{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import curve_trades as ct\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from ipywidgets import widgets\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "w = widgets.Dropdown(\n",
    "    options=['IG', 'EU'],\n",
    "    value='IG',\n",
    "    description='Index:',\n",
    "    disabled=False,\n",
    ")\n",
    "w"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "index = w.value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#On the run spread differences\n",
    "spreads_diff = ct.curve_spread_diff(index, 6)\n",
    "spreads_diff.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Table of Spread Differences, and Z-score of current spread differences\n",
    "ct.spreads_diff_table(spreads_diff)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Theta per unit duration\n",
    "ct.theta_matrix_by_series(index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#on the run theta\n",
    "ct.on_the_run_theta(index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Curve Trade returns\n",
    "ct.curve_returns()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ct.cross_series_curve(index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Theta with 3-5-10 Strategy\n",
    "df = ct.ratio_within_series(param='duration')\n",
    "ct.curve_3_5_10(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Theta with 5-10 Strategy\n",
    "df = ct.ratio_within_series(param='duration')\n",
    "ct.curve_5_10(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Relative Spread Difference\n",
    "spread_ratio = ct.ratio_within_series(param = 'closespread')\n",
    "spread_ratio.groupby(level = ['date']).last()['closespread_ratio_to_5yr'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = ct.curve_model('5yr', '10yr')\n",
    "model_results = ct.curve_model_results(model[0], model[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Scenario Anslysis on current position\n",
    "report_date = (pd.datetime.today() - pd.offsets.BDay(1)).normalize()\n",
    "curve_pos = ct.curve_pos(report_date)\n",
    "origpv = curve_pos.pv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "flat_curve = ct.curve_shape(report_date, percentile = .05)\n",
    "for ind in curve_pos.indices:\n",
    "    ind.spread = flat_curve((pd.to_datetime(ind.end_date) - trade_date).days/365)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#PNL in flattening to a 5% case\n",
    "curve_pos.pv - origpv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = ct.forward_spread(index)\n",
    "df.plot()\n",
    "plt.ylabel('spread')\n",
    "plt.xlabel('forward spread start date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = ct.spot_forward(index)\n",
    "df.plot()\n",
    "plt.ylabel('spread')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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