diff options
| -rw-r--r-- | python/calibrate_swaption.py | 8 | ||||
| -rw-r--r-- | python/exploration/option_trades.py | 2 |
2 files changed, 6 insertions, 4 deletions
diff --git a/python/calibrate_swaption.py b/python/calibrate_swaption.py index 087b9c3b..40e6ccd4 100644 --- a/python/calibrate_swaption.py +++ b/python/calibrate_swaption.py @@ -1,5 +1,4 @@ import pandas as pd -import argparse from analytics import Index, Swaption import datetime from db import dbengine @@ -91,12 +90,13 @@ def calibrate(index_type=None, series=None, date=None, nproc=4, latest=False): serenitas_engine.execute(sql_str, to_insert) if __name__ == "__main__": + import argparse parser = argparse.ArgumentParser() parser.add_argument('--index', required=False, type=lambda s: s.upper(), dest="index_type") parser.add_argument('--series', required=False, type=int, default=28) - parser.add_argument('--date', required = False, default=datetime.date.min) - parser.add_argument('--latest', required = False, action="store_true") - parser.add_argument('--nproc', required = False, type=int, default=4) + parser.add_argument('--date', required=False, default=datetime.date.min) + parser.add_argument('--latest', required=False, action="store_true") + parser.add_argument('--nproc', required=False, type=int, default=4) args = parser.parse_args() if args.latest: calibrate(latest=True, nproc=args.nproc) diff --git a/python/exploration/option_trades.py b/python/exploration/option_trades.py index ab61a520..8562549d 100644 --- a/python/exploration/option_trades.py +++ b/python/exploration/option_trades.py @@ -83,10 +83,12 @@ def atm_vol(index, date, series=None, moneyness=0.2): df = pd.read_sql_query(sql_str, serenitasdb, index_col=['quotedate', 'expiry', 'series'], params=params, parse_dates=['quotedate']) + df = df.groupby(df.index).filter(lambda x: len(x)>2) return atm_vol_calc(df, index, moneyness) def rolling_vol(df, col='atm_vol', term=[3]): """compute the rolling volatility for various terms""" + df = df.reset_index(level=['expiry', 'series']) df = df.groupby(df.index).filter(lambda x: len(x)>2) def aux(s, col, term): k = s.index[0] |