diff options
Diffstat (limited to 'python/analytics')
| -rw-r--r-- | python/analytics/index.py | 17 | ||||
| -rw-r--r-- | python/analytics/option.py | 16 |
2 files changed, 17 insertions, 16 deletions
diff --git a/python/analytics/index.py b/python/analytics/index.py index 0da98e47..a1ec4bb8 100644 --- a/python/analytics/index.py +++ b/python/analytics/index.py @@ -15,9 +15,24 @@ from pyisda.curve import SpreadCurve from .utils import previous_twentieth from yieldcurve import YC, ql_to_jp, roll_yc, rate_helpers - serenitasdb = dbconn('serenitasdb') +def g(index, spread : float, exercise_date : datetime.date, use_rolled_curve = True): + """ computes the strike clean price using the expected forward yield curve """ + if use_rolled_curve: + rolled_curve = roll_yc(index._yc, exercise_date) + else: + rolled_curve = index._yc + step_in_date = exercise_date + datetime.timedelta(days=1) + exercise_date_settle = (pd.Timestamp(exercise_date) + 3* BDay()).date() + sc = SpreadCurve(exercise_date, rolled_curve, index.start_date, + step_in_date, exercise_date_settle, + [index.end_date], array.array('d', [spread * 1e-4]), + index.recovery) + a = index._fee_leg.pv(exercise_date, step_in_date, exercise_date_settle, + rolled_curve, sc, True) + return (spread - index.fixed_rate) * a *1e-4 + class Index(): """ minimal class to represent a credit index """ def __init__(self, start_date, end_date, recovery, fixed_rate, diff --git a/python/analytics/option.py b/python/analytics/option.py index 02598665..de59ea2b 100644 --- a/python/analytics/option.py +++ b/python/analytics/option.py @@ -6,6 +6,7 @@ import pandas as pd from .black import black from .utils import GHquad +from .index import g from yieldcurve import roll_yc from pandas.tseries.offsets import BDay from pyisda.curve import SpreadCurve @@ -13,21 +14,6 @@ from pyisda.flat_hazard import strike_vec from scipy.optimize import brentq from scipy.integrate import simps -def g(index, spread : float, exercise_date : datetime.date, use_rolled_curve = True): - """ computes the strike clean price using the expected forward yield curve """ - if use_rolled_curve: - rolled_curve = roll_yc(index._yc, exercise_date) - else: - rolled_curve = index._yc - step_in_date = exercise_date + datetime.timedelta(days=1) - exercise_date_settle = (pd.Timestamp(exercise_date) + 3* BDay()).date() - sc = SpreadCurve(exercise_date, rolled_curve, index.start_date, - step_in_date, exercise_date_settle, - [index.end_date], array.array('d', [spread * 1e-4]), - index.recovery) - a = index._fee_leg.pv(exercise_date, step_in_date, exercise_date_settle, - rolled_curve, sc, True) - return (spread - index.fixed_rate) * a *1e-4 def calib(S0, fp, exercise_date : datetime.date, exercise_date_settle :datetime.date, index, rolled_curve, tilt, w): |