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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"from analytics import TrancheBasket, ManualTrancheBasket\n",
"from datetime import date"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"index_type = 'HY'\n",
"series = 35\n",
"value_date = date.today()\n",
"new_index = ManualTrancheBasket(index_type, series, \"5yr\", value_date=value_date, ref=104.625, quotes=[43, 92.5, 110, 120.27])\n",
"new_index.tweak()\n",
"new_index.build_skew()\n",
"new_index "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"new_index.implied_ss()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#Build previous series skew to price this new series\n",
"base_index = TrancheBasket(index_type, series-4, \"5yr\")\n",
"base_index.tweak()\n",
"base_index.build_skew()\n",
"\n",
"new_index.rho = base_index.map_skew(new_index)\n",
"new_index"
]
},
{
"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": "3.8.5"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
|
