{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import exploration.option_trades as rvol\n",
    "import datetime\n",
    "import pandas as pd\n",
    "\n",
    "from analytics import on_the_run\n",
    "from scipy.interpolate import interp1d\n",
    "from matplotlib import pyplot as plt\n",
    "from ipywidgets import widgets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "w = widgets.Dropdown(\n",
    "    options=['IG', 'HY'],\n",
    "    value='IG',\n",
    "    description='Index:',\n",
    "    disabled=False,\n",
    ")\n",
    "w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "index = w.value\n",
    "start_date=datetime.date(2014, 6, 11)\n",
    "onTR, model = rvol.realized_vol(index, tenor=\"5yr\", years=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "onTR.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#compute lo and hi percentiles of atm volatility daily change (vol of vol)\n",
    "rvol.vol_var()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = rvol.atm_vol(index, start_date, moneyness = .2)\n",
    "df['steepness'] = df.otm_vol - df.atm_vol\n",
    "df1 = df.reset_index()\n",
    "df1['date'] = df1.quotedate.dt.date\n",
    "df1 = df1.groupby(['date','expiry']).last()\n",
    "#Need to do: the vol looks jumpy, is it because of quote source issue? yes, need to first try to get the same quote source..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = []\n",
    "time = [1/12, 2/12, 3/12, 4/12, 5/12]\n",
    "for t in time:\n",
    "    for date, g in df1.groupby(level='date'):\n",
    "        f = interp1d(g['T'].values, g['steepness'].values, fill_value='extrapolate')\n",
    "        r.append((date, t, f(t)))\n",
    "steepness = pd.DataFrame(r, columns=['date', 'T', 'steepness'])\n",
    "steepness = steepness.set_index(['date','T']).unstack().astype('float')\n",
    "steepness.columns = steepness.columns.droplevel()\n",
    "steepness.ewm(span = 3).mean().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(steepness.iloc[-1] - steepness.mean()) / steepness.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Need to do: look at steepness not on moneyness but on delta range (60 delta vs 20 delta)"
   ]
  }
 ],
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