr'):spreads_ratio73,2462 +def loglik(beta, returns):loglik79,2727 + returns = calc_returns()returns86,2906 + betas = calc_betas(returns)betas87,2935 + vol = calc_realized_vol(returns)vol89,2989 + ratios = spreads_ratio()ratios90,3026 + prog = minimize_scalar(loglik, bracket=(3, 5), args=(returns,))prog91,3055 -tranche_functions.py,1770 -def wrapped_ndpointer(*args, **kwargs):wrapped_ndpointer11,343 - def from_param(cls, obj):from_param13,421 -libloss = np.ctypeslib.load_library("lossdistrib", "../R/lossdistrib/src/")libloss19,616 -def GHquad(n):GHquad93,3228 -def stochasticrecov(R, Rtilde, Z, w, rho, porig, pmod):stochasticrecov97,3308 -def fitprob(Z, w, rho, p0):fitprob103,3604 -def BCloss_recov_dist(defaultprob, issuerweights, recov, rho, Z, w, Ngrid=101, defaultflag=False):BCloss_recov_dist108,3780 -def lossdistrib_joint(p, pp, w, S, Ngrid=101, defaultflag=False):lossdistrib_joint118,4339 -def lossdistrib_joint_Z(p, pp, w, S, rho, Ngrid=101, defaultflag=False, nZ=500):lossdistrib_joint_Z158,5521 -def joint_default_averagerecov_distrib(p, S, Ngrid=101):joint_default_averagerecov_distrib215,7164 -def adjust_attachments(K, losstodate, factor):adjust_attachments246,8077 -def trancheloss(L, K1, K2):trancheloss253,8277 -def trancherecov(R, K1, K2):trancherecov256,8363 -def tranche_cl(L, R, cs, K1, K2, scaled = False):tranche_cl259,8458 -def tranche_pl(L, cs, K1, K2, scaled=False):tranche_pl272,8957 -def tranche_pv(L, R, cs, K1, K2):tranche_pv284,9338 -def creditSchedule(tradedate, tenor, coupon, yc, enddate = None):creditSchedule287,9441 -def cdsAccrued(tradedate, coupon):cdsAccrued305,10209 -def dist_transform(q):dist_transform317,10643 -def dist_transform2(q):dist_transform2332,11057 -def compute_pv(q, strike):compute_pv346,11458 -def average_recov(p, R, Ngrid):average_recov353,11660 - n_issuers = 100n_issuers381,12666 - p = np.random.rand(n_issuers)p382,12686 - R = np.random.rand(n_issuers)R383,12720 - Rbar = joint_default_averagerecov_distrib(p, 1-R, 1001)Rbar384,12754 - Rbar_slow = average_recov(p, R, 1001)Rbar_slow385,12814 - -exploration/beta_trade.py,633 -returns = index_returns(index=['IG', 'HY'], tenor='5yr')returns8,175 -returns = (returns.returns9,232 -returns = (returns.returns14,376 -vol_sma = returns.hy.rolling(20).std() * math.sqrt(252)vol_sma22,719 -vol_ewma = returns.hy.ewm(span=20).std() * math.sqrt(252)vol_ewma23,775 -scale = 10scale26,896 -am = arch_model(scale * returns.hy.dropna())am27,907 -res = am.fit()res28,952 -vol_garch = res.conditional_volatility * math.sqrt(252)/scalevol_garch29,967 -vol = pd.concat([vol_sma, vol_ewma, vol_garch], axis=1)vol30,1029 -beta_ewma = (returns.beta_ewma33,1109 -resids = returns.ig-beta_ewma*returns.hyresids39,1285 +exploration/tranches.py,326 +engine = dbengine('serenitasdb')engine17,571 +def rv_calc1():rv_calc119,606 +def dispersion():dispersion71,2854 +def scenarios(tranche, shock_range=None, roll_corr=False):scenarios99,4320 +def run_scen(trade_date = pd.Timestamp.today().normalize()- pd.offsets.BDay()):run_scen148,6960 +def plot_pnl():plot_pnl198,9083 exploration/sell_atm_vol.py,357 option_delta = Index.from_name('ig', 28, '5yr')option_delta6,145 @@ -1188,94 +1521,151 @@ receiver = BlackSwaption(option_delta, datetime.date(2017, 8, 16), 62.5, 'receiv portfolio = Portfolio([payer, receiver, option_delta])portfolio24,668 r = []r27,804 -exploration/curve_trades.py,2027 -df = get_index_quotes("IG", [23, 24, 25, 26, 27], tenor=['3yr', '5yr', '7yr', '10yr'])df6,107 -spreads = df.groupby(level=['date', 'tenor']).nth(-1)['closespread'].unstack(-1)spreads7,194 -spreads = spreads.sort_index(1)spreads10,350 -spreads_diff = spreads.diff(axis=1)spreads_diff11,382 -spreads_diff = spreads_diff.filter([5, 7, 10])spreads_diff12,418 -df = index_returns(index='IG', series=[24, 25, 26, 27, 28], tenor=['3yr', '5yr', '7yr', '10yr'])df17,551 -returns = df.price_return.unstack(-1).dropna().groupby(level='date').nth(-1)returns19,670 -strategy510 = 1.78 * returns['5yr'] - returns['10yr']strategy51020,747 -strategy710 = 1.33 * returns['7yr'] - returns['10yr']strategy71021,801 -strategy3510 = -2 * returns['3yr']+ 3 * returns['5yr'] - 1 * returns['10yr']strategy351022,855 -monthly_returns510 = strategy510.groupby(pd.TimeGrouper(freq='M')).agg(lambda df:(1+df).prod()-1)monthly_returns51024,933 -monthly_returns710 = strategy710.groupby(pd.TimeGrouper(freq='M')).agg(lambda df:(1+df).prod()-1)monthly_returns71025,1031 -monthly_returns3510 = strategy3510.groupby(pd.TimeGrouper(freq='M')).agg(lambda df:(1+df).prod()-1)monthly_returns351026,1129 -sharpe510 = strategy510.mean()/strategy510.std()*math.sqrt(252)sharpe51028,1230 -sharpe710 = strategy710.mean()/strategy710.std()*math.sqrt(252)sharpe71029,1294 -sharpe3510 = strategy3510.mean()/strategy3510.std()*math.sqrt(252)sharpe351030,1358 -monthly_sharpe510 = monthly_returns510.mean()/monthly_returns510.std()*math.sqrt(12)monthly_sharpe51032,1426 -monthly_sharpe710 = monthly_returns710.mean()/monthly_returns710.std()*math.sqrt(12)monthly_sharpe71033,1511 -monthly_sharpe3510 = monthly_returns3510.mean()/monthly_returns3510.std()*math.sqrt(12)monthly_sharpe351034,1596 -worst_drawdown510 = strategy510.nsmallest(10)worst_drawdown51036,1685 -worst_drawdown710 = strategy710.nsmallest(10)worst_drawdown71037,1731 -worst_drawdown3510 = strategy3510.nsmallest(10)worst_drawdown351038,1777 -def forward_loss():forward_loss40,1826 +exploration/test_cms.py,652 +cap = 0.00758cap7,194 +corr = 0.8corr8,208 +r = []r9,219 +maturity = pd.Timestamp("2020-01-19")maturity10,226 +today = pd.Timestamp.today()today11,264 + cms_spread_coupon_ln = quantlib_model(d, cms30y2y, yc, cap, corr, maturity)cms_spread_coupon_ln17,500 + rate1 = cms_spread_coupon_ln.raterate118,580 + cms_spread_coupon_n = quantlib_model(d, cms30y2y, yc, cap, corr, maturity,cms_spread_coupon_n19,618 + rate2 = cms_spread_coupon_n.raterate221,759 + rate3 = globeop_model(d, cms30y2y, yc, cap, corr - 0.075, maturity)rate322,796 +df = pd.DataFrame(r, columns=['date', 'QL_ln', 'QL_n', 'Globeop']).set_index('date')df24,907 + +exploration/curve_trades.py,1273 +_engine = dbengine('serenitasdb')_engine15,461 +def on_the_run(index):on_the_run17,496 +def curve_spread_diff(index='IG', rolling=6):curve_spread_diff23,689 +def spreads_diff_table(spreads_diff):spreads_diff_table35,1217 + def current(s):current36,1255 + def zscore(s):zscore38,1300 +def theta_matrix_by_series(index='IG', rolling=6):theta_matrix_by_series44,1517 +def ratio_within_series(index='IG', rolling=6, param='duration'):ratio_within_series53,1999 +def curve_3_5_10(df):curve_3_5_1064,2548 +def curve_5_10(df):curve_5_1075,2872 +def on_the_run_theta(index='IG', rolling=6):on_the_run_theta80,3033 +def curve_returns(index='IG', rolling=6):curve_returns88,3405 + def sharpe(df, period="daily"):sharpe107,4344 +def cross_series_curve(index='IG', rolling=6):cross_series_curve119,4843 +def forward_loss(index='IG'):forward_loss137,5704 +def curve_model(tenor_1='5yr', tenor_2='10yr'):curve_model154,6655 +def curve_model_results(df, model):curve_model_results169,7304 +def spread_fin_crisis(index='IG'):spread_fin_crisis182,8088 +def forward_spread(index='IG', series=None, tenors=['3yr', '5yr', '7yr', '10yr']):forward_spread206,8989 +def spot_forward(index='IG', series=None, tenors=['3yr', '5yr', '7yr', '10yr']):spot_forward220,9485 + +exploration/backtest.py,130 +def calc_mark_diff():calc_mark_diff5,64 + def closest(s):closest12,385 + def avg_minus_maxmin(s):avg_minus_maxmin20,592 + +exploration/option_trades.py,1558 +serenitasdb = dbengine('serenitasdb')serenitasdb14,310 +def realized_vol(index, series, tenor='5yr', date=None, years=None, return_type='spread'):realized_vol16,349 +def lr_var(res):lr_var29,1048 +def atm_vol_calc(df, index_type, moneyness):atm_vol_calc42,1443 +def atm_vol(index, date, series=None, moneyness=0.2):atm_vol75,3123 +def rolling_vol(df, col='atm_vol', term=[3]):rolling_vol91,3914 + def aux(s, col, term):aux95,4128 +def vol_var(percentile=0.975, index='IG', start_date=datetime.date(2014, 6, 11)):vol_var106,4606 +def get_index_spread(index, series, date, conn):get_index_spread119,5093 +def get_index_ref(index, series, date, expiry, conn):get_index_ref131,5487 +def get_option_pnl(strike, expiry, index, series, start_date, engine):get_option_pnl144,5988 +def sell_vol_strategy(index="IG", months=3):sell_vol_strategy179,7669 +def aggregate_trades(d):aggregate_trades205,8976 +def compute_allocation(df):compute_allocation211,9119 + df = atm_vol("HY", datetime.date(2017, 3, 20))df246,10413 + df_hy28 = df.xs(28, level='series')df_hy28250,10603 + results = smf.ols('log_atm_vol ~ log_forward_spread + T', data=df_hy28).fit()results251,10643 + beta_hy28 = 1 + results.params.log_forward_spreadbeta_hy28252,10725 + df = atm_vol("IG", datetime.date(2017, 3, 20))df256,10819 + df_ig28 = df.xs(28, level='series')df_ig28260,11009 + results = smf.ols('log_atm_vol ~ log_forward_spread + T', data=df_ig28).fit()results261,11049 + beta_ig28 = 1 + results.params.log_forward_spreadbeta_ig28262,11131 + +exploration/curve_trades2.py,945 +def on_the_run(index):on_the_run10,267 +def curve_spread_diff(index='IG', rolling=6):curve_spread_diff16,470 +def spreads_diff_table(spreads_diff):spreads_diff_table31,1140 + def current(s):current32,1178 + def zscore(s):zscore34,1223 +def theta_matrix_by_series(index='IG', rolling=6):theta_matrix_by_series40,1440 +def ratio_within_series(index='IG', rolling=6, param='duration'):ratio_within_series49,1922 +def curve_3_5_10(theta_ratio_within_series):curve_3_5_1059,2417 +def curve_5_10(theta_ratio_within_series):curve_5_1071,2983 +def on_the_run_theta(index='IG', rolling=6):on_the_run_theta77,3211 +def curve_returns(index='IG', rolling=6):curve_returns85,3583 + def sharpe(df, period="daily"):sharpe102,4387 +def cross_series_curve(index='IG'):cross_series_curve114,4886 +def forward_loss(index='IG'):forward_loss131,5655 +def read_IG_curve_pos():read_IG_curve_pos148,6606 +def curve_model():curve_model155,6840 + +exploration/marketing.py,357 +gridsize = 500gridsize6,131 +def run_scenario(pool_size, rho, successprob, issuerweights, amount):run_scenario8,147 +def plot_scenarios(df, bins = [0,0.1, 50, 100, 150, 200, 250, 300, 350, 400, 450, 500, 2000]):plot_scenarios17,553 +def stats(df):stats37,1333 +def plot_prob_over(df):plot_prob_over44,1565 +def add_to_plot(df, ax):add_to_plot51,1763 + +exploration/.ropeproject/config.py,90 +def set_prefs(prefs):set_prefs5,45 +def project_opened(project):project_opened110,4652 -exploration/option_trades.py,1262 -serenitasdb = dbengine('serenitasdb')serenitasdb14,300 -def realized_vol(index, series, tenor='5yr', date=None, years=None, return_type='spread'):realized_vol16,339 -def lr_var(res):lr_var28,972 -def atm_vol_fun(v, moneyness=0.2, index=None):atm_vol_fun41,1366 -def atm_vol(index, date, series=None, moneyness=0.2):atm_vol57,2034 -def atm_vol_calc(df, index):atm_vol_calc71,2636 -def rolling_vol(df, col='atm_vol', term=[3]):rolling_vol84,3200 - def aux(s, col, term):aux87,3362 -def vol_var(percentile=0.975, index='IG', start_date=datetime.date(2014, 6, 11)):vol_var98,3840 -def get_index_spread(index, series, date, conn):get_index_spread111,4327 -def get_index_ref(index, series, date, expiry, conn):get_index_ref123,4721 -def get_option_pnl(strike, expiry, index, series, start_date, engine):get_option_pnl136,5222 -def sell_vol_strategy(index="IG", months=3):sell_vol_strategy171,6903 -def aggregate_trades(d):aggregate_trades197,8210 -def compute_allocation(df):compute_allocation203,8353 - d1 = sell_vol_strategy(months=1)d1227,9135 - d2 = sell_vol_strategy(months=2)d2228,9172 - d3 = sell_vol_strategy(months=3)d3229,9209 - all_tenors = pd.concat([aggregate_trades(d) for d in [d1, d2, d3]], axis=1)all_tenors230,9246 +exploration/sell_vol.py,575 +df = index_returns(index="IG", tenor=["5yr"])df12,438 +df = df.reset_index(['index', 'tenor'], drop=True)df13,484 +spreads = df.dropna().groupby(['date']).nth(-1)['spread_return']spreads14,535 +monthly_returns = spreads.rolling('30D').apply(lambda s: (1 + s).prod() - 1)monthly_returns15,600 +mu = monthly_returns.median()mu16,677 +ecdf = ECDF(monthly_returns)ecdf17,707 +def implied_vol(q):implied_vol19,737 +engine = dbengine('serenitasdb')engine24,949 +sched = Schedule.from_rule(Date(1, 6, 2014), Date(1, 4, 2018), Period(1, Months), UnitedStates())sched25,982 -exploration/swaption_calendar_spread.py,746 -engine = dbengine('serenitasdb')engine23,645 -def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name='shiftedcmap'):shiftedColorMap25,680 -def plot_df(df, spread_shock, vol_shock, attr="pnl"):plot_df76,2455 -def plot_color_map(df, spread_shock, vol_shock, attr="pnl", path="."):plot_color_map91,3050 -def plot_time_color_map(df, spread_shock, attr="pnl", path=".", color_map = cm.RdYlGn):plot_time_color_map116,4187 -def dec_jan_2017_trade():dec_jan_2017_trade141,5249 -def april_may_2017_trade(what='pnl'):april_may_2017_trade158,6123 -def june_july_2017_trade():june_july_2017_trade176,6997 -def hy_trade_scenario():hy_trade_scenario207,8494 -def portfolio():portfolio246,10502 -def probabilities():probabilities268,11718 +exploration/swaption_calendar_spread.py,406 +engine = dbengine('serenitasdb')engine22,606 +def plot_df(df, spread_shock, vol_shock, attr="pnl"):plot_df25,642 +def plot_color_map(df, spread_shock, vol_shock, attr="pnl", path=".", index ='IG'):plot_color_map40,1237 +def plot_trade_scenarios(portf, shock_min=-.15, shock_max=.2, period = -1, vol_time_roll=True):plot_trade_scenarios65,2461 +def exercise_probability():exercise_probability94,4069 -exploration/portfolio_var.py,1139 -dawndb = dbengine('dawndb')dawndb10,260 -serenitasdb = dbengine('serenitasdb')serenitasdb11,288 -shock = []shock15,387 -shock_values = [.95,.05]shock_values16,398 -shock = pd.DataFrame.from_records(shock, columns=['index', 