diff options
Diffstat (limited to 'python/notebooks/Option Trades.ipynb')
| -rw-r--r-- | python/notebooks/Option Trades.ipynb | 150 |
1 files changed, 47 insertions, 103 deletions
diff --git a/python/notebooks/Option Trades.ipynb b/python/notebooks/Option Trades.ipynb index f550923d..ff4c6525 100644 --- a/python/notebooks/Option Trades.ipynb +++ b/python/notebooks/Option Trades.ipynb @@ -6,11 +6,15 @@ "metadata": {}, "outputs": [], "source": [ + "import datetime\n", + "import pandas as pd\n", + "import numpy as np\n", + "\n", + "from graphics import plot_time_color_map, plot_color_map\n", "from analytics import Swaption, BlackSwaption, BlackSwaptionVolSurface, Index, Portfolio\n", "from analytics.scenarios import run_swaption_scenarios, run_index_scenarios, run_portfolio_scenarios\n", - "import datetime\n", "\n", - "from exploration.swaption_calendar_spread import plot_trade_scenarios\n", + "#from exploration.swaption_calendar_spread import plot_trade_scenarios\n", "#import swaption_calendar_spread as spread" ] }, @@ -29,17 +33,48 @@ "metadata": {}, "outputs": [], "source": [ + "def plot_trade_scenarios(portf, shock_min=-.15, shock_max=.2, period=-1, vol_time_roll=True):\n", + " portf.reset_pv()\n", + " earliest_date = min(portf.swaptions, key=lambda x: x.exercise_date).exercise_date\n", + " date_range = pd.bdate_range(portf.indices[0].value_date,\n", + " earliest_date - pd.tseries.offsets.BDay(), freq='3B')\n", + " vol_shock = np.arange(-0.15, 0.3, 0.01)\n", + " spread_shock = np.arange(shock_min, shock_max, 0.01)\n", + " index = portf.indices[0].name.split()[1]\n", + " series = portf.indices[0].name.split()[3][1:]\n", + " vs = BlackSwaptionVolSurface(index, series, value_date=portf.indices[0].value_date)\n", + " vol_surface = vs[vs.list(option_type='payer')[-1]]\n", + "\n", + " df = run_portfolio_scenarios(portf, date_range, spread_shock, vol_shock, vol_surface,\n", + " params=[\"pnl\",\"delta\"])\n", + "\n", + " hy_plot_range = 100 + (500 - portf.indices[0].spread * (1 + spread_shock)) * \\\n", + " abs(portf.indices[0].DV01) / portf.indices[0].notional * 100\n", + "\n", + " shock = hy_plot_range if index == 'HY' else portf.indices[0].spread * (1 + spread_shock)\n", + "\n", + " plot_time_color_map(df[round(df.vol_shock,2)==0], shock, 'pnl', index=index)\n", + " plot_time_color_map(df[round(df.vol_shock,2)==.2], shock, 'pnl', index=index)\n", + " plot_color_map(df.loc[date_range[period]], shock, vol_shock, 'pnl', index=index)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ "#Ad hoc\n", - "option_delta = Index.from_name('IG', 29, '5yr', trade_date=datetime.date(2018, 1, 3))\n", - "option_delta.spread = 50\n", - "option1 = BlackSwaption(option_delta, datetime.date(2018, 2, 21), 55, option_type=\"payer\")\n", - "option2 = BlackSwaption(option_delta, datetime.date(2018, 2, 21), 67.5, option_type=\"payer\")\n", - "option3 = BlackSwaption(option_delta, datetime.date(2018, 2, 21), 80, option_type=\"payer\")\n", - "option1.sigma = .38\n", - "option2.sigma = .61\n", + "option_delta = Index.from_name('IG', 30, '5yr', value_date=datetime.date(2018, 5, 17))\n", + "option_delta.spread = 61\n", + "option1 = BlackSwaption(option_delta, datetime.date(2018, 8, 15), 60, option_type=\"payer\")\n", + "option2 = BlackSwaption(option_delta, datetime.date(2018, 8, 15), 80, option_type=\"payer\")\n", + "option3 = BlackSwaption(option_delta, datetime.date(2018, 8, 15), 80, option_type=\"payer\")\n", + "option1.sigma = .381\n", + "option2.sigma = .545\n", "option3.sigma = .69\n", "option1.notional = 100_000_000\n", - "option2.notional = 200_000_000\n", + "option2.notional = 300_000_000\n", "option3.notional = 1\n", "option1.direction = 'Long'\n", "option2.direction = 'Short'\n", @@ -68,34 +103,6 @@ "metadata": {}, "outputs": [], "source": [ - "portf.trade_date = datetime.date(2018,2,1)\n", - "portf.ref = 52\n", - "#portf.swaptions[0].sigma = .25\n", - "#portf.swaptions[1].sigma = .31\n", - "#portf.swaptions[2].sigma = .46\n", - "portf.swaptions[0].sigma = .38\n", - "portf.swaptions[1].sigma = .61\n", - "#portf.swaptions[2].sigma = .69\n", - "portf" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "df.spread = df.spread.round(2)\n", - "df1= df.set_index('spread', append=True)\n", - "df1.xs(('2018-01-16', '66.0'))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ "#Dec Jan 2017 Trade\n", "option_delta = Index.from_tradeid(864)\n", "option1 = BlackSwaption.from_tradeid(3, option_delta)\n", @@ -147,7 +154,7 @@ "option_delta_pf.notional = 50_335_169\n", "\n", "portf = Portfolio([option1_pf, option2_pf, option_delta_pf])\n", - "portf.trade_date = datetime.date(2017, 5, 17)\n", + "portf.value_date = datetime.date(2017, 5, 17)\n", "portf.mark()\n", "plot_trade_scenarios(portf)" ] @@ -171,69 +178,6 @@ "execution_count": null, "metadata": {}, "outputs": [], - "source": [ - "#Ad hoc\n", - "option_delta = Index.from_name('IG', 29, '5yr')\n", - "option_delta.spread = 49.5\n", - "option1 = BlackSwaption(option_delta, datetime.date(2018, 2, 21), 55, option_type=\"payer\")\n", - "option2 = BlackSwaption(option_delta, datetime.date(2018, 2, 21), 67.5, option_type=\"payer\")\n", - "option3 = BlackSwaption(option_delta, datetime.date(2018, 1, 21), 52.5, option_type=\"payer\")\n", - "option4 = BlackSwaption(option_delta, datetime.date(2018, 1, 21), 60, option_type=\"payer\")\n", - "option1.sigma = .38\n", - "option2.sigma = .61\n", - "option3.sigma = .371\n", - "option4.sigma = .581\n", - "option1.notional = 100_000_000\n", - "option2.notional = 200_000_000\n", - "option3.notional = 100_000_000\n", - "option4.notional = 100_000_000\n", - "option1.direction = 'Long'\n", - "option2.direction = 'Short'\n", - "option3.direction = 'Short'\n", - "option4.direction = 'Long'\n", - "#option_delta.notional = 1\n", - "option_delta.notional = option1.notional * option1.delta + option2.notional * option2.delta \n", - "option_delta.direction = 'Seller' if option_delta.notional > 0 else 'Buyer'\n", - "option_delta.notional = abs(option_delta.notional)\n", - "portf = Portfolio([option1, option2, option3, option4, option_delta])\n", - "#Plot Scenarios Inputs: Portfolio, spread shock tightening%, spread shock widening%, snapshot period)\n", - "plot_trade_scenarios(portf, -.15, .8, -4, vol_time_roll=False)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "portf" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "portf.pv" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "portf.trade_date = datetime.date(2018,1,16)\n", - "portf.ref = 47\n", - "portf.pnl" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], "source": [] } ], @@ -253,7 +197,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.4" + "version": "3.6.5" } }, "nbformat": 4, |