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from serenitas.analytics.bbg_helpers import init_bbg_session, retrieve_data, BBG_IP
import datetime
import numpy as np
import pandas as pd
from pandas import bdate_range
import re
import os
import logging
def get_list(
engine,
workdate: datetime.date = None,
asset_class=None,
include_unsettled: bool = True,
fund="SERCGMAST",
):
if workdate:
positions = pd.read_sql_query(
"SELECT identifier, bbg_type FROM " "list_positions(%s, %s, %s, %s)",
engine,
params=(workdate, asset_class, include_unsettled, fund),
)
positions.loc[
positions.identifier.str.len() <= 11, "cusip"
] = positions.identifier.str.slice(stop=9)
positions.loc[
positions.identifier.str.len() == 12, "isin"
] = positions.identifier
else:
positions = pd.read_sql_table("securities", engine)
positions["bbg_id"] = (
positions.cusip.where(positions.cusip.notnull(), positions["isin"])
+ " "
+ positions.bbg_type
)
positions.set_index("bbg_id", inplace=True)
return positions
def get_list_range(engine, begin, end, asset_class=None):
begin = pd.Timestamp(begin).date()
end = pd.Timestamp(end).date()
positions = pd.read_sql_query(
"select identifier, bbg_type, strategy from list_positions_range(%s, %s, %s)",
engine,
params=(begin, end, asset_class),
)
positions.loc[
positions.identifier.str.len() <= 11, "cusip"
] = positions.identifier.str.slice(stop=9)
positions.loc[positions.identifier.str.len() == 12, "isin"] = positions.identifier
positions["bbg_id"] = (
positions.cusip.where(positions.cusip.notnull(), positions["isin"])
+ " "
+ positions.bbg_type
)
positions.set_index("bbg_id", inplace=True)
return positions
def backpopulate_marks(begin_str="2015-01-15", end_str="2015-07-15"):
pattern = re.compile("\d{4}-\d{2}-\d{2}")
list_of_daily_folder = (
fullpath
for (fullpath, _, _) in os.walk("/home/serenitas/Daily")
if pattern.match(os.path.basename(fullpath))
)
list_of_bdays = bdate_range(start=begin_str, end=end_str)
for path in list_of_daily_folder:
date = pd.to_datetime(os.path.basename(path))
if date in list_of_bdays:
marks_file = [f for f in os.listdir(path) if f.startswith("securitiesNpv")]
if marks_file:
marks_file.sort(
key=lambda x: x[13:], reverse=True
) # sort by lexicographic order which is what we want since we use ISO dates
marks = pd.read_csv(os.path.join(path, marks_file[0]))
positions = get_list(pd.to_datetime(date))
positions = positions.merge(
marks, left_on="identifier", right_on="IDENTIFIER"
)
positions.drop(["IDENTIFIER", "last_settle_date"], axis=1, inplace=True)
positions["date"] = date
positions.rename(columns={"Price": "price"}, inplace=True)
positions = positions.drop_duplicates()
positions.to_sql("position", engine, if_exists="append", index=False)
def update_securities(engine, session, workdate):
field = {"Corp": "PREV_CPN_DT", "Mtge": "START_ACC_DT"}
securities = get_list(engine)
securities = securities[securities.paid_down.isnull()]
data = retrieve_data(
session,
securities.index.tolist(),
["PREV_CPN_DT", "START_ACC_DT", "CUR_CPN", "CPN_ASOF_DT"],
)
data = pd.DataFrame.from_dict(data, orient="index")
data = data[
data.CPN_ASOF_DT.isnull() | (data.CPN_ASOF_DT <= pd.Timestamp(workdate))
]
m = securities.merge(data, left_index=True, right_index=True)
conn = engine.raw_connection()
with conn.cursor() as c:
for r in m.to_dict("records"):
accrued_field = field[r["bbg_type"]]
if r[accrued_field] < workdate:
c.execute(
f"UPDATE securities SET start_accrued_date=%({accrued_field})s "
",coupon=%(CUR_CPN)s WHERE identifier=%(identifier)s",
r,
)
conn.commit()
conn.close()
def init_fx(session, engine, startdate):
currencies = ["EURUSD", "CADUSD"]
securities = [c + " Curncy" for c in currencies]
data = retrieve_data(session, securities, ["PX_LAST"], start_date=startdate)
data = data["EURUSD Curncy"].merge(
data["CADUSD Curncy"], left_on="date", right_on="date"
)
data.rename(columns={"PX_LAST_x": "eurusd", "PX_LAST_y": "cadusd"}, inplace=True)
data.to_sql("fx", engine, if_exists="append")
def update_fx(conn, session, currencies):
securities = [c + " Curncy" for c in currencies]