'percent', 'shock'], index=['index', 'percent'])shock26,981 -trade_date = datetime.date.today() - BDay(2)trade_date32,1174 - "maturity, folder FROM cds where trade_date < %s",df34,1341 -df = df.groupby(['security_id','maturity','folder']).agg(sum)df36,1498 -df1 = pd.read_sql_query("SELECT redindexcode as security_id, index, series, indexfactor from index_version where lastdate = 'infinity'", serenitasdb)df139,1599 -df2 = pd.read_sql_query("SELECT * from index_maturity", serenitasdb, parse_dates=['maturity'])df240,1749 - " FROM index_quotes where date = %s",df342,1911 -df = df.merge(df1, on='security_id')df45,2030 -df = df.merge(df2, how='inner', on=['index','maturity', 'series'])df46,2067 -df = df.merge(df3, on=['index','series','tenor'])df47,2134 -df1 = df.groupby(['folder']).agg(sum)[[.95,.05]]df153,2477 -df1 = df1.min(axis = 1)df154,2526 +exploration/compression.py,181 +df = get_index_quotes(["IG", "HY"], 27, "5yr")df2,40 +df = df.groupby(level=['date', 'index']).nth(-1)df3,87 +df = df.groupby(level=['date', 'index', 'version']).nth(-1)df5,168 -exploration/portfolio_example.py,697 -option_delta = Index.from_tradeid(870)option_delta23,808 -option1 = BlackSwaption.from_tradeid(5, option_delta)option124,847 -option2 = BlackSwaption.from_tradeid(6, option_delta)option225,901 -portf = Portfolio([option1, option2, option_delta])portf27,956 -date_range = pd.bdate_range(option_delta.trade_date,date_range28,1008 -vol_shock = np.arange(-0.15, 0.3, 0.01)vol_shock30,1129 -spread_shock = np.arange(-0.2, 0.3, 0.01)spread_shock31,1169 -vs = VolatilitySurface("IG", 27, trade_date=option_delta.trade_date)vs32,1211 -vol_surface = vs[vs.list(model="black")[-1]]vol_surface33,1280 -df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface,df34,1325 +exploration/cds_pnl.py,318 +trade_date = datetime.date(2017, 5, 31)trade_date7,126 +def get_portf(trade_date):get_portf9,167 +portf = get_portf(datetime.date(2017, 5, 31))portf29,870 +dr = pd.date_range('2017-06-01', '2017-06-30', freq=bus_day)dr30,916 +pnl = []pnl32,978 + portf = get_portf(datetime.date(2017, 6, 27))portf38,1175 + +exploration/portfolio_var.py,463 +dawndb = dbengine('dawndb')dawndb14,330 +serenitasdb = dbengine('serenitasdb')serenitasdb15,358 +def on_the_run(index):on_the_run17,397 +def rel_spread_diff(report_date = datetime.date.today(), index='HY', rolling=10):rel_spread_diff23,600 +def get_pos(report_date):get_pos38,1249 +def cleared_cds_margins(report_date=datetime.date.today()):cleared_cds_margins49,1712 +def index_curve_margins(report_date=datetime.date.today()):index_curve_margins71,2856 + +exploration/portfolio_example.py,681 +option_delta = Index.from_tradeid(870)option_delta7,210 +option1 = BlackSwaption.from_tradeid(5, option_delta)option18,249 +option2 = BlackSwaption.from_tradeid(6, option_delta)option29,303 +portf = Portfolio([option1, option2, option_delta])portf11,358 +date_range = pd.bdate_range(option_delta.trade_date,date_range12,410 +vol_shock = np.arange(-0.15, 0.3, 0.01)vol_shock14,529 +spread_shock = np.arange(-0.2, 0.3, 0.01)spread_shock15,569 +vs = BlackSwaptionVolSurface("IG", 27, trade_date=option_delta.trade_date)vs16,611 +vol_surface = vs[vs.list()[-1]]vol_surface17,686 +df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface,df18,718 murano.py,1029 df = pd.read_table("/home/share/guillaume/murano leads.csv.txt", encoding="utf-16-le", low_memory=False)df6,71 @@ -1296,38 +1686,20 @@ investorsdb = dbengine('investorsdb')investorsdb125,5202 sql_str = "INSERT INTO investors VALUES({})".format(",".join(list_placeholders(df)))sql_str126,5240 conn = investorsdb.raw_connection()conn127,5325 -mark_backtest_underpar.py,2286 -df = pd.read_sql_table('external_marks_mapped', dbengine('dawndb'),df11,205 - parse_dates=['date'])parse_dates12,273 -df = df[df.source.notnull()]df13,318 -df_wide = (pd.pivot_table(df, 'mark', ['identifier', 'date'], 'source').df_wide14,347 -df_trades = {}df_trades18,479 - parse_dates=['trade_date'])parse_dates22,725 - parse_dates=['trade_date'])parse_dates26,1018 -df_sell_wide = pd.merge_asof(df_trades['sell'], df_wide, left_on='trade_date', right_on='date', by='identifier')df_sell_wide30,1186 -df_wide_temp = df_wide.set_index('date').shift(periods = -1, freq= 'M', axis = 1).reset_index()df_wide_temp31,1299 -df_buy_wide = pd.merge_asof(df_trades['buy'], df_wide_tempdf_buy_wide32,1395 -d_sell = {}d_sell35,1542 -d_buy = {}d_buy36,1554 -df_long = {}df_long37,1565 -df_long = pd.concat(d_sell, join='inner')df_long47,2025 -df_long = df_long.append(pd.concat(d_buy, join='inner'))df_long48,2067 -df_long = df_long.reset_index().dropna(subset=['price','mark'])df_long49,2124 -diff_threshold = 5diff_threshold53,2277 -begindate = '2013-01-01'begindate54,2296 -enddate = '2018-01-01'enddate55,2321 -df_long = df_long[df_long.identifier.str.len() == 9]df_long57,2345 -df_long = df_long[(df_long['trade_date'] > begindate) & (df_long['trade_date'] < enddate)]df_long58,2398 -order = ['MANAGER','BROKER','BVAL','IDC','MARKIT','PB','PRICESERVE','PRICINGDIRECT','REUTERS','S&P']order70,2758 -g_sell = sb.FacetGrid(df_long[df_long.dir == 'sell'], hue='source', hue_kws={'s':[50] + [20]*9, 'marker': ["o"]+["s"]*9, 'alpha': [1]+[.4]*9}, legend_out=True, aspect = 2.1, size = 4, hue_order = order)g_sell73,2907 -ax_sell = g_sell.map(plt.scatter, 'mark', 'price').add_legend()ax_sell75,3151 -g_buy = sb.FacetGrid(df_long[df_long.dir == 'buy'], hue='source', hue_kws={'s':[50] + [20]*9, 'marker': ["o"]+["s"]*9, 'alpha': [1]+[.4]*9}, legend_out=True, aspect = 2.1, size = 4, hue_order = order)g_buy77,3216 -ax_buy = g_buy.map(plt.scatter, 'mark', 'price').add_legend()ax_buy79,3457 -params = {}params84,3647 -error = {}error85,3659 -trade_PNL = {}trade_PNL86,3670 -trade_PNL_stat = {}trade_PNL_stat87,3685 -buychart = trade_PNL['buy'].unstack(-1).plot()buychart102,4458 +mark_backtest_underpar.py,794 +def get_mark_df(asset_class = 'Subprime'):get_mark_df12,235 +def calc_mark_diff(df, sources= ['PRICESERVE', 'PRICINGDIRECT','BVAL','MARKIT','BROKER', 'REUTERS', 'S&P', 'IDC']):calc_mark_diff25,1000 +def closest(x):closest51,2224 +def remove_max_min(x):remove_max_min58,2431 +def diff_by_source(df):diff_by_source64,2572 +def diff_by_source_percentage(df):diff_by_source_percentage73,2980 +def count_sources(df):count_sources80,3190 +def alt_navs():alt_navs86,3483 +def annual_performance(nav_100):annual_performance100,4184 +def alt_nav_impact():alt_nav_impact106,4376 +def back_test(begindate = '2013-01-01', enddate = '2018-01-01', sell_price_threshold = 200):back_test112,4551 +def stats(df_long, diff_threshold = 5):stats133,5865 +def pretty_plot(df_long):pretty_plot144,6224 insert_index.py,1288 engine = create_engine('postgresql://serenitas_user@debian/serenitasdb')engine4,74 @@ -1358,45 +1730,7 @@ CFLAGS=-O2 -march=native -fpicCFLAGS1,0 LDLIBS=-lm -llapackLDLIBS2,31 LDFLAGS=-fpic -sharedLDFLAGS3,51 -index_data.py,462 -serenitasdb = dbengine('serenitasdb')serenitasdb6,96 -def insert_quotes():insert_quotes8,135 -def get_index_quotes(index=None, series=None, tenor=None, from_date=None, years=3):get_index_quotes41,1880 - def make_str(key, val):make_str49,2224 - def make_params(args):make_params65,2758 -def index_returns(df=None, index=None, series=None, tenor=None, from_date=None, years=3, per=1):index_returns80,3383 - def add_accrued(df):add_accrued110,4643 - -test_upfront_cds.py,2424 -def snac_pv(spread, term_date, fixed_coupon=0.01, recovery=0.4, ts=YC()):snac_pv23,1044 -def jpmorgan_curves(trade_date, value_date, start_date, end_date, spread, recovery=0.4):jpmorgan_curves45,2476 - settings = Settings()settings54,2877 - yield_helpers = rate_helpers()yield_helpers56,2952 - ts = YC(helpers = yield_helpers)ts57,2987 - tenor = Period(5, Years)tenor58,3024 - trade_date = datetime.date(2009, 5, 21)trade_date59,3053 - stepin_date = trade_date + datetime.timedelta(days=1)stepin_date60,3097 - value_date = datetime.date(2009, 5, 26)value_date61,3155 - term_date = datetime.date(2019, 6, 20)term_date62,3199 - start_date = datetime.date(2009, 3, 20)start_date63,3242 - spread = 0.001spread64,3286 - sc_data = sc.inspect()['data']sc_data66,3405 - hazard_rate = math.log(1 + sc_data[0][1])hazard_rate67,3440 - contingent_leg = ContingentLeg(start_date, term_date, 10000000)contingent_leg68,3486 - fee_leg = FeeLeg(start_date, term_date, True, 10000000, 0.01)fee_leg69,3554 - flat_curve = FlatHazardRate(0, WeekendsOnly(), hazard_rate, Actual365Fixed())flat_curve71,3621 - cds_schedule = Schedule(Date.from_datetime(trade_date), Date.from_datetime(term_date),cds_schedule72,3703 - cds_trade = CreditDefaultSwap.from_upfront(BUYER, 10000000, 0., 0.01, cds_schedule, Following, Actual360(),cds_trade75,3916 - protection_start = Date.from_datetime(trade_date) + 1,protection_start76,4028 - last_period_day_counter = Actual360(True))last_period_day_counter77,4130 - isda_pricer = IsdaCdsEngine(flat_curve, 0.4, ts, accrual_bias=AccrualBias.HalfDayBias,isda_pricer78,4220 - forwards_in_coupon_period = ForwardsInCouponPeriod.Piecewise)forwards_in_coupon_period79,4311 - cds_trade2 = CreditDefaultSwap(BUYER, 10000000, spread, cds_schedule, Following, Actual360(),cds_trade283,4469 - protection_start = Date.from_datetime(trade_date) + 1,protection_start84,4567 - last_period_day_counter = Actual360(True))last_period_day_counter85,4657 - h = 0.00168276528775h87,4783 - flat_curve2 = FlatHazardRate(0, WeekendsOnly(), h, Actual365Fixed())flat_curve288,4808 - isda_pricer2 = IsdaCdsEngine(flat_curve2, 0.4, ts)isda_pricer289,4881 +notebooks/path.py,0 test_hyoption.py,410 index = Index.from_name("hy", 27, "5yr",index3,54 @@ -1406,28 +1740,21 @@ strike = 102.5strike7,225 payer = Swaption(index, exercise_date, strike, strike_is_price = True)payer8,240 receiver = Swaption(index, exercise_date, strike, "receiver", strike_is_price = True)receiver13,374 -bbg_prices.py,1159 -engine = create_engine('postgresql://et_user@debian/ET')engine10,257 -fields_update = ["LN_ISSUE_STATUS", "AMT_OUTSTANDING", "PX_LAST","LAST_UPDATE_DT",fields_update12,315 - "AND not called", engine, index_col='cusip')cusips20,812 -securities = ["{0} Corp".format(cusip) for cusip in cusips.index]securities22,885 - data = retrieve_data(session, securities, fields_update)data25,994 -df = pd.DataFrame.from_dict(data, orient='index')df27,1056 -to_insert = df[['DEFAULTED', 'DEFAULT_DATE', 'CALLED', 'CALLED_DT', 'LN_ISSUE_STATUS', 'ID_BB_UNIQUE']]to_insert32,1261 -to_insert = to_insert.where(to_insert.notnull(), None)to_insert33,1365 -conn = engine.raw_connection()conn35,1421 -currentdata = pd.read_sql_query("SELECT id_bb_unique, pricingdate from bloomberg_corp",currentdata43,1811 - parse_dates=["pricingdate"],parse_dates45,1939 - index_col=['id_bb_unique', 'pricingdate'])index_col46,2000 -df = df.ix[df.index.difference(currentdata.index)]df50,2232 -to_insert = df[['ID_BB_UNIQUE','LAST_UPDATE_DT','PX_LAST','LN_CURRENT_MARGIN',to_insert54,2365 - -test_hyoption2.py,308 -index = Index.from_name("hy", 27, "5yr",index3,54 - trade_date = datetime.date(2016, 11, 16))trade_date4,95 -exercise_date = datetime.date(2017, 3, 15)exercise_date6,182 -strike = 102.5strike7,225 -payer = Swaption(index, exercise_date, strike, strike_is_price = True)payer8,240 +bbg_prices.py,1158 +engine = create_engine('postgresql://et_user@debian/ET')engine9,252 +fields_update = ["LN_ISSUE_STATUS", "AMT_OUTSTANDING", "PX_LAST","LAST_UPDATE_DT",fields_update11,310 + "AND not called", engine, index_col='cusip')cusips19,807 +securities = ["{0} Corp".format(cusip) for cusip in cusips.index]securities21,880 + data = retrieve_data(session, securities, fields_update)data24,989 +df = pd.DataFrame.from_dict(data, orient='index')df26,1051 +to_insert = df[['DEFAULTED', 'DEFAULT_DATE', 'CALLED', 'CALLED_DT', 'LN_ISSUE_STATUS', 'ID_BB_UNIQUE']]to_insert31,1256 +to_insert = to_insert.where(to_insert.notnull(), None)to_insert32,1360 +conn = engine.raw_connection()conn34,1416 +currentdata = pd.read_sql_query("SELECT id_bb_unique, pricingdate from bloomberg_corp",currentdata42,1806 + parse_dates=["pricingdate"],parse_dates44,1934 + index_col=['id_bb_unique', 'pricingdate'])index_col45,1995 +df = df.ix[df.index.difference(currentdata.index)]df49,2227 +to_insert = df[['ID_BB_UNIQUE','LAST_UPDATE_DT','PX_LAST','LN_CURRENT_MARGIN',to_insert53,2360 sftp.py,469 hostname="alias.im"hostname4,27 @@ -1441,33 +1768,37 @@ hostkey = host_keys[hostname]['ssh-rsa']hostkey14,347 sftp = paramiko.SFTPClient.from_transport(t)sftp16,448 dirlist = sftp.listdir('.')dirlist17,493 -mark_swaptions.py,817 +mark_swaptions.py,815 level=logging.INFO,level13,295 format='%(asctime)s %(message)s')format14,335 def get_trades(date, engine):get_trades16,390 def get_swaptionvol(index, series, strike, expiry, date, engine):get_swaptionvol25,830 -def mark_trades(date, engine):mark_trades45,1697 - parser = argparse.ArgumentParser()parser97,3990 - type = lambda s: pd.datetime.strptime(s, "%Y-%m-%d").date()),type99,4076 - dawn_engine = dbengine('dawndb')dawn_engine100,4162 - serenitas_engine = dbengine('serenitasdb')serenitas_engine101,4199 - args = parser.parse_args()args102,4246 - workdate = (pd.Timestamp.today()-BDay()).date()workdate104,4307 - workdate = args.workdateworkdate106,4373 - r = mark_trades(workdate, dawn_engine)r108,4407 +def mark_trades(date, engine):mark_trades47,1739 + parser = argparse.ArgumentParser()parser95,4033 + type = lambda s: pd.datetime.strptime(s, "%Y-%m-%d").date()),type97,4119 + dawn_engine = dbengine('dawndb')dawn_engine98,4205 + serenitas_engine = dbengine('serenitasdb')serenitas_engine99,4242 + args = parser.parse_args()args100,4289 + workdate = (pd.Timestamp.today()-BDay()).date()workdate102,4350 + workdate = args.workdateworkdate104,4416 + r = mark_trades(workdate, dawn_engine)r106,4450 risk_insight/__init__.py,31 app = Flask(__name__)app2,24 -risk_insight/views.py,349 -def get_attach_from_name(index_type, series):get_attach_from_name7,138 -def get_db():get_db24,676 -def close_connection(exception):close_connection33,982 -def get_risk_numbers():get_risk_numbers39,1127 -def get_indices_quotes():get_indices_quotes56,1848 -def tranches():tranches84,2981 -def indices():indices91,3287 -def main():main95,3408 +risk_insight/views.py,353 +def get_attach_from_name(index_type, series):get_attach_from_name11,176 +def get_db():get_db28,714 +def close_connection(exception):close_connection37,1020 +def get_risk_numbers():get_risk_numbers43,1165 +def get_indices_quotes():get_indices_quotes63,2174 +def tranches():tranches95,3405 +def indices():indices102,3711 +def main():main106,3832 + +risk_insight/.ropeproject/config.py,90 +def set_prefs(prefs):set_prefs5,45 +def project_opened(project):project_opened110,4652 risk_insight/templates/index.html,0 @@ -1475,214 +1806,284 @@ risk_insight/templates/tranches.html,0 risk_insight/templates/indices.html,0 -Dawn/__init__.py,290 -app = Flask(__name__)app6,112 -db = SQLAlchemy(app, metadata = MetaData(schema=app.config['SCHEMA']))db8,165 - fh = logging.FileHandler(filename=app.config['LOGFILE'])fh11,255 - formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')formatter13,346 +Dawn/__init__.py,325 +app = Flask(__name__)app8,152 +csrf = CSRFProtect(app)csrf10,205 +db = SQLAlchemy(app, metadata=MetaData(schema=app.config['SCHEMA']))db11,229 + fh = logging.FileHandler(filename=app.config['LOGFILE'])fh14,317 + formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')formatter16,408 + +Dawn/models.py,15182 +class Counterparties(db.Model):Counterparties11,309 + __tablename__ = 'counterparties'__tablename__12,341 + code = db.Column(db.String(12), primary_key=True)code13,378 + name = db.Column(db.String)name14,432 + city = db.Column(db.String)city15,464 + state = db.Column(db.String(2))state16,496 + dtc_number = db.Column(db.Integer)dtc_number17,532 + sales_contact = db.Column(db.String)sales_contact18,571 + sales_email = db.Column(EmailType)sales_email19,612 + sales_phone = db.Column(PhoneNumberType())sales_phone20,651 + valuation_contact1 = db.Column(db.String)valuation_contact121,698 + valuation_email1 = db.Column(EmailType)valuation_email122,744 + valuation_contact2 = db.Column(db.String)valuation_contact223,788 + valuation_email2 = db.Column(EmailType)valuation_email224,834 + valuation_contact3 = db.Column(db.String)valuation_contact325,878 + valuation_email3 = db.Column(EmailType)valuation_email326,924 + valuation_contact4 = db.Column(db.String)valuation_contact427,968 + valuation_email4 = db.Column(EmailType)valuation_email428,1014 + notes = db.Column(db.String)notes29,1058 + instructions = db.Column(db.String, info={'form_field_class': FileField})instructions30,1091 +class Accounts(db.Model):Accounts32,1170 + __tablename__ = 'accounts'__tablename__33,1196 + code = db.Column(db.String(5), primary_key=True)code34,1227 + name = db.Column(db.String)name35,1280 + custodian = db.Column(db.String)custodian36,1312 + cash_account = db.Column(db.String)cash_account37,1349 + counterparty = db.Column(db.String(12), db.ForeignKey('counterparties.code'))counterparty38,1389 +BOND_STRAT = ENUM('M_STR_MAV', 'M_STR_MEZZ', 'CSO_TRANCH',BOND_STRAT40,1472 +CDS_STRAT = ENUM('HEDGE_CSO', 'HEDGE_CLO', 'HEDGE_MAC', 'HEDGE_MBS',CDS_STRAT45,1760 +SWAPTION_STRAT = ENUM('IGPAYER', 'IGREC', 'HYPAYER', 'HYREC',SWAPTION_STRAT50,2069 + name='swaption_strat')name51,2131 +FUTURE_STRAT = ENUM('M_STR_MAV', 'M_MTG_IO', 'M_STR_MEZZ', 'M_MTG_RW', 'SER_ITRXCURVE',FUTURE_STRAT53,2177 + name='future_strat')name54,2265 +CASH_STRAT = ENUM('M_CSH_CASH', 'MBSCDSCSH', 'SER_IGCVECSH', 'SER_ITRXCVCSH', 'CSOCDSCSH',CASH_STRAT56,2307 + name='cash_strat')name59,2521 +SWAPTION_TYPE = ENUM('PAYER', 'RECEIVER',SWAPTION_TYPE61,2559 + name='swaption_type')name62,2601 +REPO_TYPE = ENUM('REPO', 'REVERSE REPO', name='repo_type')REPO_TYPE64,2645 +FUTURE_TYPE = ENUM('FUTURE', 'CFD', 'SYNTHETIC-FUTURE', 'LME-FORWARD', name='future_type')FUTURE_TYPE65,2704 +CALL_NOTICE = ENUM('24H', '48H', '3D', '4D', '5D', '6D',CALL_NOTICE67,2796 +ASSET_CLASS = ENUM('CSO', 'Subprime', 'CLO', 'Tranches', 'Futures', 'Cash', 'FX', 'Cleared',ASSET_CLASS70,2936 + name='asset_class')name71,3029 +ACTION = ENUM('NEW', 'UPDATE', 'CANCEL', name='action')ACTION72,3068 +CCY = ENUM('USD', 'CAD', 'EUR', 'YEN', name='currency')CCY74,3125 +BBG_TYPE = ENUM('Mtge', 'Corp', name='bbg_type')BBG_TYPE76,3182 +SWAP_TYPE = ENUM('CD_INDEX', 'CD_INDEX_TRANCHE', 'CD_BASKET_TRANCHE', 'ABS_CDS', name='swap_type')SWAP_TYPE78,3232 +ISDA = ENUM('ISDA2014', 'ISDA2003Cred', name='isda')ISDA80,3332 +DAY_COUNT = ENUM('ACT/360', 'ACT/ACT', '30/360', 'ACT/365', name='day_count')DAY_COUNT82,3386 +BUS_DAY_CONVENTION = ENUM('Modified Following', 'Following', 'Modified Preceding', 'Preceding',BUS_DAY_CONVENTION84,3465 +PROTECTION = ENUM('Buyer', 'Seller', name='protection')PROTECTION86,3650 +class BondDeal(db.Model):BondDeal88,3707 + __tablename__ = 'bonds'__tablename__89,3733 + id = db.Column('id', db.Integer, primary_key=True)id90,3761 + dealid = db.Column(db.String(28))dealid91,3816 + lastupdate = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())lastupdate92,3854 + action = db.Column(ACTION)action93,3948 + folder = db.Column(BOND_STRAT, nullable=False)folder94,3979 + custodian = db.Column(db.String(12), default='BAC', nullable=False)custodian95,4030 + cashaccount = db.Column(db.String(10), default='V0NSCLMAMB', nullable=False)cashaccount96,4102 + cp_code = db.Column(db.String(12), db.ForeignKey('counterparties.code'),cp_code97,4183 + info={'choices': [(None, '')],info98,4260 + trade_date = db.Column(db.Date, nullable = False)trade_date100,4387 + settle_date = db.Column(db.Date, nullable = False)settle_date101,4441 + cusip = db.Column(db.String(9), info={'validators': Length(9, 9),cusip102,4496 + isin = db.Column(db.String(12), info={'validators': Length(12, 12),isin105,4700 + identifier = db.Column(db.String(12), info={'filters': [lambda x: x or None,],identifier108,4906 + description = db.Column(db.String(32), nullable = False, info={'trim': True})description110,5052 + buysell = db.Column(db.Boolean, nullable = False, info={'choices':[(0, 'sell'), (1, 'buy')],buysell111,5134 + faceamount = db.Column(db.Float, nullable=False)faceamount114,5412 + price = db.Column(db.Float, nullable=False)price115,5465 + accrued = db.Column(db.Float, nullable = False)accrued116,5513 + asset_class = db.Column(ASSET_CLASS)asset_class117,5565 + ticket = db.Column(db.String, info={'form_field_class': FileField})ticket118,5606 + principal_payment = db.Column(db.Float)principal_payment119,5678 + accrued_payment = db.Column(db.Float)accrued_payment120,5722 + counterparty = db.relationship(Counterparties)counterparty121,5764 + __table_args__= (db.CheckConstraint('cusip is not Null or isin is not Null'),)__table_args__122,5815 +class CDSDeal(db.Model):CDSDeal124,5899 + __tablename__ = 'cds'__tablename__125,5924 + id = db.Column('id', db.Integer, primary_key=True)id126,5950 + dealid = db.Column(db.String(28))dealid127,6005 + lastupdate = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())lastupdate128,6043 + action = db.Column(ACTION)action129,6137 + folder = db.Column(CDS_STRAT, nullable=False)folder130,6168 + custodian = db.Column(db.String(12), default='SGFCM', nullable=False)custodian131,6218 + cashaccount = db.Column(db.String(10), default='SGNSCLMASW', nullable=False)cashaccount132,6292 + cp_code = db.Column(db.String(12), db.ForeignKey('counterparties.code'),cp_code133,6373 + info={'choices': [(None, '')],info134,6450 + trade_date = db.Column(db.Date, nullable=False)trade_date136,6577 + effective_date = db.Column(db.Date, nullable=False)effective_date137,6629 + maturity = db.Column(db.Date, nullable=False)maturity138,6685 + currency = db.Column(CCY, nullable=False)currency139,6735 + payment_rolldate = db.Column(BUS_DAY_CONVENTION, nullable=False)payment_rolldate140,6781 + notional = db.Column(db.Float, nullable=False)notional141,6850 + fixed_rate = db.Column(db.Float, nullable=False)fixed_rate142,6901 + day_count = db.Column(DAY_COUNT, nullable=False)day_count143,6954 + frequency = db.Column(db.SmallInteger, default=4, nullable=False)frequency144,7007 + protection = db.Column(PROTECTION, nullable=False)protection145,7077 + security_id = db.Column(db.String(12), nullable=False)security_id146,7132 + security_desc = db.Column(db.String(32), nullable=False)security_desc147,7191 + upfront = db.Column(db.Float, nullable=False)upfront148,7252 + upfront_settle_date = db.Column(db.Date, nullable=False)upfront_settle_date149,7302 + initial_margin_percentage = db.Column(db.Float)initial_margin_percentage150,7363 + swap_type = db.Column(SWAP_TYPE, nullable=False)swap_type151,7415 + attach = db.Column(db.SmallInteger, info={'min': 0, 'max':100})attach152,7468 + detach = db.Column(db.SmallInteger, info={'min': 0, 'max':100})detach153,7536 + clearing_facility = db.Column(db.String(12), default='ICE-CREDIT')clearing_facility154,7604 + isda_definition = db.Column(ISDA)isda_definition155,7675 + counterparty = db.relationship(Counterparties)counterparty156,7713 + "clearing_facility is NULL)"),)__table_args__159,7936 +class RepoDeal(db.Model):RepoDeal161,8010 + __tablename__ = 'repo'__tablename__162,8036 + id = db.Column('id', db.Integer, primary_key=True)id163,8063 + lastupdate = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())lastupdate164,8118 + action = db.Column(ACTION)action165,8212 + folder = db.Column(CDS_STRAT, nullable=False)folder166,8243 + custodian = db.Column(db.String(12), default='SGFCM', nullable=False)custodian167,8293 + cashaccount = db.Column(db.String(10), default='SGNSCLMASW', nullable=False)cashaccount168,8367 + cp_code = db.Column(db.String(12), db.ForeignKey('counterparties.code'),cp_code169,8448 + info={'choices': [(None, '')],info170,8525 + trade_date = db.Column(db.Date, nullable=False)trade_date172,8652 + settle_date = db.Column(db.Date, nullable=False)settle_date173,8704 + cusip = db.Column(db.String(9), info={'validators': Length(9,9),cusip174,8757 + isin = db.Column(db.String(12), info={'validators': Length(12, 12),isin177,8960 + identifier = db.Column(db.String(12), info={'filters': [lambda x: x or None,],identifier180,9166 + description = db.Column(db.String(32), nullable=False, info={'trim': True})description182,9312 + transation_indicator = db.Column(REPO_TYPE)transation_indicator183,9392 + faceamount = db.Column(db.Float, nullable=False)faceamount184,9440 + price = db.Column(db.Float, nullable=False)price185,9493 + currency = db.Column(CCY, nullable=False)currency186,9541 + expiration_date = db.Column(db.Date)expiration_date187,9587 + weighted_amount = db.Column(db.Float)weighted_amount188,9628 + haircut = db.Column(db.Float)haircut189,9670 + repo_rate = db.Column(db.Float, nullable=False)repo_rate190,9704 + call_notice = db.Column(CALL_NOTICE)call_notice191,9756 + daycount = db.Column(DAY_COUNT)daycount192,9797 + ticket = db.Column(db.String, info={'form_field_class': FileField})ticket193,9833 + "haircut is NULL and weighted_amount is NOT NULL)"),__table__args195,10002 +class SwaptionDeal(db.Model):SwaptionDeal198,10178 + __tablename__ = 'swaptions'__tablename__199,10208 + id = db.Column('id', db.Integer, primary_key=True)id200,10240 + dealid = db.Column(db.String(28))dealid201,10295 + lastupdate = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())lastupdate202,10333 + action = db.Column(ACTION)action203,10427 + folder = db.Column(SWAPTION_STRAT, nullable=False)folder204,10458 + custodian = db.Column(db.String(12), default='NONE', nullable=False)custodian205,10513 + cashaccount = db.Column(db.String(10), default='SGNSCLMASW', nullable=False)cashaccount206,10586 + cp_code = db.Column(db.String(12), db.ForeignKey('counterparties.code'),cp_code207,10667 + info={'choices': [(None, '')],info208,10744 + trade_date = db.Column(db.Date, nullable=False)trade_date210,10871 + settle_date = db.Column(db.Date, nullable=False)settle_date211,10923 + buysell = db.Column(db.Boolean, nullable=False, info={'choices':[(0, 'sell'), (1, 'buy')],buysell212,10976 + notional = db.Column(db.Float, nullable=False)notional215,11250 + swaption_type = db.Column(SWAPTION_TYPE, nullable=False)swaption_type216,11301 + strike = db.Column(db.Float, nullable=False)strike217,11362 + price = db.Column(db.Float, nullable=False)price218,11411 + expiration_date = db.Column(db.Date, nullable=False)expiration_date219,11459 + initial_margin_percentage = db.Column(db.Float)initial_margin_percentage220,11516 + index_ref = db.Column(db.Float)index_ref221,11568 + security_id = db.Column(db.String(12), nullable=False)security_id222,11604 + security_desc = db.Column(db.String(32), nullable=False)security_desc223,11663 + fixed_rate = db.Column(db.Float, nullable=False)fixed_rate224,11724 + maturity = db.Column(db.Date, nullable=False)maturity225,11777 + currency = db.Column(CCY, nullable=False)currency226,11827 + counterparty = db.relationship(Counterparties)counterparty227,11873 +class FutureDeal(db.Model):FutureDeal229,11925 + __tablename__ = 'futures'__tablename__230,11953 + id = db.Column('id', db.Integer, primary_key=True)id231,11983 + dealid = db.Column(db.String(28))dealid232,12038 + lastupdate = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())lastupdate233,12076 + action = db.Column(ACTION)action234,12170 + folder = db.Column(FUTURE_STRAT, nullable=False)folder235,12201 + custodian = db.Column(db.String(12), default='INTBR', nullable=False)custodian236,12254 + cashaccount = db.Column(db.String(10), default='IANSCLMAFU', nullable=False)cashaccount237,12328 + cp_code = db.Column(db.String(12), db.ForeignKey('counterparties.code'),cp_code238,12409 + info={'choices': [('IBKRNY', 'Interactive Brokers')],info239,12486 + trade_date = db.Column(db.Date, nullable=False)trade_date241,12636 + settle_date = db.Column(db.Date, nullable=False)settle_date242,12688 + buysell = db.Column(db.Boolean, nullable=False, info={'choices':[(0, 'sell'), (1, 'buy')],buysell243,12741 + bbg_ticker = db.Column(db.String(32), nullable=False)bbg_ticker246,13015 + quantity = db.Column(db.Float, nullable=False)quantity247,13073 + price = db.Column(db.Float, nullable=False)price248,13124 + commission = db.Column(db.Float)commission249,13172 + swap_type = db.Column(FUTURE_TYPE, nullable=False)swap_type250,13209 + security_desc = db.Column(db.String(32), nullable=False)security_desc251,13264 + maturity = db.Column(db.Date, nullable=False)maturity252,13325 + currency = db.Column(CCY, nullable=False)currency253,13375 + exchange = db.Column(db.String(3), default='CME', nullable=False)exchange254,13421 + counterparty = db.relationship(Counterparties)counterparty255,13491 +class CashFlowDeal(db.Model):CashFlowDeal257,13543 + __tablename__ = 'wires'__tablename__258,13573 + id = db.Column('id', db.Integer, primary_key=True)id259,13601 + dealid = db.Column(db.String(28))dealid260,13656 + lastupdate = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())lastupdate261,13694 + action = db.Column(ACTION)action262,13788 + folder = db.Column(CASH_STRAT, nullable=False)folder263,13819 + code = db.Column(db.String(5), db.ForeignKey('accounts.code'), nullable=False)code264,13870 + amount = db.Column(db.Float, nullable=False)amount265,13953 + currency = db.Column(CCY, nullable=False)currency266,14002 + trade_date = db.Column(db.Date, nullable=False)trade_date267,14048 + account = db.relationship(Accounts)account268,14100 +BaseModelForm = model_form_factory(FlaskForm)BaseModelForm270,14141 +class ModelForm(BaseModelForm):ModelForm271,14187 + def get_session(self):get_session273,14236 -Dawn/models.py,11647 -class Counterparties(db.Model):Counterparties11,304 - __tablename__ = 'counterparties'__tablename__12,336 - code = db.Column(db.String(12), primary_key=True)code13,373 - name = db.Column(db.String)name14,427 - city = db.Column(db.String)city15,459 - state = db.Column(db.String(2))state16,491 - dtc_number = db.Column(db.Integer)dtc_number17,527 - sales_contact = db.Column(db.String)sales_contact18,566 - sales_email = db.Column(EmailType)sales_email19,607 - sales_phone = db.Column(PhoneNumberType())sales_phone20,646 - valuation_contact1 = db.Column(db.String)valuation_contact121,693 - valuation_email1 = db.Column(EmailType)valuation_email122,739 - valuation_contact2 = db.Column(db.String)valuation_contact223,783 - valuation_email2 = db.Column(EmailType)valuation_email224,829 - valuation_contact3 = db.Column(db.String)valuation_contact325,873 - valuation_email3 = db.Column(EmailType)valuation_email326,919 - valuation_contact4 = db.Column(db.String)valuation_contact427,963 - valuation_email4 = db.Column(EmailType)valuation_email428,1009 - notes = db.Column(db.String)notes29,1053 - instructions = db.Column(db.String, info={'form_field_class': FileField})instructions30,1086 -BOND_STRAT = ENUM('M_STR_MAV', 'M_STR_MEZZ', 'CSO_TRANCH',BOND_STRAT32,1165 -CDS_STRAT = ENUM('HEDGE_CSO', 'HEDGE_CLO', 'HEDGE_MAC', 'HEDGE_MBS',CDS_STRAT37,1453 -SWAPTION_STRAT = ENUM('IGPAYER', 'IGREC', 'HYPAYER', 'HYREC',SWAPTION_STRAT42,1745 - name='swaption_strat')name43,1807 -SWAPTION_TYPE = ENUM('PAYER', 'RECEIVER',SWAPTION_TYPE45,1853 - name='swaption_type')name46,1895 -REPO_TYPE = ENUM('REPO', 'REVERSE REPO', name='repo_type')REPO_TYPE48,1939 -CALL_NOTICE = ENUM('24H', '48H', '3D', '4D', '5D', '6D',CALL_NOTICE49,1998 -ASSET_CLASS = ENUM('CSO', 'Subprime', 'CLO', 'Tranches', 'Futures', 'Cash', 'FX', 'Cleared',ASSET_CLASS52,2138 - name='asset_class')name53,2231 -ACTION = ENUM('NEW', 'UPDATE', 'CANCEL', name='action')ACTION54,2270 -CCY = ENUM('USD', 'CAD', 'EUR', 'YEN', name='currency')CCY56,2327 -BBG_TYPE = ENUM('Mtge', 'Corp', name='bbg_type')BBG_TYPE58,2384 -SWAP_TYPE = ENUM('CD_INDEX', 'CD_INDEX_TRANCHE', 'CD_BASKET_TRANCHE', 'ABS_CDS', name='swap_type')SWAP_TYPE60,2434 -ISDA = ENUM('ISDA2014', 'ISDA2003Cred', name='isda')ISDA62,2534 -DAY_COUNT = ENUM('ACT/360', 'ACT/ACT', '30/360', 'ACT/365', name='day_count')DAY_COUNT64,2588 -BUS_DAY_CONVENTION = ENUM('Modified Following', 'Following', 'Modified Preceding', 'Preceding',BUS_DAY_CONVENTION66,2667 -PROTECTION = ENUM('Buyer', 'Seller', name='protection')PROTECTION68,2852 -class BondDeal(db.Model):BondDeal70,2909 - __tablename__ = 'bonds'__tablename__71,2935 - id = db.Column('id', db.Integer, primary_key=True)id72,2963 - dealid = db.Column(db.String(28))dealid73,3018 - lastupdate = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())lastupdate74,3056 - action = db.Column(ACTION)action75,3150 - folder = db.Column(BOND_STRAT, nullable=False)folder76,3181 - custodian = db.Column(db.String(12), default='BAC', nullable=False)custodian77,3232 - cashaccount = db.Column(db.String(10), default='V0NSCLMAMB', nullable=False)cashaccount78,3304 - cp_code = db.Column(db.String(12), db.ForeignKey('counterparties.code'),cp_code79,3385 - info={'choices': [(None, '')],info80,3462 - trade_date = db.Column(db.Date, nullable = False)trade_date82,3591 - settle_date = db.Column(db.Date, nullable = False)settle_date83,3645 - cusip = db.Column(db.String(9), info={'validators': Length(9,9),cusip84,3700 - isin = db.Column(db.String(12), info={'validators': Length(12, 12),isin87,3903 - identifier = db.Column(db.String(12), info={'filters': [lambda x: x or None,],identifier90,4109 - description = db.Column(db.String(32), nullable = False, info={'trim': True})description92,4255 - buysell = db.Column(db.Boolean, nullable = False, info={'choices':[(0, 'sell'), (1, 'buy')],buysell93,4337 - faceamount = db.Column(db.Float, nullable=False)faceamount96,4615 - price = db.Column(db.Float, nullable=False)price97,4668 - accrued = db.Column(db.Float, nullable = False)accrued98,4716 - asset_class = db.Column(ASSET_CLASS)asset_class99,4768 - ticket = db.Column(db.String, info={'form_field_class': FileField})ticket100,4809 - principal_payment = db.Column(db.Float)principal_payment101,4881 - accrued_payment = db.Column(db.Float)accrued_payment102,4925 - counterparty = db.relationship(Counterparties)counterparty103,4967 - __table_args__= (db.CheckConstraint('cusip is not Null or isin is not Null'),)__table_args__104,5018 -class CDSDeal(db.Model):CDSDeal106,5102 - __tablename__ = 'cds'__tablename__107,5127 - id = db.Column('id', db.Integer, primary_key=True)id108,5153 - dealid = db.Column(db.String(28))dealid109,5208 - lastupdate = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())lastupdate110,5246 - action = db.Column(ACTION)action111,5340 - folder = db.Column(CDS_STRAT, nullable = False)folder112,5371 - custodian = db.Column(db.String(12), default='SGFCM', nullable=False)custodian113,5423 - cashaccount = db.Column(db.String(10), default='SGNSCLMASW', nullable=False)cashaccount114,5497 - cp_code = db.Column(db.String(12), db.ForeignKey('counterparties.code'),cp_code115,5578 - info={'choices': [(None, '')],info116,5655 - trade_date = db.Column(db.Date, nullable = False)trade_date118,5784 - effective_date = db.Column(db.Date, nullable = False)effective_date119,5838 - maturity = db.Column(db.Date, nullable = False)maturity120,5896 - currency = db.Column(CCY, nullable = False)currency121,5948 - payment_rolldate = db.Column(BUS_DAY_CONVENTION, nullable = False)payment_rolldate122,5996 - notional = db.Column(db.Float, nullable = False)notional123,6067 - fixed_rate = db.Column(db.Float, nullable = False)fixed_rate124,6120 - day_count = db.Column(DAY_COUNT, nullable = False)day_count125,6175 - frequency = db.Column(db.SmallInteger, default=4, nullable = False)frequency126,6230 - protection = db.Column(PROTECTION, nullable = False)protection127,6302 - security_id = db.Column(db.String(12), nullable = False)security_id128,6359 - security_desc = db.Column(db.String(32), nullable = False)security_desc129,6420 - upfront = db.Column(db.Float, nullable = False)upfront130,6483 - upfront_settle_date = db.Column(db.Date, nullable = False)upfront_settle_date131,6535 - swap_type = db.Column(SWAP_TYPE, nullable = False)swap_type132,6598 - attach = db.Column(db.SmallInteger, info={'min': 0, 'max':100})attach133,6653 - detach = db.Column(db.SmallInteger, info={'min': 0, 'max':100})detach134,6721 - clearing_facility = db.Column(db.String(12), default='ICE-CREDIT')clearing_facility135,6789 - isda_definition = db.Column(ISDA)isda_definition136,6860 - counterparty = db.relationship(Counterparties)counterparty137,6898 - "(attach is not NULL and detach is not NULL)"),)__table_args__139,7028 -class RepoDeal(db.Model):RepoDeal141,7119 - __tablename__ = 'repo'__tablename__142,7145 - id = db.Column('id', db.Integer, primary_key=True)id143,7172 - lastupdate = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())lastupdate144,7227 - action = db.Column(ACTION)action145,7321 - folder = db.Column(CDS_STRAT, nullable = False)folder146,7352 - custodian = db.Column(db.String(12), default='SGFCM', nullable=False)custodian147,7404 - cashaccount = db.Column(db.String(10), default='SGNSCLMASW', nullable=False)cashaccount148,7478 - cp_code = db.Column(db.String(12), db.ForeignKey('counterparties.code'),cp_code149,7559 - info={'choices': [(None, '')],info150,7636 - trade_date = db.Column(db.Date, nullable = False)trade_date152,7765 - settle_date = db.Column(db.Date, nullable = False)settle_date153,7819 - cusip = db.Column(db.String(9), info={'validators': Length(9,9),cusip154,7874 - isin = db.Column(db.String(12), info={'validators': Length(12, 12),isin157,8077 - identifier = db.Column(db.String(12), info={'filters': [lambda x: x or None,],identifier160,8283 - description = db.Column(db.String(32), nullable = False, info={'trim': True})description162,8429 - transation_indicator = db.Column(REPO_TYPE)transation_indicator163,8511 - faceamount = db.Column(db.Float, nullable = False)faceamount164,8559 - price = db.Column(db.Float, nullable = False)price165,8614 - currency = db.Column(CCY, nullable = False)currency166,8664 - expiration_date = db.Column(db.Date)expiration_date167,8712 - weighted_amount = db.Column(db.Float)weighted_amount168,8753 - haircut = db.Column(db.Float)haircut169,8795 - repo_rate = db.Column(db.Float, nullable = False)repo_rate170,8829 - call_notice = db.Column(CALL_NOTICE)call_notice171,8883 - daycount = db.Column(DAY_COUNT)daycount172,8924 - ticket = db.Column(db.String, info={'form_field_class': FileField})ticket173,8960 - "haircut is NULL and weighted_amount is NOT NULL)"),__table__args175,9129 -class SwaptionDeal(db.Model):SwaptionDeal178,9305 - __tablename__ = 'swaptions'__tablename__179,9335 - id = db.Column('id', db.Integer, primary_key=True)id180,9367 - dealid = db.Column(db.String(28))dealid181,9422 - lastupdate = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())lastupdate182,9460 - action = db.Column(ACTION)action183,9554 - folder = db.Column(SWAPTION_STRAT, nullable = False)folder184,9585 - custodian = db.Column(db.String(12), default='NONE', nullable=False)custodian185,9642 - cashaccount = db.Column(db.String(10), default='SGNSCLMASW', nullable=False)cashaccount186,9715 - cp_code = db.Column(db.String(12), db.ForeignKey('counterparties.code'),cp_code187,9796 - info={'choices': [(None, '')],info188,9873 - trade_date = db.Column(db.Date, nullable = False)trade_date190,10002 - settle_date = db.Column(db.Date, nullable = False)settle_date191,10056 - buysell = db.Column(db.Boolean, nullable = False, info={'choices':[(0, 'sell'), (1, 'buy')],buysell192,10111 - notional = db.Column(db.Float, nullable = False)notional195,10389 - swaption_type = db.Column(SWAPTION_TYPE, nullable = False)swaption_type196,10442 - strike = db.Column(db.Float, nullable = False)strike197,10505 - price = db.Column(db.Float, nullable = False)price198,10556 - expiration_date = db.Column(db.Date, nullable = False)expiration_date199,10606 - initial_margin_percentage = db.Column(db.Float)initial_margin_percentage200,10665 - index_ref = db.Column(db.Float)index_ref201,10717 - security_id = db.Column(db.String(12), nullable = False)security_id202,10753 - security_desc = db.Column(db.String(32), nullable = False)security_desc203,10814 - fixed_rate = db.Column(db.Float, nullable = False)fixed_rate204,10877 - maturity = db.Column(db.Date, nullable = False)maturity205,10932 - currency = db.Column(CCY, nullable = False)currency206,10984 - counterparty = db.relationship(Counterparties)counterparty207,11032 -BaseModelForm = model_form_factory(Form)BaseModelForm209,11084 -class ModelForm(BaseModelForm):ModelForm210,11125 - def get_session(self):get_session212,11174 +Dawn/views.py,2767 +fed_cal = get_calendar('USFederalHolidayCalendar')fed_cal27,754 +bond_cal = HolidayCalendarFactory('BondCalendar', fed_cal, GoodFriday)bond_cal28,805 +bus_day = CustomBusinessDay(calendar=bond_cal())bus_day29,876 +def cp_choices(kind='bond'):cp_choices31,926 +def account_codes():account_codes43,1403 +def get_queue():get_queue46,1512 +def get_db():get_db56,1813 +def close_connection(exception):close_connection65,2119 +class CounterpartyForm(ModelForm):CounterpartyForm70,2234 + class Meta:Meta71,2269 + model = Counterpartiesmodel72,2285 + include_primary_keys = Trueinclude_primary_keys73,2316 +class BondForm(ModelForm):BondForm75,2353 + upload_globeop = BooleanField(label="Upload to globeop?")upload_globeop76,2380 + class Meta:Meta77,2442 + model = BondDealmodel78,2458 + include_foreign_keys = Trueinclude_foreign_keys79,2483 + exclude = ['dealid', 'lastupdate', #we generate it with a trigger at the server levelexclude80,2519 +class CDSForm(ModelForm):CDSForm83,2673 + upload_globeop = BooleanField(label="Upload to globeop?")upload_globeop84,2699 + class Meta:Meta85,2761 + model = CDSDealmodel86,2777 + include_foreign_keys = Trueinclude_foreign_keys87,2801 + exclude = ['dealid', 'lastupdate']exclude88,2837 +class SwaptionForm(ModelForm):SwaptionForm90,2881 + upload_globeop = BooleanField(label="Upload to globeop?")upload_globeop91,2912 + class Meta:Meta92,2974 + model = SwaptionDealmodel93,2990 + include_foreign_keys = Trueinclude_foreign_keys94,3019 + exclude = ['dealid', 'lastupdate']exclude95,3055 +class FutureForm(ModelForm):FutureForm97,3099 + upload_globeop = BooleanField(label="Upload to globeop?")upload_globeop98,3128 + class Meta:Meta99,3190 + model = FutureDealmodel100,3206 + include_foreign_keys = Trueinclude_foreign_keys101,3233 + exclude = ['dealid', 'lastupdate']exclude102,3269 +def get_deal(kind):get_deal104,3313 +def _get_form(kind):_get_form116,3596 +def get_form(trade, kind):get_form128,3880 +def get_wire_form(wire):get_wire_form153,4819 +def get_trade(tradeid, kind):get_trade161,5011 +def save_ticket(trade, old_ticket_name):save_ticket165,5126 +def split_direction(g, direction):split_direction178,5610 +def gen_cashflow_deals(form, session, wire_id=None):gen_cashflow_deals190,6170 +def wire_manage(wire_id):wire_manage221,7514 +def trade_manage(tradeid, kind):trade_manage260,9590 +def list_trades(kind):list_trades296,11024 +def download_ticket(tradeid):download_ticket305,11329 +def list_counterparties(instr):list_counterparties318,11843 +def edit_counterparty(cpcode):edit_counterparty329,12370 +def get_bbg_id():get_bbg_id355,13280 -Dawn/views.py,2099 -fed_cal = get_calendar('USFederalHolidayCalendar')fed_cal19,656 -bond_cal = HolidayCalendarFactory('BondCalendar', fed_cal, GoodFriday)bond_cal20,707 -bus_day = CustomBusinessDay(calendar=bond_cal())bus_day21,778 -def cp_choices():cp_choices23,828 -def get_queue():get_queue27,962 -def get_db():get_db37,1284 -def close_connection(exception):close_connection46,1590 -class CounterpartyForm(ModelForm):CounterpartyForm51,1705 - class Meta:Meta52,1740 - model = Counterpartiesmodel53,1756 - include_primary_keys = Trueinclude_primary_keys54,1787 -class BondForm(ModelForm):BondForm56,1824 - upload_globeop = BooleanField(label="Upload to globeop?")upload_globeop57,1851 - class Meta:Meta58,1913 - model = BondDealmodel59,1929 - include_foreign_keys = Trueinclude_foreign_keys60,1954 - exclude = ['dealid', 'lastupdate', #we generate it with a trigger at the server levelexclude61,1990 -class CDSForm(ModelForm):CDSForm64,2144 - upload_globeop = BooleanField(label="Upload to globeop?")upload_globeop65,2170 - class Meta:Meta66,2232 - model = CDSDealmodel67,2248 - include_foreign_keys = Trueinclude_foreign_keys68,2272 - exclude = ['dealid', 'lastupdate']exclude69,2308 -class SwaptionForm(ModelForm):SwaptionForm71,2352 - upload_globeop = BooleanField(label="Upload to globeop?")upload_globeop72,2383 - class Meta:Meta73,2445 - model = SwaptionDealmodel74,2461 - include_foreign_keys = Trueinclude_foreign_keys75,2490 - exclude = ['dealid', 'lastupdate']exclude76,2526 -def get_deal(kind):get_deal79,2571 -def get_form(trade, kind):get_form89,2801 -def get_trade(tradeid, kind):get_trade121,3922 -def save_ticket(trade, old_ticket_name):save_ticket125,4037 -def trade_manage(tradeid, kind):trade_manage141,4783 -def list_trades(kind):list_trades173,6110 -def download_ticket(tradeid):download_ticket180,6359 -def list_counterparties(instr):list_counterparties193,6877 -def edit_counterparty(cpcode):edit_counterparty204,7416 -def get_bbg_id():get_bbg_id230,8360 +Dawn/.ropeproject/config.py,90 +def set_prefs(prefs):set_prefs5,45 +def project_opened(project):project_opened110,4652 Dawn/templates/swaption_blotter.html,0 +Dawn/templates/wire_blotter.html,0 + Dawn/templates/trade_entry.html,0 +Dawn/templates/wire_entry.html,0 + Dawn/templates/edit_cp.html,0 Dawn/templates/base.html,0 @@ -1691,13 +2092,13 @@ Dawn/templates/cds_blotter.html,0 Dawn/templates/bond_blotter.html,0 +Dawn/templates/future_blotter.html,0 + Dawn/templates/counterparties.html,0 -Dawn/utils.py,197 -def load_counterparties(engine):load_counterparties7,103 -def load_trades(engine):load_trades26,1441 -def bump_rev(filename):bump_rev57,3057 -def simple_serialize(obj):simple_serialize63,3299 +Dawn/utils.py,89 +def bump_rev(filename):bump_rev6,66 +def simple_serialize(obj):simple_serialize12,308 trade_template.py,234 default = "\underline{\hspace{1cm}}"default3,29 @@ -1711,12 +2112,12 @@ fed_cal = get_calendar('USFederalHolidayCalendar')fed_cal9,259 bond_cal = HolidayCalendarFactory('BondCalendar', fed_cal, GoodFriday)bond_cal10,310 bus_day = CustomBusinessDay(calendar=bond_cal())bus_day11,381 def imm_dates(start_date, end_date):imm_dates13,431 -def previous_twentieth(d):previous_twentieth21,767 -def days_accrued(tradedate):days_accrued30,982 -def isleapyear(date):isleapyear40,1427 -def yearfrac(date1, date2, daycount):yearfrac43,1535 -class TestDaysAccrued(unittest.TestCase):TestDaysAccrued60,2077 - def test(self):test61,2119 +def previous_twentieth(d):previous_twentieth21,771 +def days_accrued(tradedate):days_accrued30,986 +def isleapyear(date):isleapyear40,1431 +def yearfrac(date1, date2, daycount):yearfrac43,1539 +class TestDaysAccrued(unittest.TestCase):TestDaysAccrued60,2081 + def test(self):test61,2123 bbg_newids.py,1671 engine = create_engine('postgresql://et_user@debian/ET')engine7,220 @@ -1743,50 +2144,29 @@ pd_colnames = ['ID_BB_UNIQUE','LAST_UPDATE_DT','PX_LAST','LN_CURRENT_MARGIN',pd sql_colnames = [c.name for c in bloomberg_corp.columns]sql_colnames72,3462 to_insert2 = df.filter(pd_colnames)to_insert273,3518 -option_exploration.py,1906 -SQL_CON = 'postgresql://serenitas_user@debian/serenitasdb'SQL_CON16,220 -df = pd.read_sql_table('swaption_quotes', SQL_CON, index_col=['quotedate', 'index', 'series', 'expiry'])df17,279 -index_data = pd.read_sql_table('swaption_ref_quotes', SQL_CON, index_col=['quotedate', 'index', 'series', 'expiry'])index_data18,384 -def atm_vol_fun(k, v, moneyness = 0.2):atm_vol_fun24,551 -df_filtered = df.groupby(df.index).filter(lambda x: len(x)>=2)df_filtered36,924 -grouped = df_filtered.groupby(df_filtered.index)grouped37,987 -ind = pd.MultiIndex.from_tuples(ind, names=['quotedate', 'indextype', 'series', 'expiry'])ind39,1112 -df_vol = pd.DataFrame({'atm_vol': atm_vol, 'otm_vol':otm_vol}, index=ind)df_vol40,1203 -df_vol = df_vol.reset_index(level=-1) #move expiry back to the columndf_vol41,1277 -def rolling_vol(df, col='atm_vol'):rolling_vol47,1433 - def aux(k, s, col):aux50,1588 -df_atm_vol_rolling = rolling_vol(df_vol)df_atm_vol_rolling58,2013 -df_otm_vol_rolling = rolling_vol(df_vol, 'otm_vol')df_otm_vol_rolling59,2054 -df_vol_rolling = df_atm_vol_rolling.join(df_otm_vol_rolling)df_vol_rolling60,2106 -df_compare = df_vol_rolling.unstack(level=1)df_compare65,2180 -df_27 = df_compare.xs(27, level='series')df_2766,2225 -df_27 = df_27.groupby(pd.TimeGrouper('D')).last().dropna()df_2767,2267 -df_compare = df_vol_rolling.unstack(level=1)df_compare73,2363 -df_26 = df_compare.xs(26, level='series')df_2674,2408 -df_26 = df_26.groupby(pd.TimeGrouper('D')).last().dropna()df_2675,2450 -df_compare = df_vol_rolling.unstack(level=1)df_compare81,2545 -df_25 = df_compare.xs(25, level='series')df_2582,2590 -df_25 = df_25.groupby(pd.TimeGrouper('D')).last().dropna()df_2583,2632 -skew = df_26.otm_vol.IG-df_26.atm_vol.IGskew94,2788 -skew = df_27.otm_vol.IG-df_27.atm_vol.IGskew100,2854 -ig26_vol = df_vol_rolling.xs(('IG', 26), level=['indextype','series'])ig26_vol106,2920 - -process_queue.py,1031 -HEADERS = {'bond_trades':['Deal Type', 'Deal ID', 'Action', 'Client', 'Reserved', 'Reserved',HEADERS27,546 -def decode_dict(d):decode_dict80,4858 -def get_redis_queue():get_redis_queue84,5013 -def get_effective_date(d):get_effective_date96,5353 -def aux(v):aux99,5443 -def get_trades(q, queue_name='bond_trades'):get_trades109,5689 -def build_line(obj, queue_name='bond_trades'):build_line123,6188 -def get_bbg_data(conn, session, identifier, cusip=None, isin = None, settle_date = None, asset_class=None,get_bbg_data218,10495 -def bond_trade_process(conn, session, trade):bond_trade_process273,13383 -def cds_trade_process(serenitasdb, dawndb, session, trade):cds_trade_process293,14303 -def generate_csv(l, queue_name='bond_trades'):generate_csv308,14917 -def get_filename(timestamp, queue_name):get_filename319,15274 -def upload_file(timestamp, queue_name='bond_trades'):upload_file325,15529 -def write_buffer(buf, queue_name='bond_trades'):write_buffer337,16011 -def email_subject(trade):email_subject347,16395 +process_queue.py,1414 +HEADERS = {'bond_trades': [HEADERS25,531 +def get_effective_date(d):get_effective_date101,5942 +def get_trades(q, queue_name='bond_trades'):get_trades104,6032 +def rename_keys(d, mapping):rename_keys122,6684 +def build_line(obj, queue_name='bond_trades'):build_line128,6865 +def get_bbg_data(conn, session, identifier, cusip=None, isin = None, settle_date = None, asset_class=None,get_bbg_data236,12001 +def bond_trade_process(conn, session, trade):bond_trade_process291,14889 +def cds_trade_process(serenitasdb, dawndb, session, trade):cds_trade_process317,15994 +def generate_csv(l, queue_name='bond_trades'):generate_csv332,16604 +def get_filename(timestamp, queue_name):get_filename343,16961 +def upload_file(timestamp, queue_name='bond_trades'):upload_file351,17287 +def write_buffer(buf, queue_name='bond_trades'):write_buffer363,17769 +def email_subject(trade):email_subject373,18159 +def print_trade(trade):print_trade377,18399 + parser = argparse.ArgumentParser()parser383,18573 + args = parser.parse_args()args385,18711 + q = get_redis_queue()q386,18742 + serenitasdb = dbconn('serenitasdb')serenitasdb387,18768 + dawndb = dbconn('dawndb')dawndb388,18808 + list_trades = get_trades(q, queue_name)list_trades390,18936 + buf = generate_csv(list_trades, queue_name)buf401,19452 + timestamp = write_buffer(buf, queue_name)timestamp402,19508 task_server/__init__.py,320 app = Flask(__name__)app2,24 @@ -1795,26 +2175,26 @@ formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(messag loggers = [logging.getLogger('intex'), app.logger, logging.getLogger(__name__)]loggers11,294 task_server/insert_tranche_quotes.py,658 -logger = logging.getLogger(__name__)logger8,167 -engine = create_engine('postgresql://serenitas_user@debian/serenitasdb')engine10,207 -metadata = MetaData(bind = engine)metadata11,281 -quotes = Table('tranche_quotes', metadata, autoload = True)quotes12,317 -ins = quotes.insert()ins13,378 -def convert(x):convert15,403 -def convert_int(x):convert_int24,604 -tenordict = {'3': '3yr', '5': '5yr', '7':'7yr', '10':'10yr'}tenordict33,812 -runningdict1 = {0: 500, 3:100, 7:100, 15: 25}runningdict134,874 -runningdict2 = {0: 500, 3:500, 7:500, 10:100, 15:100, 30:100}runningdict235,921 -def insert_quotes(year=2016, quote_dir=None):insert_quotes37,986 +logger = logging.getLogger(__name__)logger8,160 +engine = create_engine('postgresql://serenitas_user@debian/serenitasdb')engine10,198 +metadata = MetaData(bind = engine)metadata11,271 +quotes = Table('tranche_quotes', metadata, autoload = True)quotes12,306 +ins = quotes.insert()ins13,366 +def convert(x):convert15,389 +def convert_int(x):convert_int24,581 +tenordict = {'3': '3yr', '5': '5yr', '7':'7yr', '10':'10yr'}tenordict33,780 +runningdict1 = {0: 500, 3:100, 7:100, 15: 25}runningdict134,841 +runningdict2 = {0: 500, 3:500, 7:500, 10:100, 15:100, 30:100}runningdict235,887 +def insert_quotes(year=2016, quote_dir=None):insert_quotes37,950 task_server/rest.py,238 def get_db():get_db11,283 def get_queue():get_queue20,584 def close_db(error):close_db27,768 def intex():intex34,948 -def globeop():globeop40,1113 -def insert_tranches():insert_tranches46,1358 -def run_tasks():run_tasks51,1466 +def globeop():globeop40,1116 +def insert_tranches():insert_tranches46,1364 +def run_tasks():run_tasks51,1475 task_server/__main__.py,565 level=logging.INFO,level9,224 @@ -1827,6 +2207,10 @@ group = parser.add_mutually_exclusive_group(required=True)group13,354 args = parser.parse_args()args22,896 engine = create_engine('postgresql://dawn_user@debian/dawndb')engine27,996 +task_server/.ropeproject/config.py,90 +def set_prefs(prefs):set_prefs5,45 +def project_opened(project):project_opened110,4652 + task_server/config.py,330 ftp_password = 'B6#dEu7V'ftp_password1,0 key_password = 'Serenitas;1'key_password2,27 @@ -1835,17 +2219,20 @@ gmail_login = 'david.weeks@serenitascapital.com'gmail_login4,87 markit_password = 'Welcome3!'markit_password5,137 markit_login = 'guillaume.horel@serenitascapital.com'markit_login6,168 -task_server/globeop.py,455 -logger = logging.getLogger(__name__)logger12,200 -def get_ped(s):get_ped20,349 -def key_fun(s):key_fun30,655 -def run_date(s):run_date40,972 -def get_ftp(folder):get_ftp47,1170 -def get_gpg():get_gpg53,1313 -def download_data(workdate):download_data62,1659 -def upload_bond_marks(engine, workdate):upload_bond_marks111,4030 -def upload_cds_marks(engine, workdate):upload_cds_marks123,4637 -def upload_data(engine, workdate):upload_data135,5251 +task_server/globeop.py,619 +logger = logging.getLogger(__name__)logger15,263 +def get_ped(s):get_ped23,412 +def key_fun(s):key_fun33,725 +def run_date(s):run_date43,1042 +def get_ftp(folder):get_ftp50,1240 +def get_gpg():get_gpg56,1383 +def convert_to_csv(f):convert_to_csv65,1743 +def download_data(workdate):download_data71,1954 +def insert_todb(workdate):insert_todb120,4076 +def upload_bond_marks(engine, workdate):upload_bond_marks140,5075 +def upload_cds_marks(engine, workdate):upload_cds_marks152,5683 +def upload_data(engine, workdate):upload_data164,6298 +def back_fill(start_date=pd.datetime(2017,7,20)):back_fill168,6417 parse_gs.py,2375 data_dir = "/home/share/guillaume/swaptions"data_dir6,52 @@ -1913,6 +2300,13 @@ df2bis = pd.read_sql_query("SELECT date FROM test WHERE date<='2014-10-17'",df2 df3 = pd.read_sql_query("SELECT date FROM test", engine,df311,376 