diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/risk/bonds.py | 29 |
1 files changed, 12 insertions, 17 deletions
diff --git a/python/risk/bonds.py b/python/risk/bonds.py index 2a8b28c5..28d823cc 100644 --- a/python/risk/bonds.py +++ b/python/risk/bonds.py @@ -6,7 +6,7 @@ import datetime from enum import Enum, auto from serenitas.analytics.yieldcurve import YC from serenitas.analytics.index import CreditIndex -from serenitas.analytics.index_data import on_the_run +from serenitas.analytics.base import Trade class AssetClass(Enum): @@ -228,8 +228,7 @@ def get_portfolio(date, conn, asset_class: AssetClass, fund="SERCGMAST"): def crt_risk(date, dawn_conn, crt_engine, fund="SERCGMAST"): - hy_ontr = CreditIndex("HY", on_the_run("HY", date), "5yr", value_date=date) - hy_ontr.mark() + Trade.init_ontr(date) yc = YC(evaluation_date=date) df = get_portfolio(date, dawn_conn, AssetClass.CRT, fund) scen = { @@ -244,18 +243,23 @@ def crt_risk(date, dawn_conn, crt_engine, fund="SERCGMAST"): if scen_type is None and date < d: scen_type = s sql_string = ( - "SELECT a.* FROM crt.priced_at_market a " + "SELECT a.*, be.* FROM crt.priced_at_market a " "JOIN (SELECT cusip, MAX(timestamp) timestamp " "FROM crt.priced_at_market where timestamp between %s " "AND date_add(%s, INTERVAL 1 DAY) " "and model_des = %s GROUP BY cusip) b " - "ON a.cusip= b.cusip AND a.timestamp = b.timestamp;" + "using (cusip, timestamp) " + "LEFT JOIN map_cusip using (cusip) " + "LEFT JOIN bond_types USING (bond) " + "LEFT JOIN (select bond_type, value from crt.beta_estimates " + "where date = (SELECT MAX(date) FROM crt.beta_estimates where date <= %s)) be " + "using (bond_type)" ) df_model = pd.read_sql_query( sql_string, crt_engine, "cusip", - params=(date - datetime.timedelta(days=15), date, scen_type), + params=(date - datetime.timedelta(days=15), date, scen_type, date), ) if any(~df_model["delta.ir"].isna()): df_model = df_model[~df_model["delta.ir"].isna()] @@ -269,22 +273,13 @@ def crt_risk(date, dawn_conn, crt_engine, fund="SERCGMAST"): curr_ntl=df.notional * df.factor, hy_equiv=( df.modDur - / hy_ontr.risky_annuity - * Trade._beta["CRT"] + / Trade._ontr["HY"].risky_annuity + * df.value * df.notional * df.factor ), ) df["bond_yield"] = df.swap_rate + df.DM / 10000 - delta = pd.read_sql_query( - "SELECT distinct on (strategy) " - "strategy, beta_crt from beta_crt WHERE " - "date <= %s ORDER BY strategy, date desc", - dawn_conn, - index_col="strategy", - params=(date,), - ) - df.hy_equiv *= df["strategy"].replace(delta.beta_crt.to_dict()) return df |