data = retrieve_data(session, securities, ["FIXED_CLOSING_PRICE_NY", "PX_CLOSE_DT"])
colnames = ["date"]
values = []
for k, v in data.items():
currency_pair = k.split(" ")[0].lower()
colnames.append(currency_pair)
values.append(v["FIXED_CLOSING_PRICE_NY"])
values = [v["PX_CLOSE_DT"]] + values
sqlstr = "INSERT INTO fx({0}) VALUES({1}) ON CONFLICT DO NOTHING".format(
",".join(colnames), ",".join(["%s"] * len(values))
)
with conn.cursor() as c:
c.execute(sqlstr, values)
conn.commit()
def init_swap_rates(
conn,
session,
tenors=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30],
start_date=datetime.date(1998, 10, 7),
):
securities = [f"USISDA{t:02} Index" for t in tenors]
data = retrieve_data(
session, securities, ["PX_LAST"], start_date=datetime.date(1998, 10, 7)
)
for t in tenors:
ticker = f"USISDA{t:02} Index"
sql_str = (
f'INSERT INTO USD_swap_fixings(fixing_date, "{t}y") '
+ "VALUES(%s, %s) ON CONFLICT (fixing_date)"
+ f' DO UPDATE SET "{t}y" = excluded."{t}y"'
)
with conn.cursor() as c:
c.executemany(sql_str, [(d, r) for d, r in data[ticker]["PX_LAST"].items()])
conn.commit()
def init_swaption_vol(
session,
tenors=["A", "C", "F", "I"] + list(range(1, 11)) + [15, 20, 25, 30],
source="BBIR",
vol_type="N",
start_date=datetime.date(1990, 1, 1),
):
tickers = []
for t1 in tenors:
for t2 in tenors[4:]:
tickers.append(f"USS{vol_type}{t1:0>2}{t2} {source} Curncy")
data = retrieve_data(session, tickers, ["PX_LAST"], start_date=start_date)
return data
def split_tenor_expiry(ticker, vol_type="N"):
m = re.match(f"USS{vol_type}(.{{2}})([^\s]*) ([^\s]*) Curncy", ticker)
expiry, tenor, _ = m.groups()
if expiry[0] == "0":
expiry = expiry[1:]
if not expiry.isalpha():
expiry = int(expiry)
tenor = int(tenor)
return expiry, tenor
def insert_swaption_vol(data, conn, source, vol_type="N"):
tenors = ["A", "C", "F", "I"] + list(range(1, 11)) + [15, 20, 25, 30]
df = pd.concat(data, axis=1)
df.columns = df.columns.get_level_values(0)
df.columns = pd.MultiIndex.from_tuples(
[split_tenor_expiry(c, vol_type) for c in df.columns]
)
table_name = "swaption_normal_vol" if vol_type == "N" else "swaption_lognormal_vol"
for t in tenors[-14:]:
sql_str = (
f'INSERT INTO {table_name}(date, "{t}y", source) '
+ "VALUES(%s, %s, %s) ON CONFLICT (date, source)"
+ f' DO UPDATE SET "{t}y" = excluded."{t}y", source = excluded.source'
)
with conn.cursor() as c:
df_temp = df.xs(t, axis=1, level=1).reindex(tenors, axis=1)
for k, v in df_temp.iterrows():
if np.all(np.isnan(v.values)):
continue
c.execute(sql_str, (k, v.tolist(), source))
conn.commit()
def update_swaption_vol(
conn,
session,
tenors=["A", "C", "F", "I"] + list(range(1, 11)) + [15, 20, 25, 30],
*,
sources=["BBIR", "CMPN", "ICPL"],
vol_type="N",
):
"""
Parameters
----------
vol_type : one of 'N' or 'V' (normal or log-normal)
"""
table_name = "swaption_normal_vol" if vol_type == "N" else "swaption_lognormal_vol"
for source in ["BBIR", "CMPN", "ICPL"]:
tickers = []
for expiry in tenors:
for tenor in tenors:
tickers.append(f"USS{vol_type}{expiry:0>2}{tenor} {source} Curncy")
data = retrieve_data(session, tickers, ["PX_YEST_CLOSE", "PX_CLOSE_DT"])
for t in tenors[4:]:
sql_str = (
f'INSERT INTO {table_name}(date, "{t}y", source) '
+ "VALUES(%s, %s, %s) ON CONFLICT (date, source)"
+ f' DO UPDATE SET "{t}y" = excluded."{t}y", source = excluded.source'
)
r = []
dates = []
for expiry in tenors:
ticker = f"USS{vol_type}{expiry:0>2}{t} {source} Curncy"
if data[ticker]:
r.append(data[ticker]["PX_YEST_CLOSE"])
dates.append(data[ticker]["PX_CLOSE_DT"])
else:
r.append(None)
dates.append(dates[-1])
if dates.count(dates[0]) < len(dates):
raise ValueError("Not all quotes are from the same date")
with conn.cursor() as c:
c.execute(sql_str, (dates[0], r, source))
conn.commit()
def update_swap_rates(
conn, session, tenors=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30]
):
securities = [f"USISDA{t:02} Index" for t in tenors]
data = retrieve_data(session, securities, ["PX_LAST", "LAST_UPDATE_DT"])
for t in tenors:
ticker = f"USISDA{t:02} Index"
sql_str = (
f'INSERT INTO USD_swap_fixings(fixing_date, "{t}y") '