parse_dates=['date'])parse_dates12,433 +experiments/test_async.py,157 +async def pomme():pomme3,16 +async def poire():poire8,106 +async def main():main13,196 +async def ping(msg):ping18,275 +async def pong(msg):pong26,416 + experiments/test_trace.py,359 df = pd.read_clipboard(header=None)df5,101 trace_data = {}trace_data6,137 @@ -1920,10 +2314,34 @@ trace_data = {}trace_data6,137 start_date=datetime.datetime(2016, 5, 22, 12, 42),start_date11,337 end_date=datetime.datetime(2017, 5, 22, 18, 42))end_date12,430 -experiments/test_asyncpg.py,169 -async def dbconn():dbconn5,47 -async def get_singlenames_quotes_async(indexname, date):get_singlenames_quotes_async10,235 -loop = asyncio.get_event_loop()loop20,627 +experiments/test_dask.py,721 +strip_percent = lambda s: float(s.rstrip('%'))/100 if s else np.nanstrip_percent4,48 +tenors = ['6m'] + [f'{y}y' for y in [1, 2, 3, 4, 5, 7, 10, 15, 20, 30]]tenors5,116 + for t in tenors}converters8,233 +dtype = {'Rating' + t: 'object' for t in tenors}dtype10,303 +df = dd.read_csv("/home/guillaume/composites/*.csv",df14,483 + skiprows=2,skiprows15,536 + converters=converters,converters16,556 + dtype=dtype,dtype17,587 + parse_dates=['Date'])parse_dates18,608 + ["Rating" + t for t in tenors]to_categorize22,802 +df = df.categorize(columns=to_categorize, index=False)df23,841 +df = df.set_index("Date")df24,896 +df = df.repartition(npartitions=100)df25,922 + +experiments/.ropeproject/config.py,90 +def set_prefs(prefs):set_prefs5,45 +def project_opened(project):project_opened110,4652 + +experiments/test_basket.py,138 +ig29 = TrancheBasket("IG", 29, "5yr", trade_date=pd.Timestamp.today().normalize() - BDay())ig294,96 +df = ig29.tranche_deltas()df8,220 + +experiments/test_asyncpg.py,235 +async def dbconn():dbconn10,178 +async def get_singlenames_quotes_async(con, indexname, date):get_singlenames_quotes_async16,388 +async def get_curves(con, currency="USD", date=None):get_curves24,738 +async def main():main29,1022 experiments/exchange_example.py,369 credentials = Credentials(username='LEEMUNDER\\ghorel', password='')credentials3,46 @@ -1954,8 +2372,9 @@ df = df.unstack(level=0).stack(level=0).reset_index(level=1)df12,378 tranche_quotes = df.join(index_quotes)tranche_quotes20,813 index_label='quotedate')index_label27,1292 -common.py,52 -def sanitize_float(intex_float):sanitize_float1,0 +common.py,99 +def sanitize_float(intex_float):sanitize_float6,50 +def get_redis_queue():get_redis_queue18,445 futures.py,1105 ticker = "GE"ticker11,178 @@ -1987,31 +2406,40 @@ def plot_allocation(W, fund_return, fund_vol):plot_allocation60,2146 delta = {'CLO': 0.4,delta82,2810 mu = np.array([0.01, 0.075, 0.065, 0.25])mu85,2890 -download_markit_quotes.py,484 - level=logging.INFO,level17,687 - format='%(asctime)s %(message)s')format18,727 -profile = FirefoxProfile()profile21,871 -driver = Firefox(profile)driver27,1181 -menu = WebDriverWait(driver, 10).until(EC.element_to_be_clickable((By.CSS_SELECTOR,menu34,1586 -hiddenmenu = WebDriverWait(driver, 10).until(hiddenmenu38,1806 - link = WebDriverWait(driver, 10).until(EC.element_to_be_clickable(link46,2142 -total_wait = 0total_wait57,2559 +download_markit_quotes.py,478 + level=logging.INFO,level17,720 + format='%(asctime)s %(message)s')format18,760 +profile = FirefoxProfile()profile21,904 +driver = Firefox(profile)driver27,1214 + menu = WebDriverWait(driver, 15).until(EC.element_to_be_clickable((By.ID,menu35,1474 +hiddenmenu = WebDriverWait(driver, 10).until(hiddenmenu45,1789 + link = WebDriverWait(driver, 10).until(EC.element_to_be_clickable(link53,2069 +total_wait = 0total_wait63,2446 + +mark_backtest_backfill.py,273 +def runAllFill():runAllFill15,307 +def runSingleFill(f):runSingleFill21,464 +def get_CUSIPs():get_CUSIPs51,1733 +def get_BVAL():get_BVAL57,1930 +def pop_BVAL_to_database(df):pop_BVAL_to_database74,2685 +def get_globs():get_globs87,3161 +settings = {settings99,3701 load_cf.py,1172 def sanitize_float(string):sanitize_float20,588 def processzipfiles(tradedate=datetime.date.today()):processzipfiles31,841 -def get_configfile(dealname, tradedate):get_configfile51,1915 -def get_dist(date):get_dist61,2293 -def get_dealdata(dealname, tradedate):get_dealdata67,2564 -def get_cusipdata(cusip, tradedate):get_cusipdata75,3017 -def get_dealschedule(dealdata, freq='1Mo', adj=Unadjusted):get_dealschedule80,3220 -def dealname_from_cusip(conn, cusips):dealname_from_cusip87,3670 -def discounts(tradedate):discounts93,3854 -def getdealcf(dealnames, zipfiles, tradedate = datetime.date.today()):getdealcf104,4411 -def getcusipcf(params, cfdata, tradedate):getcusipcf145,6423 -def compute_delta(dist, dealweight, cusip_pv, tradedate, K1 = 0, K2 = 1):compute_delta178,8290 - tradedate = datetime.datetime.strptime(sys.argv[1], "%Y-%m-%d").date()tradedate189,8766 - tradedate = datetime.date.today()tradedate191,8857 - params = processzipfiles(tradedate)params192,8900 - cfdata = getdealcf(params["dealnames"], params["zipfiles"], tradedate)cfdata193,8941 - cusipdata = getcusipcf(params, cfdata, tradedate)cusipdata194,9017 +def get_configfile(dealname, tradedate):get_configfile51,1913 +def get_dist(date):get_dist61,2291 +def get_dealdata(dealname, tradedate):get_dealdata67,2562 +def get_cusipdata(cusip, tradedate):get_cusipdata75,3015 +def get_dealschedule(dealdata, freq='1Mo', adj=Unadjusted):get_dealschedule80,3218 +def dealname_from_cusip(conn, cusips):dealname_from_cusip87,3668 +def discounts(tradedate):discounts93,3852 +def getdealcf(dealnames, zipfiles, tradedate = datetime.date.today()):getdealcf104,4409 +def getcusipcf(params, cfdata, tradedate):getcusipcf145,6421 +def compute_delta(dist, dealweight, cusip_pv, tradedate, K1 = 0, K2 = 1):compute_delta178,8288 + tradedate = datetime.datetime.strptime(sys.argv[1], "%Y-%m-%d").date()tradedate189,8764 + tradedate = datetime.date.today()tradedate191,8855 + params = processzipfiles(tradedate)params192,8898 + cfdata = getdealcf(params["dealnames"], params["zipfiles"], tradedate)cfdata193,8939 + cusipdata = getcusipcf(params, cfdata, tradedate)cusipdata194,9015 diff --git a/python/analytics/__init__.py b/python/analytics/__init__.py index da3b5ae7..1dc1e24f 100644 --- a/python/analytics/__init__.py +++ b/python/analytics/__init__.py @@ -1,5 +1,6 @@ from .index import Index, ForwardIndex -from .option import BlackSwaption, Swaption, VolatilitySurface, ATMstrike, ProbSurface, QuoteSurface, VolSurface +from .option import (BlackSwaption, Swaption, ATMstrike, ProbSurface, + QuoteSurface, VolSurface, BlackSwaptionVolSurface) from .portfolio import Portfolio from .basket_index import MarkitBasketIndex from .tranche_basket import TrancheBasket diff --git a/python/analytics/option.py b/python/analytics/option.py index 4721dfbc..949ea224 100644 --- a/python/analytics/option.py +++ b/python/analytics/option.py @@ -596,7 +596,6 @@ class ModelBasedVolSurface(VolSurface): ax.set_ylabel("Moneyness") ax.set_zlabel("Volatility") - class BlackSwaptionVolSurface(ModelBasedVolSurface): pass @@ -702,10 +701,10 @@ def calib_sabr(x, option, strikes, pv, beta): r[i] = option.pv - pv[i] return r -class SABRVolatilitySurface(VolatilitySurface): +class SABRVolSurface(VolSurface): def __init__(self, index_type, series, tenor='5yr', trade_date=datetime.date.today(), beta=None): - VolatilitySurface.__init__(self, index_type, series, tenor='5yr', + VolSurface.__init__(self, index_type, series, tenor='5yr', trade_date=datetime.date.today()) if index_type == "HY": self.beta = 3.19 diff --git a/python/analytics/portfolio.py b/python/analytics/portfolio.py index 50b43477..bea0f5cd 100644 --- a/python/analytics/portfolio.py +++ b/python/analytics/portfolio.py @@ -1,5 +1,5 @@ from .index import Index -from .option import BlackSwaption, VolatilitySurface +from .option import BlackSwaption, BlackSwaptionVolSurface from db import dbengine from warnings import warn import pandas as pd @@ -87,7 +87,7 @@ class Portfolio: k = (index.trade_date, index_type, series, tenor) if self.swaptions: if k not in self._vs: - vs = VolatilitySurface(index_type, series, tenor, index.trade_date) + vs = BlackSwaptionVolSurface(index_type, series, tenor, index.trade_date) if surface_id is None: for source in source_list: if len(vs.list(source, option_type, model)) >=1: diff --git a/python/exploration/portfolio_example.py b/python/exploration/portfolio_example.py index ebaa6b3b..6b72a2c1 100644 --- a/python/exploration/portfolio_example.py +++ b/python/exploration/portfolio_example.py @@ -1,24 +1,8 @@ from analytics import (Portfolio, BlackSwaption, Index, - VolatilitySurface, Swaption) + BlackSwaptionVolSurface, Swaption) from analytics.scenarios import run_portfolio_scenarios import pandas as pd -from pandas.tseries.offsets import BDay import numpy as np -import datetime - -# option_delta = Index.from_tradeid(874) -# option1 = BlackSwaption.from_tradeid(7, option_delta) -# option2 = BlackSwaption.from_tradeid(8, option_delta) - -# portf = Portfolio([option1, option2, option_delta]) -# date_range = pd.bdate_range(option_delta.trade_date, -# pd.Timestamp('2017-05-01'), freq = 'B') -# pnl = [] -# for date in date_range: -# portf.trade_date = date.date() -# portf.mark(source_list=["BAML", "GS"], model="black") -# pnl.append(portf.pnl) -# df = pd.DataFrame({'pnl': pnl}, index=date_range) option_delta = Index.from_tradeid(870) option1 = BlackSwaption.from_tradeid(5, option_delta) @@ -26,22 +10,10 @@ option2 = BlackSwaption.from_tradeid(6, option_delta) portf = Portfolio([option1, option2, option_delta]) date_range = pd.bdate_range(option_delta.trade_date, - pd.Timestamp('2017-04-19'), freq = 'W') + pd.Timestamp('2017-04-19'), freq='W') vol_shock = np.arange(-0.15, 0.3, 0.01) spread_shock = np.arange(-0.2, 0.3, 0.01) -vs = VolatilitySurface("IG", 27, trade_date=option_delta.trade_date) -vol_surface = vs[vs.list(model="black")[-1]] +vs = BlackSwaptionVolSurface("IG", 27, trade_date=option_delta.trade_date) +vol_surface = vs[vs.list()[-1]] df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface, ['pv', 'delta']) - -# pnl = [] -# for date in date_range: -# portf.trade_date = date.date() -# try: -# portf.mark(source_list=["BAML", "GS"], model="black") -# except ValueError: -# pnl.append(None) -# continue -# else: -# pnl.append(portf.pnl) -# df = pd.DataFrame({'pnl': pnl}, index=date_range) diff --git a/python/exploration/portfolio_var.py b/python/exploration/portfolio_var.py index 7fba2ba2..65b1f113 100644 --- a/python/exploration/portfolio_var.py +++ b/python/exploration/portfolio_var.py @@ -1,5 +1,5 @@ from index_data import get_index_quotes, index_returns, _serenitas_engine -from analytics import Swaption, BlackSwaption, Index, VolatilitySurface, Portfolio +from analytics import Index, Portfolio from db import dbengine, dbconn from pandas.tseries.offsets import BDay, BMonthEnd from copy import deepcopy diff --git a/python/exploration/swaption_calendar_spread.py b/python/exploration/swaption_calendar_spread.py index d703bbe7..e21ffd66 100644 --- a/python/exploration/swaption_calendar_spread.py +++ b/python/exploration/swaption_calendar_spread.py @@ -1,7 +1,8 @@ import sys #don't do this at home sys.path.append("..") -from analytics import Swaption, BlackSwaption, Index, VolatilitySurface, Portfolio +from analytics import (Swaption, BlackSwaption, BlackSwaptionVolSurface, + Index, ProbSurface, Portfolio) from analytics.scenarios import run_swaption_scenarios, run_index_scenarios, run_portfolio_scenarios from pandas.tseries.offsets import BDay import datetime @@ -9,19 +10,15 @@ import numpy as np import pandas as pd from scipy.interpolate import SmoothBivariateSpline -from mpl_toolkits.mplot3d import Axes3D -import matplotlib.pyplot as plt - import os import numpy as np import matplotlib import matplotlib.pyplot as plt -from graphics import plot_time_color_map +from graphics import plot_time_color_map, plot_color_map from db import dbengine engine = dbengine('serenitasdb') - def plot_df(df, spread_shock, vol_shock, attr="pnl"): val_date = df.index[0].date() fig = plt.figure() @@ -37,44 +34,17 @@ def plot_df(df, spread_shock, vol_shock, attr="pnl"): ax.set_zlabel("PnL") ax.set_title('{} of Trade on {}'.format(attr.title(), val_date)) -def plot_color_map(df, spread_shock, vol_shock, attr="pnl", path=".", index ='IG'): - - val_date = df.index[0].date() - #rows are spread, columns are volatility surface shift - fig, ax = plt.subplots() - #We are plotting an image, so we have to sort from high to low on the Y axis - ascending = [False,False] if index == 'HY' else [True,False] - df.sort_values(by=['spread','vol_shock'], ascending = ascending, inplace = True) - series = df[attr] - - midpoint = 1 - series.max() / (series.max() + abs(series.min())) - shifted_cmap = shiftedColorMap(cm.RdYlGn, midpoint=midpoint, name='shifted') - - chart = ax.imshow(series.values.reshape(spread_shock.size, vol_shock.size).T, - extent=(spread_shock.min(), spread_shock.max(), - vol_shock.min(), vol_shock.max()), - aspect='auto', interpolation='bilinear', cmap=shifted_cmap) - - ax.set_xlabel('Price') if index == 'HY' else ax.set_xlabel('Spread') - ax.set_ylabel('Volatility shock') - ax.set_title('{} of Trade on {}'.format(attr.title(), val_date)) - - fig.colorbar(chart, shrink=.8) - #fig.savefig(os.path.join(path, "vol_spread_color_map"+ attr+ "_{}.png".format(val_date))) - -def plot_trade_scenarios(portf, shock_min=-.15, shock_max=.2, period = -1, vol_time_roll=True): - +def plot_trade_scenarios(portf, shock_min=-.15, shock_max=.2, period=-1, vol_time_roll=True): portf.reset_pv() earliest_date = min(portf.swaptions, key=lambda x: x.exercise_date).exercise_date - #earliest_date = max(portf.swaptions,key=attrgetter('exercise_date')).exercise_date - date_range = pd.bdate_range(portf.indices[0].trade_date, earliest_date - BDay(), freq = '3B') + date_range = pd.bdate_range(portf.indices[0].trade_date, + earliest_date - BDay(), freq='3B') vol_shock = np.arange(-0.15, 0.3, 0.01) spread_shock = np.arange(shock_min, shock_max, 0.01) index = portf.indices[0].name.split()[1] series = portf.indices[0].name.split()[3][1:] - vs = VolatilitySurface(index, series, trade_date=portf.indices[0].trade_date) - vol_select = vs.list(option_type='payer', model='black')[-1] - vol_surface = vs[vol_select] + vs = BlackSwaptionVolSurface(index, series, trade_date=portf.indices[0].trade_date) + vol_surface = vs[vs.list(option_type='payer')[-1]] df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface, params=["pnl","delta"]) @@ -86,44 +56,11 @@ def plot_trade_scenarios(portf, shock_min=-.15, shock_max=.2, period = -1, vol_t plot_time_color_map(df[round(df.vol_shock,2)==0], shock, 'pnl', index=index) plot_time_color_map(df[round(df.vol_shock,2)==.2], shock, 'pnl', index=index) - #plot_time_color_map(df[round(df.vol_shock,2)==0], shock, 'delta', color_map = cm.coolwarm_r, index=index) plot_color_map(df.loc[date_range[period]], shock, vol_shock, 'pnl', index=index) - #plot_df(df.loc[date_range[period]], shock, vol_shock) return df def exercise_probability(): - - from analytics import Swaption, BlackSwaption, Index, VolatilitySurface, Portfolio, ProbSurface, QuoteSurface, VolSurface - from analytics.scenarios import run_swaption_scenarios, run_index_scenarios, run_portfolio_scenarios - import datetime - from operator import attrgetter - - import exploration.swaption_calendar_spread as spread - - import sys - #don't do this at home - from pandas.tseries.offsets import BDay - import datetime - import numpy as np - import pandas as pd - from scipy.interpolate import SmoothBivariateSpline - from matplotlib import cm - from mpl_toolkits.mplot3d import Axes3D - import matplotlib.pyplot as plt - from operator import attrgetter - - import os - import numpy as np - import matplotlib - import matplotlib.pyplot as plt - from mpl_toolkits.axes_grid1 import AxesGrid - - import re - from db import dbengine engine = dbengine('serenitasdb') - - #import swaption_calendar_spread as spread - #Ad hoc option_delta = Index.from_name('HY', 29, '5yr') option_delta.price = 107.875 @@ -141,18 +78,12 @@ def exercise_probability(): portf = Portfolio([option1, option2, option_delta]) portf.reset_pv() - earliest_date = min(portf.swaptions,key=attrgetter('exercise_date')).exercise_date - date_range = pd.bdate_range(portf.indices[0].trade_date, earliest_date - BDay(), freq = '5B') + earliest_date = min(portf.swaptions, key=lambda x: x.exercise_date).exercise_date + date_range = pd.bdate_range(portf.indices[0].trade_date, earliest_date - BDay(), freq='5B') vol_shock = np.arange(-0.15, 0.3, 0.01) spread_shock = np.arange(-0.15, 0.35, 0.01) index = portf.indices[0].name.split()[1] series = portf.indices[0].name.split()[3][1:] - vs = QuoteSurface(index, series, trade_date=portf.indices[0].trade_date) - - vs = VolatilitySurface(index, series, trade_date=portf.indices[0].trade_date) - vol_select = vs.list(option_type='payer', model='black')[-1] - vol_surface = vs[vol_select] - - prob = vs.prob_surf(vol_select) - vs.prob_plot(vol_select) + vs = ProbSurface(index, series, trade_date=portf.indices[0].trade_date) + vs.plot(vs.list()[-1]) diff --git a/python/exploration/tranches.py b/python/exploration/tranches.py index 094c3e9b..028d41b1 100644 --- a/python/exploration/tranches.py +++ b/python/exploration/tranches.py @@ -7,7 +7,7 @@ import analytics.basket_index as idx_bkt import numpy as np import pandas as pd -from analytics import Swaption, BlackSwaption, Index, VolatilitySurface, Portfolio +from analytics import Swaption, BlackSwaption, Index, BlackSwaptionVolSurface, Portfolio from analytics.scenarios import run_swaption_scenarios, run_index_scenarios, run_portfolio_scenarios import exploration.swaption_calendar_spread as spread from scipy.interpolate import interp1d @@ -164,9 +164,8 @@ def run_scen(trade_date = pd.Timestamp.today().normalize()- pd.offsets.BDay()): spread_shock = np.arange(shock_min, shock_max, 0.05) index = portf.indices[0].name.split()[1] series = portf.indices[0].name.split()[3][1:] - vs = VolatilitySurface(index, series, trade_date=trade_date) - vol_select = vs.list(option_type='payer', model='black')[-1] - vol_surface = vs[vol_select] + vs = BlackSwaptionVolaSurface(index, series, trade_date=trade_date) + vol_surface = vs[vs.list(option_type='payer')[-1]] df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface, params=["pnl","delta"]) diff --git a/python/graphics.py b/python/graphics.py index 0f348a04..3a88147a 100644 --- a/python/graphics.py +++ b/python/graphics.py @@ -1,6 +1,7 @@ import numpy as np import matplotlib.pyplot as plt from matplotlib import cm +from matplotlib.colors import LinearSegmentedColormap def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name='shiftedcmap'): ''' @@ -48,7 +49,7 @@ def shiftedColorMap(cmap, start=0, midpoint=0.5, stop=1.0, name='shiftedcmap'): cdict['blue'].append((si, b, b)) cdict['alpha'].append((si, a, a)) - newcmap = matplotlib.colors.LinearSegmentedColormap(name, cdict) + newcmap = LinearSegmentedColormap(name, cdict) plt.register_cmap(cmap=newcmap) return newcmap @@ -82,3 +83,28 @@ def plot_time_color_map(df, spread_shock, attr="pnl", path=".", color_map=cm.RdY fig.colorbar(chart, shrink=.8) #fig.savefig(os.path.join(path, "spread_time_color_map_"+ attr+ "_{}.png".format(val_date))) + +def plot_color_map(df, spread_shock, vol_shock, attr="pnl", path=".", index='IG'): + # TODO: merge with plot_time_color_map + val_date = df.index[0].date() + #rows are spread, columns are volatility surface shift + fig, ax = plt.subplots() + #We are plotting an image, so we have to sort from high to low on the Y axis + ascending = [False,False] if index == 'HY' else [True,False] + df.sort_values(by=['spread','vol_shock'], ascending=ascending, inplace=True) + series = df[attr] + + midpoint = 1 - series.max() / (series.max() + abs(series.min())) + shifted_cmap = shiftedColorMap(cm.RdYlGn, midpoint=midpoint, name='shifted') + + chart = ax.imshow(series.values.reshape(spread_shock.size, vol_shock.size).T, + extent=(spread_shock.min(), spread_shock.max(), + vol_shock.min(), vol_shock.max()), + aspect='auto', interpolation='bilinear', cmap=shifted_cmap) + + ax.set_xlabel('Price') if index == 'HY' else ax.set_xlabel('Spread') + ax.set_ylabel('Volatility shock') + ax.set_title('{} of Trade on {}'.format(attr.title(), val_date)) + + fig.colorbar(chart, shrink=.8) + #fig.savefig(os.path.join(path, "vol_spread_color_map"+ attr+ "_{}.png".format(val_date))) diff --git a/python/notebooks/Option Trades.ipynb b/python/notebooks/Option Trades.ipynb index 58b32b5d..9aa46523 100644 --- a/python/notebooks/Option Trades.ipynb +++ b/python/notebooks/Option Trades.ipynb @@ -2,15 +2,15 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ - "from analytics import Swaption, BlackSwaption, Index, VolatilitySurface, Portfolio\n", + "from analytics import Swaption, BlackSwaption, BlackSwaptionVolSurface, Index, Portfolio\n", "from analytics.scenarios import run_swaption_scenarios, run_index_scenarios, run_portfolio_scenarios\n", "import datetime\n", "\n", - "import exploration.swaption_calendar_spread as spread\n", + "from exploration.swaption_calendar_spread import plot_trade_scenarios\n", "#import swaption_calendar_spread as spread" ] }, @@ -25,12 +25,830 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/guillaume/projects/code/python/analytics/option.py:577: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n", + " inplace=True)\n" + ] + }, + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('<div/>');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " fig.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n", + " 'ui-helper-clearfix\"/>');\n", + " var titletext = $(\n", + " '<div class=\"ui-dialog-title\" style=\"width: 100%; 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top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('<canvas/>');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('<div/>')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('<button/>');\n", + " button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n", + " 'ui-button-icon-only');\n", + " button.attr('role', 'button');\n", + " button.attr('aria-disabled', 'false');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + "\n", + " var icon_img = $('<span/>');\n", + " icon_img.addClass('ui-button-icon-primary ui-icon');\n", + " icon_img.addClass(image);\n", + " icon_img.addClass('ui-corner-all');\n", + "\n", + " var tooltip_span = $('<span/>');\n", + " tooltip_span.addClass('ui-button-text');\n", + " tooltip_span.html(tooltip);\n", + "\n", + " button.append(icon_img);\n", + " button.append(tooltip_span);\n", + "\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " var fmt_picker_span = $('<span/>');\n", + "\n", + " var fmt_picker = $('<select/>');\n", + " fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n", + " fmt_picker_span.append(fmt_picker);\n", + " nav_element.append(fmt_picker_span);\n", + " this.format_dropdown = fmt_picker[0];\n", + "\n", + " for (var ind in mpl.extensions) {\n", + " var fmt = mpl.extensions[ind];\n", + " var option = $(\n", + " '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n", + " fmt_picker.append(option)\n", + " }\n", + "\n", + " // Add hover states to the ui-buttons\n", + " $( \".ui-button\" ).hover(\n", + " function() { $(this).addClass(\"ui-state-hover\");},\n", + " function() { $(this).removeClass(\"ui-state-hover\");}\n", + " );\n", + "\n", + " var status_bar = $('<span class=\"mpl-message\"/>');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "}\n", + "\n", + "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n", + " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", + " // which will in turn request a refresh of the image.\n", + " this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n", + "}\n", + "\n", + "mpl.figure.prototype.send_message = function(type, properties) {\n", + " properties['type'] = type;\n", + " properties['figure_id'] = this.id;\n", + " this.ws.send(JSON.stringify(properties));\n", + "}\n", + "\n", + "mpl.figure.prototype.send_draw_message = function() {\n", + " if (!this.waiting) {\n", + " this.waiting = true;\n", + " this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n", + " }\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " var format_dropdown = fig.format_dropdown;\n", + " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", + " fig.ondownload(fig, format);\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype.handle_resize = function(fig, msg) {\n", + " var size = msg['size'];\n", + " if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n", + " fig._resize_canvas(size[0], size[1]);\n", + " fig.send_message(\"refresh\", {});\n", + " };\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n", + " var x0 = msg['x0'] / mpl.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n", + " var x1 = msg['x1'] / mpl.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n", + " x0 = Math.floor(x0) + 0.5;\n", + " y0 = Math.floor(y0) + 0.5;\n", + " x1 = Math.floor(x1) + 0.5;\n", + " y1 = Math.floor(y1) + 0.5;\n", + " var min_x = Math.min(x0, x1);\n", + " var min_y = Math.min(y0, y1);\n", + " var width = Math.abs(x1 - x0);\n", + " var height = Math.abs(y1 - y0);\n", + "\n", + " fig.rubberband_context.clearRect(\n", + " 0, 0, fig.canvas.width, fig.canvas.height);\n", + "\n", + " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n", + " // Updates the figure title.\n", + " fig.header.textContent = msg['label'];\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n", + " var cursor = msg['cursor'];\n", + " switch(cursor)\n", + " {\n", + " case 0:\n", + " cursor = 'pointer';\n", + " break;\n", + " case 1:\n", + " cursor = 'default';\n", + " break;\n", + " case 2:\n", + " cursor = 'crosshair';\n", + " break;\n", + " case 3:\n", + " cursor = 'move';\n", + " break;\n", + " }\n", + " fig.rubberband_canvas.style.cursor = cursor;\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_message = function(fig, msg) {\n", + " fig.message.textContent = msg['message'];\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_draw = function(fig, msg) {\n", + " // Request the server to send over a new figure.\n", + " fig.send_draw_message();\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n", + " fig.image_mode = msg['mode'];\n", + "}\n", + "\n", + "mpl.figure.prototype.updated_canvas_event = function() {\n", + " // Called whenever the canvas gets updated.\n", + " this.send_message(\"ack\", {});\n", + "}\n", + "\n", + "// A function to construct a web socket function for onmessage handling.\n", + "// Called in the figure constructor.\n", + "mpl.figure.prototype._make_on_message_function = function(fig) {\n", + " return function socket_on_message(evt) {\n", + " if (evt.data instanceof Blob) {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " evt.data.type = \"image/png\";\n", + "\n", + " /* Free the memory for the previous frames */\n", + " if (fig.imageObj.src) {\n", + " (window.URL || window.webkitURL).revokeObjectURL(\n", + " fig.imageObj.src);\n", + " }\n", + "\n", + " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", + " evt.data);\n", + " fig.updated_canvas_event();\n", + " fig.waiting = false;\n", + " return;\n", + " }\n", + " else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n", + " fig.imageObj.src = evt.data;\n", + " fig.updated_canvas_event();\n", + " fig.waiting = false;\n", + " return;\n", + " }\n", + "\n", + " var msg = JSON.parse(evt.data);\n", + " var msg_type = msg['type'];\n", + "\n", + " // Call the \"handle_{type}\" callback, which takes\n", + " // the figure and JSON message as its only arguments.