{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from mark_swaptions import get_swaption_portfolio\n", "import datetime\n", "from db import dbconn\n", "from analytics import init_ontr\n", "conn = dbconn('dawndb')\n", "init_ontr()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "portf = get_swaption_portfolio(datetime.date.today(), conn)\n", "portf.mark(interp_method=\"bivariate_linear\")\n", "portf" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "df = portf._todf()\n", "df_ig=df.loc[df.Index == \"IG31 5yr\",[\"Delta\", \"Notional\"]]\n", "(df_ig.Notional * df_ig.Delta).sum()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "df_hy=df.loc[df.Index == \"HY31 5yr\", [\"Delta\", \"Notional\"]]\n", "(df_hy.Notional * df_hy.Delta).sum()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.7.2" } }, "nbformat": 4, "nbformat_minor": 2 }