diff options
Diffstat (limited to 'python/exploration')
| -rw-r--r-- | python/exploration/swaption_calendar_spread.py | 29 |
1 files changed, 15 insertions, 14 deletions
diff --git a/python/exploration/swaption_calendar_spread.py b/python/exploration/swaption_calendar_spread.py index d26ad0ee..51a22d42 100644 --- a/python/exploration/swaption_calendar_spread.py +++ b/python/exploration/swaption_calendar_spread.py @@ -147,7 +147,8 @@ def plot_trade_scenarios(portf, shock_min=-.15, shock_max=.2): 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 = max(portf.swaptions,key=attrgetter('exercise_date')).exercise_date + 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] @@ -164,7 +165,7 @@ def plot_trade_scenarios(portf, shock_min=-.15, shock_max=.2): shock = hy_plot_range if index == 'HY' else portf.indices[0].spread * (1 + spread_shock) - period = -4 + period = -1 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)==0], shock, 'delta', color_map = cm.coolwarm_r, index=index) plot_color_map(df.loc[date_range[period]], shock, vol_shock, 'pnl', index=index) @@ -172,7 +173,7 @@ def plot_trade_scenarios(portf, shock_min=-.15, shock_max=.2): def exercise_probability(): - from analytics import Swaption, BlackSwaption, Index, VolatilitySurface, Portfolio + 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 @@ -204,21 +205,19 @@ def exercise_probability(): #import swaption_calendar_spread as spread #Ad hoc - option_delta = Index.from_name('HY', 28, '5yr') - option_delta.price = 107.625 - option1 = BlackSwaption(option_delta, datetime.date(2017, 9, 20), 107, option_type="payer") - option2 = BlackSwaption(option_delta, datetime.date(2017, 9, 20), 105, option_type="payer") - option1.sigma = .270 - option2.sigma = .3625 + option_delta = Index.from_name('HY', 29, '5yr') + option_delta.price = 107.875 + option1 = BlackSwaption(option_delta, datetime.date(2017, 12, 20), 107, option_type="payer") + option2 = BlackSwaption(option_delta, datetime.date(2017, 12, 20), 105, option_type="payer") + option1.sigma = .280 + option2.sigma = .371 option1.notional = 20_000_000 option2.notional = 40_000_000 option1.direction = 'Long' option2.direction = 'Short' - option_delta.notional = -2000000 - #option_delta.notional = option_delta.notional - option_delta2.notional - if option_delta.notional < 0: - option_delta.direction = 'Seller' - option_delta.notional = abs(option_delta.notional) + option_delta.notional = option1.notional * option1.delta + option2.notional * option2.delta + option_delta.direction = 'Seller' if option_delta.notional > 0 else 'Buyer' + option_delta.notional = abs(option_delta.notional) portf = Portfolio([option1, option2, option_delta]) portf.reset_pv() @@ -229,6 +228,8 @@ def exercise_probability(): 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] |