{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Introduction\n", "This notebook takes the master data file produced in the earlier ED_Future notebook ('..\\data\\Futures\\ed_master.csv') \n", "and creates a concatenated file of futures contracts containing your chosen maturities. EG when do you want to roll? \n", "How long dated do you want to go? Do you want to test / trade the front contract only? A contract a year out? 4 years out?\n", "Back in 1982 there was not much choice. These days you can trade for delivery four years out." ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [], "source": [ "#Imports\n", "import pandas as pd\n", "import numpy as np\n", "from numba import jit\n", "import os\n", "import ffn\n", "from pandas.tseries.offsets import *\n", "import matplotlib.pyplot as plt\n", "%matplotlib notebook" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [], "source": [ "#read in the master data file produced in the earlier notebook which contains every contract maturity\n", "ed_master = '..\\data\\Futures\\ed_master.csv'\n", "\n", "eurodollar = pd.read_csv(\n", " ed_master,\n", " header=0,\n", " parse_dates=[\"Date\", \"Start\", 'End'],\n", ")" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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DateOpenHighLowCloseVolumeOpen_InterestReturnVAMIContractStartEndDStartDEnd
01982-02-0283.7784.1083.7783.8894111260.001672100.167184ED1982H1982-02-011982-03-15FalseTrue
11982-02-0283.7984.1083.7683.859419830.001912100.191182ED1982M1982-02-011982-06-14TrueTrue
21982-02-0283.8084.0583.7683.859414440.001912100.191182ED1982U1982-02-011982-09-13TrueFalse
31982-02-0383.9684.1083.7183.737591241-0.00178899.988058ED1982H1982-02-011982-03-15FalseTrue
41982-02-0383.9784.0383.8583.8975910210.000477100.238977ED1982M1982-02-011982-06-14TrueTrue
\n", "
" ], "text/plain": [ " Date Open High Low Close Volume Open_Interest Return \\\n", "0 1982-02-02 83.77 84.10 83.77 83.88 941 1126 0.001672 \n", "1 1982-02-02 83.79 84.10 83.76 83.85 941 983 0.001912 \n", "2 1982-02-02 83.80 84.05 83.76 83.85 941 444 0.001912 \n", "3 1982-02-03 83.96 84.10 83.71 83.73 759 1241 -0.001788 \n", "4 1982-02-03 83.97 84.03 83.85 83.89 759 1021 0.000477 \n", "\n", " VAMI Contract Start End DStart DEnd \n", "0 100.167184 ED1982H 1982-02-01 1982-03-15 False True \n", "1 100.191182 ED1982M 1982-02-01 1982-06-14 True True \n", "2 100.191182 ED1982U 1982-02-01 1982-09-13 True False \n", "3 99.988058 ED1982H 1982-02-01 1982-03-15 False True \n", "4 100.238977 ED1982M 1982-02-01 1982-06-14 True True " ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Add columns which will trigger your choice of contracts\n", "#Don't worry about the nonsensical VAMI. Thgis will get updated when maturites have been chosen\n", "#and the datafile thinned out to only those contract you want to test / trade\n", "eurodollar['DStart'] = eurodollar.Date.eq(eurodollar.Date.shift(1))\n", "eurodollar['DEnd'] = eurodollar.Date.eq(eurodollar.Date.shift(-1))\n", "eurodollar.head()" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [], "source": [ "#initialise variables\n", "#what length of expiration are you looking for in days?\n", "expiration = int(400)" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [], "source": [ "#Create a dictionary to store data as you loop through the master file\n", "#and a counter\n", "temp_futures = {}\n", "a = 0\n", "\n", "#loop through the master data file\n", "for i, row in enumerate(eurodollar.itertuples(), 0):\n", "\n", " if row.DStart == False:\n", " #for each trading day initiate the price series with the earliest expiry first. \n", " #Find your target expiration date\n", " #and how wide of your target this first expiry listed for this trading day is\n", " targetExpiration = row.Date + expiration * Day()\n", " targetExpirationDifference = abs(targetExpiration - row.End)\n", " expirationLocation = (i)\n", "\n", " if row.DStart == True and row.DEnd == True:\n", " #iterate through the different expirations trading each day\n", " #find the closest match to targetExpiration\n", " if abs(targetExpiration - row.End) <= targetExpirationDifference:\n", " #error correction routine - when diff between target expiration and expiration continues to decline,\n", " #algo chooses the closer expirataion\n", " targetExpirationDifference = abs(targetExpiration - row.End)\n", " expirationLocation = (i)\n", " #closest expiration to your target expiration has now been chosen. \n", " \n", " if row.DEnd == False:\n", " #Now you have reached the last contract trading on the relevant trading day\n", " if abs(targetExpiration - row.End) <= targetExpirationDifference:\n", " #error correction routine - when diff between target expiration and expiration continues to decline,\n", " #algo chooses the closer expirataion\n", " targetExpirationDifference = abs(targetExpiration - row.End)\n", " expirationLocation = (i)\n", " #You have now found the closest expiry to your target expiry for a given trading day...