diff options
Diffstat (limited to 'python/exploration/swaption_calendar_spread.py')
| -rw-r--r-- | python/exploration/swaption_calendar_spread.py | 38 |
1 files changed, 11 insertions, 27 deletions
diff --git a/python/exploration/swaption_calendar_spread.py b/python/exploration/swaption_calendar_spread.py index f6d73848..f8df96ce 100644 --- a/python/exploration/swaption_calendar_spread.py +++ b/python/exploration/swaption_calendar_spread.py @@ -148,7 +148,7 @@ def dec_jan_2017_trade(): 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_select = max([t for t in vs.list() if t[1] == 'BAML' and t[2] == 'payer' and t[3] == 'black']) + vol_select = vs.list('BAML', 'payer', 'black')[-1] vol_surface = vs[vol_select] df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface, params=["pnl", "delta"], vol_time_roll=False) @@ -165,27 +165,11 @@ def april_may_2017_trade(): 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_select = max([t for t in vs.list() if t[1] == 'BAML' and t[2] == 'payer' and t[3] == 'black']) + vol_select = vs.list('BAML', 'payer', 'black')[-1] vol_surface = vs[vol_select] - df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface, params=["pnl", "delta"], vol_time_roll=False) - plot_time_color_map(df[round(df.vol_shock,2)==0], option_delta.spread * (1 + spread_shock), 'pnl') - - -def april_may_2017_trade(): - option_delta = Index.from_tradeid(870) - option1 = BlackSwaption.from_tradeid(5, option_delta) - 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') - BDay(), freq = '2B') - 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_select = max([t for t in vs.list() if t[1] == 'BAML' and t[2] == 'payer' and t[3] == 'black']) - vol_surface = vs[vol_select] - - df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface, params=["pnl", "delta"], vol_time_roll=False) + df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, + vol_surface, params=["pnl", "delta"], vol_time_roll=False) plot_time_color_map(df[round(df.vol_shock,2)==0], option_delta.spread * (1 + spread_shock), 'pnl') @@ -196,10 +180,10 @@ def june_july_2017_trade(): option1_pf = BlackSwaption.from_tradeid(7, option_delta_pf) option2_pf = BlackSwaption.from_tradeid(9, option_delta_pf) #option_delta.notional = option_delta.notional - option_delta2.notional - option_delta_pf.notional = 50335169 + option_delta_pf.notional = 50_335_169 portf = Portfolio([option1_pf, option2_pf, option_delta_pf]) - portf.trade_date = datetime.date(2017,5,17) + portf.trade_date = datetime.date(2017, 5, 17) portf.mark() portf.reset_pv() @@ -207,10 +191,11 @@ def june_july_2017_trade(): 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=option_delta_pf.trade_date) - vol_select = max([t for t in vs.list() if t[1] == 'BAML' and t[2] == 'payer' and t[3] == 'black']) + vol_select = vs.list('BAML', 'payer', 'black')[-1] vol_surface = vs[vol_select] - df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface, params=["pnl", "delta"], vol_time_roll=True) + df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface, + params=["pnl", "delta"], vol_time_roll=True) #period = -4 #plot_df(df.loc[date_range[period]], spread_plot_range, vol_shock_range) @@ -242,7 +227,7 @@ def hy_trade_scenario(): vol_shock = np.arange(-0.15, 0.3, 0.01) spread_shock = np.arange(-0.1, 0.4, 0.01) vs = VolatilitySurface("HY", 28, trade_date=option_delta.trade_date) - vol_select = max([t for t in vs.list() if t[1] == 'BAML' and t[2] == 'payer' and t[3] == 'black']) + vol_select = vs.list('BAML', 'payer', 'black')[-1] vol_surface = vs[vol_select] df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface, params=["pnl", "delta"], vol_time_roll=True) @@ -268,7 +253,7 @@ def portfolio(): 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=option_delta.trade_date) - vol_select = max([t for t in vs.list() if t[1] == 'BAML' and t[2] == 'payer' and t[3] == 'black']) + vol_select = vs.list('BAML', 'payer', 'black')[-1] vol_surface = vs[vol_select] df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface, params=["pnl", "delta"], vol_time_roll=False) @@ -295,4 +280,3 @@ def probabilities(): curr_vols = np.maximum(vol_surface.ev(t, mon), 0) dist = lognorm(curr_vols, scale) lognorm.ppf(.5, curr_vols, scale = np.exp(64)) - |