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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from analytics.curve_trades import curve_pos\n",
+    "from analytics import Index, Portfolio\n",
+    "\n",
+    "import datetime\n",
+    "import exploration.VaR as var\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "date = (datetime.date.today() - pd.tseries.offsets.BDay(1)).date()\n",
+    "report_date = (date + pd.tseries.offsets.BMonthEnd(-1)).date()\n",
+    "index_type = \"IG\"\n",
+    "quantile = .025"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#IG Curve VaR\n",
+    "portf = curve_pos(date, index_type)\n",
+    "ig_curve_var = abs(var.hist_var(portf, quantile=quantile))\n",
+    "ig_curve_var"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#EU Curve VaR\n",
+    "index_type = \"EU\"\n",
+    "portf = curve_pos(date, index_type)\n",
+    "eu_curve_var = abs(var.hist_var(portf, quantile=quantile))\n",
+    "eu_curve_var"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Mortgage Hedge VaR - use IG spread relative move for VaR\n",
+    "df = var.get_pos(date)\n",
+    "df = df[df.strategy == 'HEDGE_MBS']\n",
+    "portf = Portfolio([Index.from_name(row.p_index, row.p_series, row.tenor,\n",
+    "                                       report_date, -row.notional)\n",
+    "                      for row in df[['p_index', 'tenor', 'p_series', 'notional']].\n",
+    "                       itertuples(index=False)])\n",
+    "portf.mark()\n",
+    "mort_hedge_var = abs(var.hist_var(portf, index_type = \"IG\", quantile=quantile, years=3))\n",
+    "mort_hedge_var"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Import the IM at the FCM account: calculate the IM share of different strategies as a share of VaR\n",
+    "filename = date.strftime('%Y%m%d') + \"_OTC_MARGIN_EX_DEF.csv\"\n",
+    "margin_df = pd.read_csv(\"/home/serenitas/Daily/SG_reports/\" + filename, index_col='Currency')\n",
+    "morg_hedge_im = mort_hedge_var + mort_hedge_var/(mort_hedge_var + ig_curve_var) * margin_df.loc[('USD', 'SG IMR')]\n",
+    "morg_hedge_im"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Oct ME Bond HY Equiv\n",
+    "bond_HY_equiv = -.12088\n",
+    "percentile = .95"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#95%tile \n",
+    "df, spread, dur = var.rel_spread_diff(report_date)\n",
+    "stress = pd.DataFrame()\n",
+    "stress.at[('2SD_widen', 'spread')] = df.quantile(.975) \n",
+    "stress.at[('2SD_tighten', 'spread')] = df.quantile(.025) \n",
+    "stress.at[('worst_widen', 'spread')] = df.max()\n",
+    "stress['pts'] = -stress * spread * dur/100\n",
+    "stress['nav_impact'] = bond_HY_equiv * stress['pts']\n",
+    "stress"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "port.cleared_cds_margins(report_date, percentile)"
+   ]
+  },
+  {
+   "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": "3.6.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}