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from serenitas.analytics.tranche_basket import TrancheBasket, MarkitTrancheBasket
from serenitas.analytics.dates import prev_business_day
from psycopg import sql
import datetime
import logging
import numpy as np
import pandas as pd
from yaml import full_load
import argparse
def get_lastdate(conn, index, series, tenor):
sql_str = (
"SELECT (max(date) AT TIME ZONE 'America/New_York')::date + 1 "
"AS date FROM risk_numbers "
"WHERE index=%s and series = %s and tenor = %s"
)
with conn.cursor() as c:
c.execute(sql_str, (index, series, tenor))
(date,) = c.fetchone()
conn.commit()
return date
def build_sql_str(df, use_markit=False):
cols = ",".join(df.columns)
cols_ex_tranche_id = ",".join([c for c in df.columns if c != "tranche_id"])
cols_excluded = ",".join([f"excluded.{c}" for c in df.columns if c != "tranche_id"])
place_holders = ",".join([f"%({c})s" for c in df.columns])
sql_str = (
f"INSERT INTO {'markit_' if use_markit else ''}tranche_risk({cols}) "
f"VALUES ({place_holders}) ON CONFLICT (tranche_id) DO "
f"UPDATE SET ({cols_ex_tranche_id}) = ({cols_excluded})"
)
return sql_str
def build_sql(table, cols, conflict):
return sql.SQL(
"INSERT INTO {table}({cols}) VALUES ({ph}) "
"ON CONFLICT ({conflict}) DO "
"UPDATE SET ({new}) = ({excluded})"
).format(
table=sql.Identifier(table),
cols=sql.SQL(",").join([sql.Identifier(c) for c in cols]),
ph=sql.SQL(",").join(sql.Placeholder() * len(cols)),
conflict=sql.Identifier(conflict),
new=sql.SQL(",").join([sql.Identifier(c) for c in cols if c != conflict]),
excluded=sql.SQL(",").join(
[
sql.SQL("EXCLUDED.{}").format(sql.Identifier(c))
for c in cols
if c != conflict
]
),
)
if __name__ == "__main__":
from serenitas.utils import SerenitasFileHandler
from serenitas.utils.db2 import NaNtoNone
from serenitas.utils.pool import serenitas_pool
from serenitas.utils.env import CONFIG_DIR
logger = logging.getLogger("tranche_calib")
parser = argparse.ArgumentParser()
parser.add_argument(
"-u",
"--update",
action="store_true",
default=False,
help="Update from the last run date [default %default]",
)
parser.add_argument(
"-c",
"--config",
metavar="config_file",
help="Runs the list of indices provided in CONFIG_FILE",
)
parser.add_argument("-i", "--index", help="Index name we want to run")
parser.add_argument(
"--tenor", default="5yr", help="Tenor we want to run [default '5yr']"
)
parser.add_argument(
"--until",
default=prev_business_day(datetime.date.today()),
type=datetime.date.fromisoformat,
)
parser.add_argument("--start_from", default=None, type=datetime.date.fromisoformat)
parser.add_argument(
"-d", "--debug", action="store_true", help="more verbose logging"
)
parser.add_argument(
"-s", "--skewtype", action="store", help="skew type", default="bottomup"
)
parser.add_argument("-m", "--markit", action="store_true", help="Use Markit quotes")
args = parser.parse_args()
logger.setLevel(logging.DEBUG if args.debug else logging.INFO)
if args.markit:
TrancheBasket = MarkitTrancheBasket
if not args.debug:
handler = SerenitasFileHandler(f"calib_tranches_{datetime.date.today()}.log")
else:
handler = logging.StreamHandler()
handler.setFormatter(SerenitasFileHandler._formatter)
logger.handlers = [handler]
start_dates = { # 'hy10': datetime.date(2014, 8, 11),
# 'hy15': datetime.date(2014, 6, 10),
# 'hy17': datetime.date(2013, 1, 1),
"hy19": datetime.date(2013, 2, 1),
"hy21": datetime.date(2013, 10, 4),
"hy23": datetime.date(2014, 10, 16),
"hy25": datetime.date(2015, 10, 1),
"hy27": datetime.date(2016, 10, 4),
"hy29": datetime.date(2017, 10, 3),
"hy31": datetime.date(2018, 10, 2),
"hy33": datetime.date(2019, 10, 1),
"hy35": datetime.date(2020, 10, 2),
"hy37": datetime.date(2021, 10, 1),
"hy39": datetime.date(2022, 10, 3),
"ig9": datetime.date(2013, 1, 1),
"ig19": datetime.date(2013, 5, 1),
"ig21": datetime.date(2013, 9, 26),
"ig23": datetime.date(2014, 10, 14),
"ig25": datetime.date(2015, 9, 22),
