{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# \"backtesting crypto\"\n", "> \"How to fetch and backtest crypto data using fastquant\"\n", "\n", "- toc: true\n", "- branch: master\n", "- badges: true\n", "- comments: true\n", "- author: Jerome de Leon\n", "- categories: [crypto, backtest, grid search]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\"Open" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# uncomment to install in colab\n", "# !pip3 install fastquant --update\n", "# or pip install git+https://www.github.com/enzoampil/fastquant.git@history" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## fetch data from binance" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from fastquant import get_crypto_data\n", "\n", "crypto = get_crypto_data(\"BTC/USDT\", \n", " \"2018-12-01\", \n", " \"2019-12-31\",\n", " time_resolution='1d'\n", " )" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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openhighlowclosevolume
dt
2019-12-277202.007275.867076.427254.7433642.701861
2019-12-287254.777365.017238.677316.1426848.982199
2019-12-297315.367528.457288.007388.2431387.106085
2019-12-307388.437408.247220.007246.0029605.911782
2019-12-317246.007320.007145.017195.2325954.453533
\n", "
" ], "text/plain": [ " open high low close volume\n", "dt \n", "2019-12-27 7202.00 7275.86 7076.42 7254.74 33642.701861\n", "2019-12-28 7254.77 7365.01 7238.67 7316.14 26848.982199\n", "2019-12-29 7315.36 7528.45 7288.00 7388.24 31387.106085\n", "2019-12-30 7388.43 7408.24 7220.00 7246.00 29605.911782\n", "2019-12-31 7246.00 7320.00 7145.01 7195.23 25954.453533" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "crypto.tail()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## run backtest with a grid of values" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 7\n", "slow_period : 30\n", "Final Portfolio Value: 167957.05730000004\n", "Final PnL: 67957.06\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 7\n", "slow_period : 45\n", "Final Portfolio Value: 200109.894525\n", "Final PnL: 100109.89\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 7\n", "slow_period : 60\n", "Final Portfolio Value: 189298.80590000006\n", "Final PnL: 89298.81\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 7\n", "slow_period : 75\n", "Final Portfolio Value: 258316.23405000006\n", "Final PnL: 158316.23\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 14\n", "slow_period : 30\n", "Final Portfolio Value: 161429.22347500004\n", "Final PnL: 61429.22\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 14\n", "slow_period : 45\n", "Final Portfolio Value: 166675.70495000004\n", "Final PnL: 66675.7\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 14\n", "slow_period : 60\n", "Final Portfolio Value: 149527.12537499995\n", "Final PnL: 49527.13\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 14\n", "slow_period : 75\n", "Final Portfolio Value: 229555.53917499998\n", "Final PnL: 129555.54\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 21\n", "slow_period : 30\n", "Final Portfolio Value: 119204.3985\n", "Final PnL: 19204.4\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 21\n", "slow_period : 45\n", "Final Portfolio Value: 162617.28744999995\n", "Final PnL: 62617.29\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 21\n", "slow_period : 60\n", "Final Portfolio Value: 185407.30802499995\n", "Final PnL: 85407.31\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 21\n", "slow_period : 75\n", "Final Portfolio Value: 218637.07270000002\n", "Final PnL: 118637.07\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 28\n", "slow_period : 30\n", "Final Portfolio Value: 99122.65879999999\n", "Final PnL: -877.34\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 28\n", "slow_period : 45\n", "Final Portfolio Value: 200118.49420000007\n", "Final PnL: 100118.49\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 28\n", "slow_period : 60\n", "Final Portfolio Value: 253832.4204\n", "Final PnL: 153832.42\n", "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 28\n", "slow_period : 75\n", "Final Portfolio Value: 215884.7391\n", "Final PnL: 115884.74\n", "Time used (seconds): 1.2722818851470947\n", "Optimal parameters: {'init_cash': 100000, 'buy_prop': 1, 'sell_prop': 1, 'commission': 0.0075, 'execution_type': 'close', 'channel': None, 'symbol': None, 'fast_period': 7, 'slow_period': 75}\n", "Optimal metrics: {'rtot': 0.9490143617322465, 'ravg': 0.002396500913465269, 'rnorm': 0.8292722866407841, 'rnorm100': 82.92722866407841, 'sharperatio': 0.9873670567519415, 'pnl': 158316.23, 'final_value': 258316.23405000006}\n" ] } ], "source": [ "from fastquant import backtest\n", "\n", "results = backtest('smac', \n", " crypto, \n", " fast_period=[7,14,21,28], \n", " slow_period=[30,45,60,75],\n", " plot=False,\n", " verbose=False\n", " )" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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strat_idinit_cashbuy_propsell_propcommissionexecution_typechannelsymbolfast_periodslow_periodrtotravgrnormrnorm100sharperatiopnlfinal_value
