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import pandas as pd
import argparse
from analytics import Index, Swaption
from db import dbconn
from joblib import Parallel, delayed
from pickle import loads, dumps
serenitasdb = dbconn('serenitasdb')
def get_data(index, series):
return pd.read_sql("SELECT * from swaption_ref_quotes JOIN swaption_quotes " \
"USING (quotedate, index, series, expiry) WHERE index=%s and series=%s " \
"ORDER BY quotedate",
"postgresql://serenitas_user@debian/serenitasdb",
params = (index, series), parse_dates = ['quotedate', 'expiry'])
def calib(d, option, expiry, index, series):
option.strike = d['strike']
option.ref = d['ref']
r = []
for pv_type in ['pv', 'pv_black']:
for option_type in ['pay', 'rec']:
mid = (d['{}_bid'.format(option_type)] + d['{}_offer'.format(option_type)])/2 * 1e-4
option.option_type = 'payer' if option_type == 'pay' else 'receiver'
try:
setattr(option, pv_type, mid)
except ValueError as e:
r.append(None)
print(e)
else:
r.append(option.sigma)
return [d['quotedate'], index, series, expiry, d['strike']] + r
def calibrate(index_type, series):
sql_str = ("INSERT INTO swaption_calib VALUES({}) ON CONFLICT DO NOTHING".
format(",".join(["%s"] * 9)))
data = get_data(index_type, series)
index = Index.from_name(index_type, series, "5yr")
for k, v in data.groupby([data['quotedate'].dt.date, 'expiry']):
trade_date, expiry = k
index.trade_date = trade_date
option = Swaption(index, expiry.date(), 100,
strike_is_price = index_type == "HY")
r = Parallel(n_jobs=4)(
delayed(calib)(d, option, expiry.date(), index_type, series) for d in
v[['ref', 'quotedate', 'strike', 'pay_bid', 'pay_offer', 'rec_bid', 'rec_offer']].
to_dict(orient = 'records'))
with serenitasdb.cursor() as c:
c.executemany(sql_str, r)
serenitasdb.commit()
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--index', required=True, type = lambda s: s.upper())
parser.add_argument('--series', required=True, type=int)
args = parser.parse_args()
calibrate(args.index, args.series)
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