\n", + " try {\n", + " var callback = fig[\"handle_\" + msg_type];\n", + " } catch (e) {\n", + " console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n", + " return;\n", + " }\n", + "\n", + " if (callback) {\n", + " try {\n", + " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", + " callback(fig, msg);\n", + " } catch (e) {\n", + " console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n", + " }\n", + " }\n", + " };\n", + "}\n", + "\n", + "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", + "mpl.findpos = function(e) {\n", + " //this section is from http://www.quirksmode.org/js/events_properties.html\n", + " var targ;\n", + " if (!e)\n", + " e = window.event;\n", + " if (e.target)\n", + " targ = e.target;\n", + " else if (e.srcElement)\n", + " targ = e.srcElement;\n", + " if (targ.nodeType == 3) // defeat Safari bug\n", + " targ = targ.parentNode;\n", + "\n", + " // jQuery normalizes the pageX and pageY\n", + " // pageX,Y are the mouse positions relative to the document\n", + " // offset() returns the position of the element relative to the document\n", + " var x = e.pageX - $(targ).offset().left;\n", + " var y = e.pageY - $(targ).offset().top;\n", + "\n", + " return {\"x\": x, \"y\": y};\n", + "};\n", + "\n", + "/*\n", + " * return a copy of an object with only non-object keys\n", + " * we need this to avoid circular references\n", + " * http://stackoverflow.com/a/24161582/3208463\n", + " */\n", + "function simpleKeys (original) {\n", + " return Object.keys(original).reduce(function (obj, key) {\n", + " if (typeof original[key] !== 'object')\n", + " obj[key] = original[key]\n", + " return obj;\n", + " }, {});\n", + "}\n", + "\n", + "mpl.figure.prototype.mouse_event = function(event, name) {\n", + " var canvas_pos = mpl.findpos(event)\n", + "\n", + " if (name === 'button_press')\n", + " {\n", + " this.canvas.focus();\n", + " this.canvas_div.focus();\n", + " }\n", + "\n", + " var x = canvas_pos.x * mpl.ratio;\n", + " var y = canvas_pos.y * mpl.ratio;\n", + "\n", + " this.send_message(name, {x: x, y: y, button: event.button,\n", + " step: event.step,\n", + " guiEvent: simpleKeys(event)});\n", + "\n", + " /* This prevents the web browser from automatically changing to\n", + " * the text insertion cursor when the button is pressed. We want\n", + " * to control all of the cursor setting manually through the\n", + " * 'cursor' event from matplotlib */\n", + " event.preventDefault();\n", + " return false;\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " // Handle any extra behaviour associated with a key event\n", + "}\n", + "\n", + "mpl.figure.prototype.key_event = function(event, name) {\n", + "\n", + " // Prevent repeat events\n", + " if (name == 'key_press')\n", + " {\n", + " if (event.which === this._key)\n", + " return;\n", + " else\n", + " this._key = event.which;\n", + " }\n", + " if (name == 'key_release')\n", + " this._key = null;\n", + "\n", + " var value = '';\n", + " if (event.ctrlKey && event.which != 17)\n", + " value += \"ctrl+\";\n", + " if (event.altKey && event.which != 18)\n", + " value += \"alt+\";\n", + " if (event.shiftKey && event.which != 16)\n", + " value += \"shift+\";\n", + "\n", + " value += 'k';\n", + " value += event.which.toString();\n", + "\n", + " this._key_event_extra(event, name);\n", + "\n", + " this.send_message(name, {key: value,\n", + " guiEvent: simpleKeys(event)});\n", + " return false;\n", + "}\n", + "\n", + "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n", + " if (name == 'download') {\n", + " this.handle_save(this, null);\n", + " } else {\n", + " this.send_message(\"toolbar_button\", {name: name});\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n", + " this.message.textContent = tooltip;\n", + "};\n", + "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", + "\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "\n", + "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n", + " // Create a \"websocket\"-like object which calls the given IPython comm\n", + " // object with the appropriate methods. Currently this is a non binary\n", + " // socket, so there is still some room for performance tuning.\n", + " var ws = {};\n", + "\n", + " ws.close = function() {\n", + " comm.close()\n", + " };\n", + " ws.send = function(m) {\n", + " //console.log('sending', m);\n", + " comm.send(m);\n", + " };\n", + " // Register the callback with on_msg.\n", + " comm.on_msg(function(msg) {\n", + " //console.log('receiving', msg['content']['data'], msg);\n", + " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", + " ws.onmessage(msg['content']['data'])\n", + " });\n", + " return ws;\n", + "}\n", + "\n", + "mpl.mpl_figure_comm = function(comm, msg) {\n", + " // This is the function which gets called when the mpl process\n", + " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", + "\n", + " var id = msg.content.data.id;\n", + " // Get hold of the div created by the display call when the Comm\n", + " // socket was opened in Python.\n", + " var element = $(\"#\" + id);\n", + " var ws_proxy = comm_websocket_adapter(comm)\n", + "\n", + " function ondownload(figure, format) {\n", + " window.open(figure.imageObj.src);\n", + " }\n", + "\n", + " var fig = new mpl.figure(id, ws_proxy,\n", + " ondownload,\n", + " element.get(0));\n", + "\n", + " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", + " // web socket which is closed, not our websocket->open comm proxy.\n", + " ws_proxy.onopen();\n", + "\n", + " fig.parent_element = element.get(0);\n", + " fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n", + " if (!fig.cell_info) {\n", + " console.error(\"Failed to find cell for figure\", id, fig);\n", + " return;\n", + " }\n", + "\n", + " var output_index = fig.cell_info[2]\n", + " var cell = fig.cell_info[0];\n", + "\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_close = function(fig, msg) {\n", + " var width = fig.canvas.width/mpl.ratio\n", + " fig.root.unbind('remove')\n", + "\n", + " // Update the output cell to use the data from the current canvas.\n", + " fig.push_to_output();\n", + " var dataURL = fig.canvas.toDataURL();\n", + " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", + " // the notebook keyboard shortcuts fail.\n", + " IPython.keyboard_manager.enable()\n", + " $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n", + " fig.close_ws(fig, msg);\n", + "}\n", + "\n", + "mpl.figure.prototype.close_ws = function(fig, msg){\n", + " fig.send_message('closing', msg);\n", + " // fig.ws.close()\n", + "}\n", + "\n", + "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n", + " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width/mpl.ratio\n", + " var dataURL = this.canvas.toDataURL();\n", + " this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n", + "}\n", + "\n", + "mpl.figure.prototype.updated_canvas_event = function() {\n", + " // Tell IPython that the notebook contents must change.\n", + " IPython.notebook.set_dirty(true);\n", + " this.send_message(\"ack\", {});\n", + " var fig = this;\n", + " // Wait a second, then push the new image to the DOM so\n", + " // that it is saved nicely (might be nice to debounce this).\n", + " setTimeout(function () { fig.push_to_output() }, 1000);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('<div/>')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items){\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) { continue; };\n", + "\n", + " var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n", + " var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " event.shiftKey = false;\n", + " // Send a \"J\" for go to next cell\n", + " event.which = 74;\n", + " event.keyCode = 74;\n", + " manager.command_mode();\n", + " manager.handle_keydown(event);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i<ncells; i++) {\n", + " var cell = cells[i];\n", + " if (cell.cell_type === 'code'){\n", + " for (var j=0; j<cell.output_area.outputs.length; j++) {\n", + " var data = cell.output_area.outputs[j];\n", + " if (data.data) {\n", + " // IPython >= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "<IPython.core.display.Javascript object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "<div id='89a7f060-3b6d-4fbd-84ea-ed955bd951da'></div>" + ], + "text/plain": [ + "<IPython.core.display.HTML object>" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "ename": "NameError", + "evalue": "name 'matplotlib' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m<ipython-input-8-de95e8fea496>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[0mportf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPortfolio\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0moption1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moption2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moption3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moption_delta\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0;31m#Plot Scenarios Inputs: Portfolio, spread shock tightening%, spread shock widening%, snapshot period)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 22\u001b[0;31m \u001b[0mplot_trade_scenarios\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mportf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m.15\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m.8\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m4\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvol_time_roll\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/projects/code/python/exploration/swaption_calendar_spread.py\u001b[0m in \u001b[0;36mplot_trade_scenarios\u001b[0;34m(portf, shock_min, shock_max, period, vol_time_roll)\u001b[0m\n\u001b[1;32m 55\u001b[0m \u001b[0mshock\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mhy_plot_range\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'HY'\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mportf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindices\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mspread\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mspread_shock\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 56\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 57\u001b[0;31m 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= BlackSwaption(option_delta, datetime.date(2018, 2, 21), 55, option_type=\"payer\")\n", "option2 = BlackSwaption(option_delta, datetime.date(2018, 2, 21), 67.5, option_type=\"payer\")\n", @@ -50,7 +868,7 @@ "option_delta.notional = abs(option_delta.notional)\n", "portf = Portfolio([option1, option2, option3, option_delta])\n", "#Plot Scenarios Inputs: Portfolio, spread shock tightening%, spread shock widening%, snapshot period)\n", - "df = spread.plot_trade_scenarios(portf, -.15, .8, -4, vol_time_roll=False)" + "plot_trade_scenarios(portf, -.15, .8, -4, vol_time_roll=False)" ] }, { @@ -101,7 +919,7 @@ "option1 = BlackSwaption.from_tradeid(3, option_delta)\n", "option2 = BlackSwaption.from_tradeid(4, option_delta)\n", "portf = Portfolio([option1, option2, option_delta])\n", - "spread.plot_trade_scenarios(portf)" + "plot_trade_scenarios(portf)" ] }, { @@ -115,7 +933,7 @@ "option1 = BlackSwaption.from_tradeid(5, option_delta)\n", "option2 = BlackSwaption.from_tradeid(6, option_delta)\n", "portf = Portfolio([option1, option2, option_delta])\n", - "spread.plot_trade_scenarios(portf)" + "plot_trade_scenarios(portf)" ] }, { @@ -129,7 +947,7 @@ "option1 = BlackSwaption.from_tradeid(7, option_delta)\n", "option2 = BlackSwaption.from_tradeid(8, option_delta)\n", "portf = Portfolio([option1, option2, option_delta])\n", - "spread.plot_trade_scenarios(portf)" + "plot_trade_scenarios(portf)" ] }, { @@ -149,7 +967,7 @@ "portf = Portfolio([option1_pf, option2_pf, option_delta_pf])\n", "portf.trade_date = datetime.date(2017, 5, 17)\n", "portf.mark()\n", - "spread.plot_trade_scenarios(portf)" + "plot_trade_scenarios(portf)" ] }, { @@ -163,7 +981,7 @@ "option1 = BlackSwaption.from_tradeid(10, option_delta)\n", "option2 = BlackSwaption.from_tradeid(11, option_delta)\n", "portf = Portfolio([option1, option2, option_delta])\n", - "spread.plot_trade_scenarios(portf)" + "plot_trade_scenarios(portf)" ] }, { @@ -197,7 +1015,7 @@ "option_delta.notional = abs(option_delta.notional)\n", "portf = Portfolio([option1, option2, option3, option4, option_delta])\n", "#Plot Scenarios Inputs: Portfolio, spread shock tightening%, spread shock widening%, snapshot period)\n", - "df = spread.plot_trade_scenarios(portf, -.15, .8, -4, vol_time_roll=False)" + "plot_trade_scenarios(portf, -.15, .8, -4, vol_time_roll=False)" ] }, { @@ -253,7 +1071,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.1" + "version": "3.6.4" } }, "nbformat": 4, diff --git a/python/tests/test_scenarios.py b/python/tests/test_scenarios.py index b7f5f9f0..4e695864 100644 --- a/python/tests/test_scenarios.py +++ b/python/tests/test_scenarios.py @@ -3,7 +3,7 @@ import datetime import numpy as np import pandas as pd -from analytics import Index, BlackSwaption, Portfolio, VolatilitySurface +from analytics import Index, BlackSwaption, Portfolio, BlackSwaptionVolSurface from pandas.tseries.offsets import BDay from analytics.scenarios import run_portfolio_scenarios, run_swaption_scenarios, run_index_scenarios @@ -18,8 +18,8 @@ class TestSenarios(unittest.TestCase): """ check that run_portfolio_scenarios match the sum of the individual pieces""" vol_shock = np.arange(-0.15, 0.3, 0.01) spread_shock = np.arange(-0.2, 0.3, 0.01) - vs = VolatilitySurface("IG", 28, trade_date=self.option_delta.trade_date) - vol_surface = vs[vs.list(model="black", source="BAML")[-1]] + vs = BlackSwaptionVolSurface("IG", 28, trade_date=self.option_delta.trade_date) + vol_surface = vs[vs.list(source="BAML")[-1]] df = run_portfolio_scenarios(self.portf, self.date_range, spread_shock, vol_shock, vol_surface) df = df.set_index(['spread', 'vol_shock'], append=True) |