"ig27": datetime.date(2016, 9, 27),
"ig29": datetime.date(2017, 9, 26),
"ig31": datetime.date(2018, 9, 25),
"ig33": datetime.date(2019, 9, 25),
"ig35": datetime.date(2020, 9, 25),
"ig37": datetime.date(2021, 9, 24),
"xo22": datetime.date(2014, 10, 20),
"xo24": datetime.date(2015, 9, 28),
"xo26": datetime.date(2016, 9, 27),
"xo28": datetime.date(2017, 9, 28),
"xo30": datetime.date(2018, 9, 25),
"xo32": datetime.date(2019, 10, 2),
"xo34": datetime.date(2020, 9, 22),
"xo36": datetime.date(2021, 9, 24),
"xo38": datetime.date(2022, 9, 20),
"eu9": datetime.date(2014, 9, 15),
"eu19": datetime.date(2013, 4, 3),
"eu21": datetime.date(2014, 3, 27),
"eu22": datetime.date(2014, 10, 22),
"eu24": datetime.date(2015, 9, 23),
"eu26": datetime.date(2016, 9, 27),
"eu28": datetime.date(2017, 9, 28),
"eu30": datetime.date(2018, 9, 25),
"eu32": datetime.date(2019, 9, 25),
"eu34": datetime.date(2020, 9, 22),
"eu36": datetime.date(2021, 9, 24),
"eu38": datetime.date(2022, 9, 20),
}
index_query = build_sql(
"tranche_risk_index",
[
"quoteset",
"price",
"basis",
"expected_loss",
"duration",
"theta",
"skew_x",
"skew_c",
],
"quoteset",
)
with serenitas_pool.connection() as serenitas_conn:
if args.config is None:
if args.index is None:
raise ValueError("Please provide an index to run")
config = {"runs": [(args.index, args.tenor, args.skewtype)]}
else:
with (CONFIG_DIR / args.config).open("r") as fh:
config = full_load(fh)
for index, tenor, skewtype in config["runs"]:
begin_date = None
index, series = index[:2].upper(), int(index[2:])
if args.update:
begin_date = get_lastdate(serenitas_conn, index, series, tenor)
if args.start_from is not None:
begin_date = args.start_from
if begin_date is None:
try:
begin_date = start_dates[f"{index.lower()}{series}"]
except KeyError:
print(index, series)
continue
dr = pd.bdate_range(begin_date, args.until)
if dr.empty:
continue
logger.info(f"calibrating {index}, {series}, {tenor}")
tranche_index = None
tranche_data = []
index_data = []
for d in dr.date:
logger.debug(f"calibrating for {d}")
try:
if tranche_index is None:
tranche_index = TrancheBasket(
index, series, tenor, value_date=d
)
else:
tranche_index.value_date = d
except (RuntimeError, ValueError) as e:
logger.error(e)
continue
try:
tranche_index.tweak()
except ValueError as e:
logger.error(e)
break
try:
tranche_index.build_skew(skewtype)
except ValueError as e:
logger.error(e)
logger.debug("Trying topdown")
tranche_index.rho[:] = np.nan
try:
tranche_index.build_skew("topdown")
except ValueError:
logger.error(e)
continue
df = pd.concat(
[
tranche_index.tranche_deltas(),
tranche_index.tranche_fwd_deltas(),
tranche_index.tranche_durations(),
tranche_index.tranche_EL(),
tranche_index.tranche_spreads(),
],
axis=1,
)
try:
df["theta"] = tranche_index.tranche_thetas(method="TLP")
except ValueError:
df["theta"] = None
duration, el, price = tranche_index.index_pv(clean=True)
index_data.append(
(
int(tranche_index.tranche_quotes.quoteset.values[0]),
price,
tranche_index.tweaks[0],
-el,
duration,
tranche_index.theta()[tenor],
tranche_index._skew.x.tobytes(),
tranche_index._skew.c.tobytes(),
)
)
df["tranche_id"] = tranche_index.tranche_quotes.id.values
df["quoteset"] = tranche_index.tranche_quotes.quoteset.values
df["corr_at_detach"] = tranche_index.rho[1:]
df["corr01"] = tranche_index.tranche_corr01()
del df["fwd_gamma"]
df["quote_price"] = (
1
- tranche_index.tranche_quotes.quotes.values
- tranche_index._accrued
)
df["calibrated_price"] = tranche_index.tranche_pvs().bond_price
tranche_data.append(df)
if index_data:
tranche_data = pd.concat(tranche_data)
cols = tranche_data.columns
tranches_query = build_sql("tranche_risk_tranches", cols, "tranche_id")
with serenitas_conn.cursor() as c:
c.executemany(
tranches_query,
[
tuple(map(NaNtoNone, t))
for t in tranche_data.itertuples(index=False)
],
)
c.executemany(
index_query, [tuple(map(NaNtoNone, t)) for t in index_data]
)
serenitas_conn.commit()
|
