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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "1d37c1d7-e332-4cb3-b228-0045c547ab93",
"metadata": {},
"outputs": [],
"source": [
"import pnl_explain as pl\n",
"import datetime\n",
"from itertools import chain\n",
"from serenitas.utils.db import dbconn\n",
"\n",
"dawndb = dbconn(\"dawndb\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f600c71b-59a9-4f10-beac-37718f6e4016",
"metadata": {},
"outputs": [],
"source": [
"today = datetime.date.today()\n",
"start_date = datetime.date(2022,7,1)\n",
"end_date = datetime.date(2022,11,1)\n",
"strats = {\n",
" \"swaption\": (\"IGOPTDEL\", \"HYOPTDEL\"),\n",
" \"macro_hedge\": (\"HEDGE_MAC\",),\n",
" \"tranche\": (\"IGINX\", \"HYINX\", \"XOINX\", \"EUINX\"),\n",
" \"curve\": (\"SER_ITRXCURVE\", \"SER_IGCURVE\", \"SER_HYCURVE\"),\n",
" \"rmbs_hedge\":(\"HEDGE_MBS\",),\n",
" \"clo_hedge\": (\"HEDGE_CLO\",),\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "79fdf8bb-79a9-48e5-b97e-ad5d862078fd",
"metadata": {},
"outputs": [],
"source": [
"for fund in ['SERCGMAST', 'ISOSEL', 'BOWDST']:\n",
" pnl = {}\n",
" #bond PNL---------------\n",
" for ac in ['CRT', 'Subprime', 'CLO']:\n",
" df_instrument = pl.get_pv(conn=dawndb, \n",
" fund=fund, \n",
" pnl_type = 'bond', \n",
" asset_class = ac, \n",
" start_date = start_date, \n",
" end_date = end_date)\n",
" if not df_instrument.empty:\n",
" pnl[ac] = pl.get_pnl(df_instrument, 'bond')\n",
" #Tranches---------------\n",
" ac = 'tranche'\n",
" pv2=True\n",
" df_instrument = pl.get_pv(conn=dawndb, \n",
" fund=fund, \n",
" pnl_type = ac, \n",
" start_date = start_date, \n",
" end_date = end_date,\n",
" pv2=pv2)\n",
" pnl[ac] = pl.get_pnl(df_instrument, ac, pv2=pv2)\n",
" #swaptions--------------\n",
" ac = 'swaption'\n",
" df_instrument = pl.get_pv(conn=dawndb, \n",
" fund=fund, \n",
" pnl_type = ac, \n",
" start_date = start_date, \n",
" end_date = end_date, \n",
" source_list=['CITI', 'JPM'])\n",
" pnl[ac] = pl.get_pnl(df_instrument, ac)\n",
" #All the cleared indices--------\n",
" for ac in ['macro_hedge', 'curve', 'tranche', 'swaption', 'rmbs_hedge', 'clo_hedge']: \n",
" df_index = pl.get_index_pv(\n",
" start_date, end_date, fund, dawndb, strats[ac]\n",
" )\n",
" pnl[ac+'_index'] = df_index.pv.diff() + df_index[[\"upfront\", \"accrued\"]].sum(axis=1)\n",
" #FX PV-------------\n",
" ac = 'fx_forward'\n",
" df_instrument = pl.get_fx_pv(start_date = start_date,\n",
" end_date = end_date,\n",
" fund=fund)\n",
" pnl_inst = pl.get_pnl(df_instrument, ac)\n",
" pnl_inst.index = pd.to_datetime(pnl_inst.index)\n",
" pnl[ac] = pnl_inst\n",
" pnl_all = pd.concat(pnl, axis=1).fillna(0)\n",
" filename = '/home/serenitas/Daily/' + today.strftime(\"%Y-%m-%d\")+ \"/\" + fund + '_pnl.csv'\n",
" pnl_all.to_csv(filename)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e179cc99-edb1-48b9-b50e-7a5ae25c1e86",
"metadata": {},
"outputs": [],
"source": [
"#check if first day of NAV and if the upfront payment line up. if not, PNL will not work\n",
"#check trade date vs. that NULL NAV/upfront date. If it is termination it is okay\n",
"ac= 'tranche'\n",
"df_instrument = pl.get_pv(conn=dawndb, \n",
" fund=fund, \n",
" pnl_type = ac, \n",
" start_date = start_date, \n",
" end_date = end_date,\n",
" pv2=pv2)\n",
"check_trades = df_instrument.loc[df_instrument['clean_nav'].isna() &\n",
" df_instrument['principal'].notna()]\n",
"cds_trades = pd.read_sql_query(\"SELECT id, trade_date from cds\", dawndb,parse_dates=[\"trade_date\"], index_col=['id'])\n",
"check_trades = pd.merge(check_trades, cds_trades, left_index=True, right_index=True)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|
