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
35
36
37
38
39
40
41
42
43
44
45
46
47
48
|
import pandas as pd
from analytics import Index, Swaption
import pdb
from db import dbconn
from joblib import Parallel, delayed
from pickle import loads, dumps
serenitasdb = dbconn('serenitasdb')
data = 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 = ('IG', 27), parse_dates = ['quotedate', 'expiry'])
ig27 = Index.from_name("ig", 27, "5yr")
sigma = {}
sql_str = "INSERT INTO swaption_calib VALUES({}) ON CONFLICT DO NOTHING".format(",".join(["%s"] * 9))
def calib(d, option, expiry):
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:
r.append(None)
print(d['ref'], d['strike'], mid, option.intrinsic_value)
else:
r.append(option.sigma)
return [d['quotedate'], "IG", 27, expiry, d['strike']] + r
for k, v in data.groupby([data['quotedate'].dt.date, 'expiry']):
trade_date, expiry = k
print(trade_date, expiry.date())
ig27.trade_date = trade_date
option = Swaption(ig27, expiry.date(), 70)
r = Parallel(n_jobs=4)(delayed(calib)(d, option, expiry.date()) 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()
|
