diff options
Diffstat (limited to 'python/calibrate_swaption.py')
| -rw-r--r-- | python/calibrate_swaption.py | 31 |
1 files changed, 19 insertions, 12 deletions
diff --git a/python/calibrate_swaption.py b/python/calibrate_swaption.py index 63a44213..ce145224 100644 --- a/python/calibrate_swaption.py +++ b/python/calibrate_swaption.py @@ -1,39 +1,43 @@ import pandas as pd -from analytics import Index, Swaption +from analytics import CreditIndex, Swaption import datetime from db import dbengine from contextlib import contextmanager from itertools import starmap from functools import partial from multiprocessing import Pool -from itertools import repeat serenitas_engine = dbengine('serenitasdb') + def get_data(index, series, date=datetime.date.min): - df = pd.read_sql_query("SELECT * from swaption_ref_quotes JOIN swaption_quotes " \ - "USING (ref_id) WHERE index=%s and series=%s " \ + df = pd.read_sql_query("SELECT * from swaption_ref_quotes JOIN swaption_quotes " + "USING (ref_id) WHERE index=%s and series=%s " "and quotedate >=%s ORDER BY quotedate", serenitas_engine, - params=(index, series, date), parse_dates=['quotedate', 'expiry']) - df.loc[(df.quote_source == "GS") & (df['index'] =="HY"), + params=(index, series, date), + parse_dates=['quotedate', 'expiry']) + df.loc[(df.quote_source == "GS") & (df['index'] == "HY"), ["pay_bid", "pay_offer", "rec_bid", "rec_offer"]] *= 100 df.quotedate = df.quotedate.dt.tz_convert('America/New_York') return df + def get_data_latest(): - df = pd.read_sql_query("SELECT quotedate, index, series, expiry, ref, quote_source, " - "swaption_quotes.* FROM swaption_ref_quotes " \ - "JOIN swaption_quotes USING (ref_id) " \ - "LEFT JOIN swaption_calib USING (quote_id) " \ + df = pd.read_sql_query("SELECT quotedate, index, series, expiry, ref, " + "quote_source, swaption_quotes.* " + "FROM swaption_ref_quotes " + "JOIN swaption_quotes USING (ref_id) " + "LEFT JOIN swaption_calib USING (quote_id) " "WHERE swaption_calib.quote_id is NULL", serenitas_engine, parse_dates=['quotedate', 'expiry']) df.loc[(df.quote_source == "GS") & (df['index'] == "HY"), - ["pay_bid", "pay_offer", "rec_bid", "rec_offer"]] *=100 + ["pay_bid", "pay_offer", "rec_bid", "rec_offer"]] *= 100 df.quotedate = df.quotedate.dt.tz_convert('America/New_York') return df + def calib(option, ref, strike, pay_bid, pay_offer, rec_bid, rec_offer): option.ref = ref option.strike = strike @@ -55,10 +59,12 @@ def calib(option, ref, strike, pay_bid, pay_offer, rec_bid, rec_offer): r.append(option.sigma) return r + @contextmanager def MaybePool(nproc): yield Pool(nproc) if nproc > 1 else None + def calibrate(index_type=None, series=None, date=None, nproc=4, latest=False): sql_str = ("INSERT INTO swaption_calib VALUES({}) ON CONFLICT DO NOTHING". format(",".join(["%s"] * 5))) @@ -71,7 +77,7 @@ def calibrate(index_type=None, series=None, date=None, nproc=4, latest=False): pstarmap = pool.starmap if pool else starmap for k, v in data.groupby([data['quotedate'].dt.date, 'index', 'series']): trade_date, index_type, series = k - index = Index.from_name(index_type, series, "5yr", trade_date) + index = CreditIndex(index_type, series, "5yr", trade_date) for expiry, df in v.groupby(['expiry']): option = Swaption(index, expiry.date(), 100) mycalib = partial(calib, option) @@ -81,6 +87,7 @@ def calibrate(index_type=None, series=None, date=None, nproc=4, latest=False): to_insert = [[a] + b for a, b in zip(df.quote_id, r)] serenitas_engine.execute(sql_str, to_insert) + if __name__ == "__main__": import argparse parser = argparse.ArgumentParser() |