{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from analytics.tranche_basket import DualCorrTranche, TrancheBasket\n", "import datetime" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "ig29 = TrancheBasket(\"IG\", 29, \"5yr\", value_date=datetime.date(2019, 2, 6))\n", "ig29.tweak()\n", "ig29.build_skew()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "bs2 = DualCorrTranche(\"BS\", 2, \"2yr\", attach=7, detach=10, corr_attach=0.4, corr_detach=0.42, tranche_running=500,\n", " value_date=datetime.date(2019, 2, 6))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "bs2.singlename_spreads()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "bs2._index.spread()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "bs2.mark(skew=ig29.skew)\n", "bs2.rho" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "bs2.spread" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "bs2" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#delta adjustement\n", "bs2.upfront + bs2.delta * (157 - bs2._index.spread())*1e-4* bs2._index.duration()*100" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "jtd = bs2.jump_to_default(ig29.skew)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "jtd.sort_values()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from pyisda.curve import Senior, Subordinated, MM14\n", "bs2._index[('BACR', Senior, MM14)].inspect()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "bs2._index[('BACR', Subordinated, MM14)].inspect()" ] } ], "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 }