blob: 45db50965b4d2dca1271cbad02382aac478468c4 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
|
from analytics import ATMstrike
import pandas as pd
def run_swaption_scenarios(swaption, date_range, spread_shock, vol_shock, vol_surface):
"""computes the pv of a swaption for a range of scenarios
Parameters
----------
swaption : Swaption
date_range : `pandas.Datetime.Index`
spread_shock : `np.array`
vol_shock : `np.array`
vol_surface
"""
r = []
spread_start = swaption.index.spread
for date in date_range:
swaption.index.trade_date = date.date()
T = swaption.T
for ss in spread_shock:
spread = spread_start * (1 + ss)
swaption.index.ref = spread
swaption._update()
atm_strike = ATMstrike(swaption.index, swaption.exercise_date)
moneyness = (swaption.index.spread / atm_strike)
curr_vol = float(vol_surface.ev(T, moneyness))
for vs in vol_shock:
vol = curr_vol * (1 + vs)
swaption.sigma = vol
r.append([date, ss, vs, swaption.pv_black])
swaption.index.spread = spread_start
df = pd.DataFrame.from_records(r, columns=['date', 'spread_shock',
'vol_shock', 'pv'])
return df.set_index('date')
|
