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from db import dbconn
from exchangelib import Credentials, Mailbox, Configuration, Account, DELEGATE
from pytz import timezone
import datetime
import json
import os
import pandas as pd
import re
def get_msgs(email_address='ghorel@lmcg.com', count=None):
with open(os.path.join('.credentials', email_address + '.json')) as fh:
creds = json.load(fh)
credentials = Credentials(**creds)
config = Configuration(server='autodiscover.lmcg.com', credentials=credentials)
account = Account(primary_smtp_address=email_address, config=config,
autodiscover=False, access_type=DELEGATE)
folder = account.root.get_folder_by_name('GS').get_folder_by_name('Swaptions')
if count:
for msg in folder.all().order_by('-datetime_sent')[:count]:
yield msg
else:
for msg in folder.all().order_by('-datetime_sent'):
yield msg
def parse_email(email, fwd_index):
m = re.search("(IG|HY)(\d{2}) 5y (?:.*)SWAPTION (?:UPDATE|CLOSES|CLOSE) - Ref\D+(.+)$",
email.subject)
if m:
indextype, series, ref = m.groups()
series = int(series)
if indextype == 'HY':
refprice, refspread = map(float,
re.match("([\S]+)\s+\(([^)]+)\)", ref).groups())
else:
refspread = float(ref)
quotedate = datetime.datetime.fromtimestamp(email.datetime_sent.timestamp(),
timezone('America/New_York'))
flag = False
masterdf = {}
for line in email.body.split("\r\n"):
if line.startswith("Expiry"):
m = re.match("Expiry (\d{2}\w{3}\d{2}) \((?:([\S]+) )?([\S]+)\)", line)
if m:
date, fwprice, fwspread = m.groups()
date = pd.to_datetime(date, format='%d%b%y')
continue
if line.startswith("Stk"):
flag = True
r = []
continue
if flag:
if line:
vals = re.sub(" +", " ", line).split(" ")
if indextype == 'HY':
vals.pop(2)
vals.pop(9)
else:
vals.pop(1)
vals.pop(8)
r.append(vals)
continue
else:
if indextype=='HY':
cols = ['Strike', 'Sprd', 'Pay', 'DeltaPay', 'Rec', 'Vol',
'VolChg', 'VolBpd', 'Tail']
else:
cols = ['Strike', 'Pay', 'DeltaPay', 'Rec', 'Vol',
'VolChg', 'VolBpd', 'Tail']
df = pd.DataFrame.from_records(r, columns = cols)
df[['PayBid', 'PayOffer']] = df.Pay.str.split('/', expand=True)
df[['RecBid', 'RecOffer']] = df.Rec.str.split('/', expand=True)
df.drop(['Pay', 'Rec'], axis=1, inplace=True)
for col in df:
df[col] = pd.to_numeric(df[col], errors = 'coerce')
df.set_index('Strike', inplace=True)
d = {'quotedate': quotedate,
'expiry': date,
'index': indextype,
'series': series,
'ref': refspread if indextype =="IG" else refprice}
if indextype == "IG":
d['fwdspread'] = float(fwspread)
else:
d['fwdprice'] = float(fwprice)
fwd_index.append(d)
masterdf[date] = df
flag = False
r = []
continue
return (quotedate, indextype, series, pd.concat(masterdf, names=['expiry']))
def clean_df(all_df):
all_df = pd.concat(all_df, names=['quotedate', 'index', 'series'])
all_df['DeltaPay'] = - all_df['DeltaPay']/100
all_df['Vol'] /= 100
all_df.reset_index(inplace=True)
all_df = all_df.rename(columns={'Strike':'strike',
'Vol': 'vol',
'PayOffer': 'pay_offer',
'PayBid': 'pay_bid',
'RecOffer': 'rec_offer',
'RecBid': 'rec_bid',
'Tail': 'tail',
'DeltaPay': 'delta_pay'})
del all_df['VolBpd'], all_df['VolChg']
if 'Sprd' in all_df:
del all_df['Sprd']
all_df['quote_source'] = 'GS'
return all_df
def insert_data(swaption_quotes, index_df):
conn = dbconn('serenitasdb')
format_str = "INSERT INTO swaption_ref_quotes({}) VALUES({}) " \
"ON CONFLICT DO NOTHING"
sqlstr = format_str.format(",".join(index_df.columns),
",".join(["%s"] * len(index_df.columns)))
with conn.cursor() as c:
c.executemany(sqlstr, index_df.itertuples(index=False))
conn.commit()
format_str = "INSERT INTO swaption_quotes({}) VALUES({}) " \
"ON CONFLICT DO NOTHING"
sqlstr = format_str.format(",".join(swaption_quotes.columns),
",".join(["%s"] * len(swaption_quotes.columns)))
with conn.cursor() as c:
c.executemany(sqlstr, swaption_quotes.itertuples(index=False))
conn.commit()
conn.close()
if __name__=="__main__":
fwd_index = []
swaption_quotes = {}
for email in get_msgs(count=20):
quotedate, indextype, series, df = parse_email(email, fwd_index)
swaption_quotes[(quotedate, indextype, series)] = df
swaption_quotes = clean_df(swaption_quotes)
index_df = pd.DataFrame(fwd_index)
index_df = index_df.drop_duplicates(['quotedate', 'index', 'series', 'expiry'])
insert_data(swaption_quotes, index_df)
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