\n", " #So add a row for the day's data for that expiry to the dictionary\n", " temp_futures[eurodollar.Date[i]] = [\n", " eurodollar.Date[i], eurodollar.Close[expirationLocation],\n", " eurodollar.Return[expirationLocation],\n", " eurodollar.Volume[expirationLocation],\n", " eurodollar.Contract[expirationLocation],\n", " eurodollar.Start[expirationLocation],\n", " eurodollar.End[expirationLocation], targetExpiration,\n", " targetExpirationDifference\n", " ]" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [], "source": [ "#This function will calculate the VAMI each day from the return for that day\n", "@jit()\n", "def calculator(a):\n", " res = np.empty(rolling_eurodollar.VAMI.shape)\n", " res[0] = 100\n", " for i in range(1, res.shape[0]):\n", " res[i] = res[i-1] +(res[i-1]* a[i])\n", " return res" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": [ "#Create a dataframe from the dictionary temp_futures\n", "rolling_eurodollar = pd.DataFrame(temp_futures).T\n", "rolling_eurodollar.index.name = 'Date'\n", "rolling_eurodollar.columns = [\n", " 'Date', 'Close', 'Return', 'Volume', 'Contract', 'Start', 'End',\n", " 'targetExpiration', 'targetExpirationDifference'\n", "]\n", "rolling_eurodollar['VAMI']=0.0\n", "#calculate the VAMI for each day\n", "rolling_eurodollar['VAMI'] = calculator(\n", " *rolling_eurodollar[list(rolling_eurodollar.loc[:, ['Return']])].values.T)" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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DateCloseReturnVolumeContractStartEndtargetExpirationtargetExpirationDifferenceVAMI
Date
2019-04-082019-04-08 00:00:0097.68-0.00020470882091ED2020M2016-06-30 00:00:002020-06-15 00:00:002020-05-12 00:00:0034 days 00:00:00152.649468
2019-04-092019-04-09 00:00:0097.710.00030712567924ED2020M2016-06-30 00:00:002020-06-15 00:00:002020-05-13 00:00:0033 days 00:00:00152.696351
2019-04-102019-04-10 00:00:0097.730.000204687106436ED2020M2016-06-30 00:00:002020-06-15 00:00:002020-05-14 00:00:0032 days 00:00:00152.727606
2019-04-112019-04-11 00:00:0097.695-0.0003581353472ED2020M2016-06-30 00:00:002020-06-15 00:00:002020-05-15 00:00:0031 days 00:00:00152.672909
2019-04-122019-04-12 00:00:0097.625-0.00071651653472ED2020M2016-06-30 00:00:002020-06-15 00:00:002020-05-16 00:00:0030 days 00:00:00152.563517
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" ], "text/plain": [ " Date Close Return Volume Contract \\\n", "Date \n", "2019-04-08 2019-04-08 00:00:00 97.68 -0.000204708 82091 ED2020M \n", "2019-04-09 2019-04-09 00:00:00 97.71 0.000307125 67924 ED2020M \n", "2019-04-10 2019-04-10 00:00:00 97.73 0.000204687 106436 ED2020M \n", "2019-04-11 2019-04-11 00:00:00 97.695 -0.00035813 53472 ED2020M \n", "2019-04-12 2019-04-12 00:00:00 97.625 -0.000716516 53472 ED2020M \n", "\n", " Start End targetExpiration \\\n", "Date \n", "2019-04-08 2016-06-30 00:00:00 2020-06-15 00:00:00 2020-05-12 00:00:00 \n", "2019-04-09 2016-06-30 00:00:00 2020-06-15 00:00:00 2020-05-13 00:00:00 \n", "2019-04-10 2016-06-30 00:00:00 2020-06-15 00:00:00 2020-05-14 00:00:00 \n", "2019-04-11 2016-06-30 00:00:00 2020-06-15 00:00:00 2020-05-15 00:00:00 \n", "2019-04-12 2016-06-30 00:00:00 2020-06-15 00:00:00 2020-05-16 00:00:00 \n", "\n", " targetExpirationDifference VAMI \n", "Date \n", "2019-04-08 34 days 00:00:00 152.649468 \n", "2019-04-09 33 days 00:00:00 152.696351 \n", "2019-04-10 32 days 00:00:00 152.727606 \n", "2019-04-11 31 days 00:00:00 152.672909 \n", "2019-04-12 30 days 00:00:00 152.563517 " ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "rolling_eurodollar.tail()" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [], "source": [ "#Save your time series to csv for retrieval for later backtesting with your chosen program\n", "rolling_eurodollar.to_csv('..\\data\\Futures/rolling_eurodollar.csv', index=None)" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [], "source": [ "#Create a new dataframe to display the results\n", "ED=rolling_eurodollar[['VAMI']].copy()" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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VAMI
Date
2019-04-08152.649468
2019-04-09152.696351
2019-04-10152.727606
2019-04-11152.672909
2019-04-12152.563517