+ "VALUES(%(LAST_UPDATE_DT)s, %(PX_LAST)s) ON CONFLICT (fixing_date)"
+ f' DO UPDATE SET "{t}y" = %(PX_LAST)s'
)
with conn.cursor() as c:
c.execute(sql_str, data[ticker])
conn.commit()
def update_cash_rates(conn, session, start_date=None):
securities = {
"FEDL01 Index": "FED_FUND",
"US0001M Index": "1M_LIBOR",
"US0003M Index": "3M_LIBOR",
}
if start_date is None:
data = retrieve_data(
session, list(securities.keys()), ["PX_LAST", "LAST_UPDATE_DT"]
)
else:
data = retrieve_data(
session, list(securities.keys()), ["PX_LAST"], start_date=start_date.date()
)
sql_str = "INSERT INTO rates VALUES(%s, %s, %s) ON CONFLICT DO NOTHING"
with conn.cursor() as c:
if start_date is None:
for k, v in data.items():
c.execute(sql_str, (v["LAST_UPDATE_DT"], securities[k], v["PX_LAST"]))
else:
for k, v in data.items():
for d, r in v["PX_LAST"].items():
c.execute(sql_str, (d, securities[k], r))
conn.commit()
def populate_cashflow_history(engine, session, workdate=None, fund="SERCGMAST"):
securities = get_list(engine, workdate, fund=fund)
data = retrieve_data(
session,
securities.index.tolist(),
["HIST_CASH_FLOW", "MTG_HIST_CPN", "FLT_CPN_HIST", "HIST_INTEREST_DISTRIBUTED"],
)
fixed_coupons = {"XS0306416982 Mtge": 7.62, "91927RAD1 Mtge": 6.77}
conn = engine.raw_connection()
for k, v in data.items():
identifier = securities.loc[k, "identifier"]
if "HIST_CASH_FLOW" in v:
to_insert = v["HIST_CASH_FLOW"].merge(
v["MTG_HIST_CPN"],
how="left",
left_on="Payment Date",
right_on="Payment Date",
)
to_insert.rename(
columns={
"Coupon_y": "coupon",
"Interest": "interest",
"Payment Date": "date",
"Principal Balance": "principal_bal",
"Principal Paid": "principal",
},
inplace=True,
)
to_insert.drop(["Period Number", "Coupon_x"], axis=1, inplace=True)
elif "FLT_CPN_HIST" in v:
to_insert = v["FLT_CPN_HIST"]
to_insert.rename(
columns={"Coupon Rate": "coupon", "Accrual Start Date": "date"},
inplace=True,
)
to_insert.coupon = to_insert.coupon.shift(1)
elif "HIST_INTEREST_DISTRIBUTED" in v:
to_insert = v["HIST_INTEREST_DISTRIBUTED"]
to_insert.rename(
columns={"Interest": "interest", "Historical Date": "date"},
inplace=True,
)
if k in fixed_coupons:
to_insert["coupon"] = fixed_coupons[k]
else: # damn you XS0299146992 !
continue
else:
logging.error(f"No cashflows for security {identifier}")
continue
to_insert["identifier"] = identifier
with conn.cursor() as c:
c.execute("DELETE FROM cashflow_history WHERE identifier=%s", (identifier,))
conn.commit()
to_insert.to_sql("cashflow_history", engine, if_exists="append", index=False)
with conn.cursor() as c:
c.execute("REFRESH MATERIALIZED VIEW CONCURRENTLY factors_history")
conn.commit()
conn.close()
if __name__ == "__main__":
from serenitas.utils.db import serenitas_pool, dawn_engine
import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
"workdate",
nargs="?",
type=datetime.date.fromisoformat,
default=datetime.date.today(),
)
args = parser.parse_args()
dawn_conn = dawn_engine.raw_connection()
serenitas_conn = serenitas_pool.getconn()
with init_bbg_session(BBG_IP) as session:
update_securities(dawn_engine, session, args.workdate)
for fund in ("SERCGMAST", "BRINKER", "BOWDST"):
populate_cashflow_history(dawn_engine, session, args.workdate, fund)
update_fx(dawn_conn, session, ["EURUSD", "CADUSD"])
update_swap_rates(serenitas_conn, session)
update_cash_rates(serenitas_conn, session)
for vol_type in ["N", "V"]:
update_swaption_vol(serenitas_conn, session, vol_type=vol_type)
serenitas_pool.putconn(serenitas_conn)
# with init_bbg_session(BBG_IP) as session:
# init_fx(session, engine, pd.datetime(2013, 1, 1))
# with init_bbg_session(BBG_IP) as session:
# init_swap_rates(serenitas_conn, session, start_date=pd.datetime(2012, 2, 2))
# for source in ['BBIR', 'ICPL', 'CMPN']:
# for vol_type in ["N", "V"]:
# with init_bbg_session(BBG_IP) as session:
# data = init_swaption_vol(session, source=source,
# vol_type=vol_type,
# start_date=datetime.date(2001, 1, 1))
# insert_swaption_vol(data, serenitas_conn, source,
# vol_type=vol_type)
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