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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from bbg_helpers import retrieve_data, init_bbg_session, BBG_IP\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"with init_bbg_session(BBG_IP) as session:\n",
" hist_data = retrieve_data(session, [\"USFS022 Curncy\", \"USFS0230 Curncy\"], [\"PX_LAST\"], start_date=pd.datetime(1994, 1, 1))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df = pd.concat(hist_data).unstack(level=0)\n",
"df.columns = ['2-2', '2-30']\n",
"df.plot(title='2yr forward swap rates')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#not sure why this doesn't work\n",
"#df.pct_change().rolling(window='91D').corr().unstack(1)[('2-2', '2-30')].plot()\n",
"#rolling 3 months correlation\n",
"df.pct_change().rolling(window=63).corr().unstack(1)[('2-2', '2-30')].plot()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"#3months realized vol\n",
"roll = df.pct_change().rolling(window=63).std().plot()"
]
},
{
"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": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|