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" ], "text/plain": [ " VAMI\n", "Date \n", "2019-04-08 152.649468\n", "2019-04-09 152.696351\n", "2019-04-10 152.727606\n", "2019-04-11 152.672909\n", "2019-04-12 152.563517" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Inspect the final results\n", "ED.tail()" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "/* Put everything inside the global mpl namespace */\n", "window.mpl = {};\n", "\n", "\n", "mpl.get_websocket_type = function() {\n", " if (typeof(WebSocket) !== 'undefined') {\n", " return WebSocket;\n", " } else if (typeof(MozWebSocket) !== 'undefined') {\n", " return MozWebSocket;\n", " } else {\n", " alert('Your browser does not have WebSocket support.' +\n", " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", " 'Firefox 4 and 5 are also supported but you ' +\n", " 'have to enable WebSockets in about:config.');\n", " };\n", "}\n", "\n", "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", " this.id = figure_id;\n", "\n", " this.ws = websocket;\n", "\n", " this.supports_binary = (this.ws.binaryType != undefined);\n", "\n", " if (!this.supports_binary) {\n", " var warnings = document.getElementById(\"mpl-warnings\");\n", " if (warnings) {\n", " warnings.style.display = 'block';\n", " warnings.textContent = (\n", " \"This browser does not support binary websocket messages. \" +\n", " \"Performance may be slow.\");\n", " }\n", " }\n", "\n", " this.imageObj = new Image();\n", "\n", " this.context = undefined;\n", " this.message = undefined;\n", " this.canvas = undefined;\n", " this.rubberband_canvas = undefined;\n", " this.rubberband_context = undefined;\n", " this.format_dropdown = undefined;\n", "\n", " this.image_mode = 'full';\n", "\n", " this.root = $('
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');\n", "\n", " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", "\n", " function canvas_keyboard_event(event) {\n", " return fig.key_event(event, event['data']);\n", " }\n", "\n", " canvas_div.keydown('key_press', canvas_keyboard_event);\n", " canvas_div.keyup('key_release', canvas_keyboard_event);\n", " this.canvas_div = canvas_div\n", " this._canvas_extra_style(canvas_div)\n", " this.root.append(canvas_div);\n", "\n", " var canvas = $('');\n", " canvas.addClass('mpl-canvas');\n", " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", "\n", " this.canvas = canvas[0];\n", " this.context = canvas[0].getContext(\"2d\");\n", "\n", " var backingStore = this.context.backingStorePixelRatio ||\n", "\tthis.context.webkitBackingStorePixelRatio ||\n", "\tthis.context.mozBackingStorePixelRatio ||\n", "\tthis.context.msBackingStorePixelRatio ||\n", "\tthis.context.oBackingStorePixelRatio ||\n", "\tthis.context.backingStorePixelRatio || 1;\n", "\n", " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", "\n", " var rubberband = $('');\n", " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", "\n", " var pass_mouse_events = true;\n", "\n", " canvas_div.resizable({\n", " start: function(event, ui) {\n", " pass_mouse_events = false;\n", " },\n", " resize: function(event, ui) {\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " stop: function(event, ui) {\n", " pass_mouse_events = true;\n", " fig.request_resize(ui.size.width, ui.size.height);\n", " },\n", " });\n", "\n", " function mouse_event_fn(event) {\n", " if (pass_mouse_events)\n", " return fig.mouse_event(event, event['data']);\n", " }\n", "\n", " rubberband.mousedown('button_press', mouse_event_fn);\n", " rubberband.mouseup('button_release', mouse_event_fn);\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband.mousemove('motion_notify', mouse_event_fn);\n", "\n", " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", "\n", " canvas_div.on(\"wheel\", function (event) {\n", " event = event.originalEvent;\n", " event['data'] = 'scroll'\n", " if (event.deltaY < 0) {\n", " event.step = 1;\n", " } else {\n", " event.step = -1;\n", " }\n", " mouse_event_fn(event);\n", " });\n", "\n", " canvas_div.append(canvas);\n", " canvas_div.append(rubberband);\n", "\n", " this.rubberband = rubberband;\n", " this.rubberband_canvas = rubberband[0];\n", " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", " this.rubberband_context.strokeStyle = \"#000000\";\n", "\n", " this._resize_canvas = function(width, height) {\n", " // Keep the size of the canvas, canvas container, and rubber band\n", " // canvas in synch.