03100000110.0075closeNoneNone7750.9490140.0023970.82927282.9272290.987367158316.23258316.234050
114100000110.0075closeNoneNone28600.9315040.0023520.80900280.9002050.986999153832.42253832.420400
27100000110.0075closeNoneNone14750.8309750.0020980.69689869.6898470.984563129555.54229555.539175
311100000110.0075closeNoneNone21750.7822430.0019750.64508364.5083230.983142118637.07218637.072700
415100000110.0075closeNoneNone28750.7695740.0019430.63187463.1874260.982741115884.74215884.739100
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" ], "text/plain": [ " strat_id init_cash buy_prop sell_prop commission execution_type \\\n", "0 3 100000 1 1 0.0075 close \n", "1 14 100000 1 1 0.0075 close \n", "2 7 100000 1 1 0.0075 close \n", "3 11 100000 1 1 0.0075 close \n", "4 15 100000 1 1 0.0075 close \n", "\n", " channel symbol fast_period slow_period rtot ravg rnorm \\\n", "0 None None 7 75 0.949014 0.002397 0.829272 \n", "1 None None 28 60 0.931504 0.002352 0.809002 \n", "2 None None 14 75 0.830975 0.002098 0.696898 \n", "3 None None 21 75 0.782243 0.001975 0.645083 \n", "4 None None 28 75 0.769574 0.001943 0.631874 \n", "\n", " rnorm100 sharperatio pnl final_value \n", "0 82.927229 0.987367 158316.23 258316.234050 \n", "1 80.900205 0.986999 153832.42 253832.420400 \n", "2 69.689847 0.984563 129555.54 229555.539175 \n", "3 64.508323 0.983142 118637.07 218637.072700 \n", "4 63.187426 0.982741 115884.74 215884.739100 " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "results.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "That's a 258% maximum profit using only SMAC because bitcoin was bullish all time long!" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(7, 75)" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#get best parameters on top row \n", "fast_best, slow_best = results.iloc[0][[\"fast_period\",\"slow_period\"]]\n", "fast_best, slow_best" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## run backtest using optimum values" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "import matplotlib as pl\n", "pl.style.use(\"default\")\n", "pl.rcParams[\"figure.figsize\"] = (9,5)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "===Global level arguments===\n", "init_cash : 100000\n", "buy_prop : 1\n", "sell_prop : 1\n", "commission : 0.0075\n", "===Strategy level arguments===\n", "fast_period : 7\n", "slow_period : 75\n", "Final Portfolio Value: 258316.23405000006\n", "Final PnL: 158316.23\n", "Time used (seconds): 0.10248279571533203\n", "Optimal parameters: {'init_cash': 100000, 'buy_prop': 1, 'sell_prop': 1, 'commission': 0.0075, 'execution_type': 'close', 'channel': None, 'symbol': None, 'fast_period': 7, 'slow_period': 75}\n", "Optimal metrics: {'rtot': 0.9490143617322465, 'ravg': 0.002396500913465269, 'rnorm': 0.8292722866407841, 'rnorm100': 82.92722866407841, 'sharperatio': 0.9873670567519415, 'pnl': 158316.23, 'final_value': 258316.23405000006}\n" ] }, { "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 = $('
');\n", " this._root_extra_style(this.root)\n", " this.root.attr('style', 'display: inline-block');\n", "\n", " $(parent_element).append(this.root);\n", "\n", " this._init_header(this);\n", " this._init_canvas(this);\n", " this._init_toolbar(this);\n", "\n", " var fig = this;\n", "\n", " this.waiting = false;\n", "\n", " this.ws.onopen = function () {\n", " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", " fig.send_message(\"send_image_mode\", {});\n", " if (mpl.ratio != 1) {\n", " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", " }\n", " fig.send_message(\"refresh\", {});\n", " }\n", "\n", " this.imageObj.onload = function() {\n", " if (fig.image_mode == 'full') {\n", " // Full images could contain transparency (where diff images\n", " // almost always do), so we need to clear the canvas so that\n", " // there is no ghosting.\n", " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", " }\n", " fig.context.drawImage(fig.imageObj, 0, 0);\n", " };\n", "\n", " this.imageObj.onunload = function() {\n", " fig.ws.close();\n", " }\n", "\n", " this.ws.onmessage = this._make_on_message_function(this);\n", "\n", " this.ondownload = ondownload;\n", "}\n", "\n", "mpl.figure.prototype._init_header = function() {\n", " var titlebar = $(\n", " '
');\n", " var titletext = $(\n", " '
');\n", " titlebar.append(titletext)\n", " this.root.append(titlebar);\n", " this.header = titletext[0];\n", "}\n", "\n", "\n", "\n", "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "\n", "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", "\n", "}\n", "\n", "mpl.figure.prototype._init_canvas = function() {\n", " var fig = this;\n", "\n", " var canvas_div = $('
');\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 = $('