diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/thetas-durations.py | 107 |
1 files changed, 67 insertions, 40 deletions
diff --git a/python/thetas-durations.py b/python/thetas-durations.py index bf7d41a7..3be12dbe 100644 --- a/python/thetas-durations.py +++ b/python/thetas-durations.py @@ -10,41 +10,51 @@ from pyisda.legs import FeeLeg, ContingentLeg from pyisda.curve import SpreadCurve from pyisda.date import previous_twentieth -tenors = {"IG": ("3yr", "5yr", "7yr", "10yr"), - "HY": ("3yr", "5yr", "7yr"), - "EU": ("3yr", "5yr", "7yr", "10yr"), - "XO": ("3yr", "5yr", "7yr", "10yr")} +tenors = { + "IG": ("3yr", "5yr", "7yr", "10yr"), + "HY": ("3yr", "5yr", "7yr"), + "EU": ("3yr", "5yr", "7yr", "10yr"), + "XO": ("3yr", "5yr", "7yr", "10yr"), +} sql_str = "INSERT INTO index_risk VALUES(%s, %s, %s)" + def get_legs(index, series, tenors): fee_legs = {} contingent_legs = {} - df = pd.read_sql_query("SELECT tenor, maturity, coupon, issue_date " - "FROM index_maturity " - "WHERE index=%s AND series=%s and tenor IN %s " - "ORDER BY maturity", - serenitas_engine, - params=(index, series, tenors), - parse_dates=['maturity', 'issue_date']) + df = pd.read_sql_query( + "SELECT tenor, maturity, coupon, issue_date " + "FROM index_maturity " + "WHERE index=%s AND series=%s and tenor IN %s " + "ORDER BY maturity", + serenitas_engine, + params=(index, series, tenors), + parse_dates=["maturity", "issue_date"], + ) df.coupon *= 1e-4 for tenor, maturity, coupon, issue_date in df.itertuples(index=False): maturity_short = maturity - relativedelta(years=1) - fee_legs[tenor] = (FeeLeg(issue_date, maturity, True, 1., 1.), - FeeLeg(issue_date, maturity_short, - True, 1., coupon)) - contingent_legs[tenor] = (ContingentLeg(issue_date, maturity, True), - ContingentLeg(issue_date, maturity_short, True)) + fee_legs[tenor] = ( + FeeLeg(issue_date, maturity, True, 1.0, 1.0), + FeeLeg(issue_date, maturity_short, True, 1.0, coupon), + ) + contingent_legs[tenor] = ( + ContingentLeg(issue_date, maturity, True), + ContingentLeg(issue_date, maturity_short, True), + ) # number of seconds since epoch # number of days between 1900-1-1 and epoch - df.maturity = (df.maturity.values.view("M8[D]").astype(int) + 134774) + df.maturity = df.maturity.values.view("M8[D]").astype(int) + 134774 return fee_legs, contingent_legs, df + def index_pv(fl, cl, value_date, step_in_date, cash_settle_date, yc, sc, recovery): dl_pv = cl.pv(value_date, step_in_date, cash_settle_date, yc, sc, recovery) cl_pv = fl.pv(value_date, step_in_date, cash_settle_date, yc, sc, True) return dl_pv - cl_pv + if __name__ == "__main__": conn = serenitas_engine.raw_connection() for index in ["IG", "HY", "EU", "XO"]: @@ -55,8 +65,7 @@ if __name__ == "__main__": for series in range(18, 33): if index in ["EU", "XO"] and series == 32: continue - fee_legs, contingent_legs, df = \ - get_legs(index, series, tenors[index]) + fee_legs, contingent_legs, df = get_legs(index, series, tenors[index]) index_quotes = pd.read_sql_query( "SELECT distinct on (date, tenor) id, date, tenor, version, close_price " @@ -67,42 +76,60 @@ if __name__ == "__main__": "ORDER BY date, tenor, version desc", serenitas_engine, params=(index, series, tenors[index]), - parse_dates=['date'], - index_col='id') + parse_dates=["date"], + index_col="id", + ) if index_quotes.empty: continue index_quotes.tenor = index_quotes.tenor.astype(tenor_t) - index_quotes = index_quotes.sort_values('tenor') - index_quotes['close_price'] = 1. - index_quotes['close_price'] / 100 + index_quotes = index_quotes.sort_values("tenor") + index_quotes["close_price"] = 1.0 - index_quotes["close_price"] / 100 with conn.cursor() as c: - for value_date, data in index_quotes.groupby('date'): - yc = get_curve(value_date, "USD" if index in ["IG", "HY"] else "EUR") + for value_date, data in index_quotes.groupby("date"): + yc = get_curve( + value_date, "USD" if index in ["IG", "HY"] else "EUR" + ) # right_index?? is it a bug? - data = data.merge(df, on='tenor', right_index=True) + data = data.merge(df, on="tenor", right_index=True) step_in_date = value_date + datetime.timedelta(days=1) cash_settle_date = value_date + 3 * BDay() start_date = previous_twentieth(value_date) - sc = SpreadCurve(value_date, yc, start_date, - step_in_date, cash_settle_date, - data.maturity.values, data.coupon.values, - data.close_price.values, - recoveries) - for r in data[['coupon', 'tenor', 'close_price']].itertuples(): + sc = SpreadCurve( + value_date, + yc, + start_date, + step_in_date, + cash_settle_date, + data.maturity.values, + data.coupon.values, + data.close_price.values, + recoveries, + ) + for r in data[["coupon", "tenor", "close_price"]].itertuples(): fl, fl_short = fee_legs[r.tenor] cl, cl_short = contingent_legs[r.tenor] - duration = fl.pv(value_date, step_in_date, - cash_settle_date, yc, sc, - True) + duration = fl.pv( + value_date, step_in_date, cash_settle_date, yc, sc, True + ) if cl_short.end_date <= value_date.date(): theta = None else: - pv = index_pv(fl_short, cl_short, - value_date, step_in_date, cash_settle_date, yc, sc, - recoveries[0]) + pv = index_pv( + fl_short, + cl_short, + value_date, + step_in_date, + cash_settle_date, + yc, + sc, + recoveries[0], + ) theta = r.close_price - pv + r.coupon - c.execute("INSERT INTO index_risk VALUES(%s, %s, %s)", - (r.Index, theta, duration)) + c.execute( + "INSERT INTO index_risk VALUES(%s, %s, %s)", + (r.Index, theta, duration), + ) conn.commit() conn.close() |