\n", " canvas_div.css('width', width)\n", " canvas_div.css('height', height)\n", "\n", " canvas.attr('width', width * mpl.ratio);\n", " canvas.attr('height', height * mpl.ratio);\n", " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", "\n", " rubberband.attr('width', width);\n", " rubberband.attr('height', height);\n", " }\n", "\n", " // Set the figure to an initial 600x600px, this will subsequently be updated\n", " // upon first draw.\n", " this._resize_canvas(600, 600);\n", "\n", " // Disable right mouse context menu.\n", " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", " return false;\n", " });\n", "\n", " function set_focus () {\n", " canvas.focus();\n", " canvas_div.focus();\n", " }\n", "\n", " window.setTimeout(set_focus, 100);\n", "}\n", "\n", "mpl.figure.prototype._init_toolbar = function() {\n", " var fig = this;\n", "\n", " var nav_element = $('
')\n", " nav_element.attr('style', 'width: 100%');\n", " this.root.append(nav_element);\n", "\n", " // Define a callback function for later on.\n", " function toolbar_event(event) {\n", " return fig.toolbar_button_onclick(event['data']);\n", " }\n", " function toolbar_mouse_event(event) {\n", " return fig.toolbar_button_onmouseover(event['data']);\n", " }\n", "\n", " for(var toolbar_ind in mpl.toolbar_items) {\n", " var name = mpl.toolbar_items[toolbar_ind][0];\n", " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", " var image = mpl.toolbar_items[toolbar_ind][2];\n", " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", "\n", " if (!name) {\n", " // put a spacer in here.\n", " continue;\n", " }\n", " var button = $('');\n", " button.click(method_name, toolbar_event);\n", " button.mouseover(tooltip, toolbar_mouse_event);\n", " nav_element.append(button);\n", " }\n", "\n", " // Add the status bar.\n", " var status_bar = $('');\n", " nav_element.append(status_bar);\n", " this.message = status_bar[0];\n", "\n", " // Add the close button to the window.\n", " var buttongrp = $('
');\n", " var button = $('');\n", " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", " buttongrp.append(button);\n", " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", " titlebar.prepend(buttongrp);\n", "}\n", "\n", "mpl.figure.prototype._root_extra_style = function(el){\n", " var fig = this\n", " el.on(\"remove\", function(){\n", "\tfig.close_ws(fig, {});\n", " });\n", "}\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(el){\n", " // this is important to make the div 'focusable\n", " el.attr('tabindex', 0)\n", " // reach out to IPython and tell the keyboard manager to turn it's self\n", " // off when our div gets focus\n", "\n", " // location in version 3\n", " if (IPython.notebook.keyboard_manager) {\n", " IPython.notebook.keyboard_manager.register_events(el);\n", " }\n", " else {\n", " // location in version 2\n", " IPython.keyboard_manager.register_events(el);\n", " }\n", "\n", "}\n", "\n", "mpl.figure.prototype._key_event_extra = function(event, name) {\n", " var manager = IPython.notebook.keyboard_manager;\n", " if (!manager)\n", " manager = IPython.keyboard_manager;\n", "\n", " // Check for shift+enter\n", " if (event.shiftKey && event.which == 13) {\n", " this.canvas_div.blur();\n", " event.shiftKey = false;\n", " // Send a \"J\" for go to next cell\n", " event.which = 74;\n", " event.keyCode = 74;\n", " manager.command_mode();\n", " manager.handle_keydown(event);\n", " }\n", "}\n", "\n", "mpl.figure.prototype.handle_save = function(fig, msg) {\n", " fig.ondownload(fig, null);\n", "}\n", "\n", "\n", "mpl.find_output_cell = function(html_output) {\n", " // Return the cell and output element which can be found *uniquely* in the notebook.\n", " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", " // IPython event is triggered only after the cells have been serialised, which for\n", " // our purposes (turning an active figure into a static one), is too late.\n", " var cells = IPython.notebook.get_cells();\n", " var ncells = cells.length;\n", " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", " data = data.data;\n", " }\n", " if (data['text/html'] == html_output) {\n", " return [cell, data, j];\n", " }\n", " }\n", " }\n", " }\n", "}\n", "\n", "// Register the function which deals with the matplotlib target/channel.\n", "// The kernel may be null if the page has been refreshed.\n", "if (IPython.notebook.kernel != null) {\n", " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", "}\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Produce an \"underwater\" or \"drawdown\" chart\n", "drawdown = stats.prices.to_drawdown_series()\n", "drawdown.plot(figsize=(8, 5),logy=False,title='Drawdown')" ] }, { "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": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 2 }