1 files changed, 99 insertions, 0 deletions
diff --git a/python/swaption_pnl.py b/python/swaption_pnl.py
new file mode 100644
index 00000000..cf0cc653
--- /dev/null
+++ b/python/swaption_pnl.py
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+import datetime
+import pandas as pd
+from psycopg2.extensions import connection
+from risk.swaptions import get_swaption_portfolio
+from risk.indices import get_index_portfolio
+from pandas.tseries.offsets import BDay
+from pyisda.date import previous_twentieth
+from typing import Tuple
+
+
+def get_index_pv(
+    start_date: datetime.date,
+    end_date: datetime.date,
+    strategies: Tuple[str],
+    conn: connection,
+):
+    dr = pd.bdate_range(start_date, end_date)
+    pvs = []
+    daily = []
+    dates = []
+
+    for d in dr:
+        prev_day = (d - BDay()).date()
+        if previous_twentieth(d, roll=True) == d.date():
+            accrued = 0.0
+            for t in portf.trades:
+                d, amount = t._fee_leg.cashflows[0]
+                accrued -= amount * t.notional * t.factor * t.fixed_rate * 1e-4
+        else:
+            accrued = 0.0
+        portf = get_index_portfolio(prev_day, strategies, conn)
+        nav = 0.0
+        with conn.cursor() as c:
+            c.execute(
+                "SELECT upfront FROM cds WHERE trade_date=%s " "AND folder in %s",
+                (prev_day, strategies),
+            )
+            for (fee,) in c:
+                nav += fee
+        daily.append(nav + accrued)
+        pvs.append(portf.pv)
+        dates.append(prev_day)
+    df = pd.DataFrame({"pv": pvs, "daily": daily}, index=pd.to_datetime(dates))
+    return df
+
+
+def get_swaption_pv(
+    start_date: datetime.date, end_date: datetime.date, conn: connection
+):
+    dr = pd.bdate_range(start_date, end_date)
+    pv = []
+    daily = []
+    dates = []
+    for d in dr:
+        print(d)
+        prev_day = (d - BDay()).date()
+        portf = get_swaption_portfolio(prev_day, conn, source_list=["GS"])
+        nav = 0.0
+        # add terminations
+        with conn.cursor() as c:
+            c.execute(
+                "SELECT termination_fee "
+                "FROM swaptions WHERE termination_date=%s AND folder != 'STEEP'",
+                (prev_day,),
+            )
+            for (fee,) in c:
+                nav += fee
+        # add new trades
+        with conn.cursor() as c:
+            c.execute(
+                "SELECT notional * price/100 * (CASE WHEN buysell THEN -1. ELSE 1. END) "
+                "FROM swaptions WHERE trade_date=%s AND folder != 'STEEP'",
+                (prev_day,),
+            )
+            for (fee,) in c:
+                nav += fee
+        dates.append(prev_day)
+        pv.append(portf.pv)
+        daily.append(nav)
+    df = pd.DataFrame({"pv": pv, "daily": daily}, index=pd.to_datetime(dates))
+    return df
+
+
+if __name__ == "__main__":
+    import argparse
+    from utils.db import dbconn
+
+    dawndb = dbconn("dawndb")
+    parser = argparse.ArgumentParser()
+    parser.add_argument("start_date", type=datetime.datetime.fromisoformat)
+    parser.add_argument("end_date", type=datetime.datetime.fromisoformat)
+    args = parser.parse_args()
+    df_index = get_index_pv(
+        args.start_date, args.end_date, ("IGOPTDEL", "HYOPTDEL"), dawndb
+    )
+    df_swaption = get_swaption_pv(args.start_date, args.end_date, dawndb)
+    pnl_index = df_index.pv.diff() + df_index.daily
+    pnl_swaption = df_swaption.pv.diff() + df_swaption.daily
+    pnl = pd.concat([pnl_index, pnl_swaption], keys=["index", "swaption"], axis=1)