{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Overview\n",
"This notebook demonstrates the proof of concept for the proposed daily notification scheme.\n",
"\n",
"Assumptions:\n",
"- The strategy has been thoroughly backtested and ready for actual trading.\n",
"- Today is Nov 5, 2018, which is trading Day 0."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 1: Initialize data (Day 0)\n",
"- Save the data to disk. This is so the script will only fetch the latest stock data."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"\n",
"from fastquant import backtest, get_stock_data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# Setup our variables\n",
"FILE_DIR = \"jfc.csv\"\n",
"SYMBOL = \"JFC\"\n",
"today = \"2018-11-06\" # Fake today date for demo purposes\n",
"\n",
"df = get_stock_data(SYMBOL, \"2018-01-01\", \"2018-11-05\")\n",
"df.to_csv(FILE_DIR)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Step 2: Daily script calls (Day 1-2)\n",
"1. Fetch today's data\n",
"2. Load data from disk and append today's data\n",
"3. Run backtest with args `live=True` and `today=today`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Demo Day 1: Nov 6, 2018 (buy)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"def daily_fetch(file_dir, symbol, today):\n",
" today_df = get_stock_data(symbol, today, today)\n",
"\n",
" # Retrieve saved historical data on disk and append new data\n",
" # TODO: add checks if daily updates were broken\n",
" df = pd.read_csv(file_dir, parse_dates=[\"dt\"]).set_index(\"dt\")\n",
" # df = df.append(today_df)\n",
" df = pd.concat([df, today_df], ignore_index=True)\n",
" df.to_csv(file_dir)\n",
"\n",
" return df"
]
},
{
"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 : 15\n",
"slow_period : 40\n",
">>> Notif bot: BUY! <<<\n",
"Final Portfolio Value: 97652.8975\n",
"Final PnL: -2347.1\n",
"Time used (seconds): 0.05349397659301758\n",
"Optimal parameters: {'init_cash': 100000, 'buy_prop': 1, 'sell_prop': 1, 'commission': 0.0075, 'execution_type': 'close', 'live': True, 'today': '2018-11-06', 'notif_script_dir': False, 'symbol': '', 'fast_period': 15, 'slow_period': 40}\n",
"Optimal metrics: {'rtot': -0.023750856806590226, 'ravg': -0.00011418681157014532, 'rnorm': -0.028365016583377686, 'rnorm100': -2.8365016583377685, 'sharperatio': None, 'pnl': -2347.1, 'final_value': 97652.8975}\n"
]
},
{
"data": {
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We want\n * to control all of the cursor setting manually through the\n * 'cursor' event from matplotlib */\n event.preventDefault();\n return false;\n}\n\nmpl.figure.prototype._key_event_extra = function(event, name) {\n // Handle any extra behaviour associated with a key event\n}\n\nmpl.figure.prototype.key_event = function(event, name) {\n\n // Prevent repeat events\n if (name == 'key_press')\n {\n if (event.which === this._key)\n return;\n else\n this._key = event.which;\n }\n if (name == 'key_release')\n this._key = null;\n\n var value = '';\n if (event.ctrlKey && event.which != 17)\n value += \"ctrl+\";\n if (event.altKey && event.which != 18)\n value += \"alt+\";\n if (event.shiftKey && event.which != 16)\n value += \"shift+\";\n\n value += 'k';\n value += event.which.toString();\n\n this._key_event_extra(event, name);\n\n this.send_message(name, {key: value,\n guiEvent: simpleKeys(event)});\n return false;\n}\n\nmpl.figure.prototype.toolbar_button_onclick = function(name) {\n if (name == 'download') {\n this.handle_save(this, null);\n } else {\n this.send_message(\"toolbar_button\", {name: name});\n }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n this.message.textContent = tooltip;\n};\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n\nmpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n // Create a \"websocket\"-like object which calls the given IPython comm\n // object with the appropriate methods. Currently this is a non binary\n // socket, so there is still some room for performance tuning.\n var ws = {};\n\n ws.close = function() {\n comm.close()\n };\n ws.send = function(m) {\n //console.log('sending', m);\n comm.send(m);\n };\n // Register the callback with on_msg.\n comm.on_msg(function(msg) {\n //console.log('receiving', msg['content']['data'], msg);\n // Pass the mpl event to the overridden (by mpl) onmessage function.\n ws.onmessage(msg['content']['data'])\n });\n return ws;\n}\n\nmpl.mpl_figure_comm = function(comm, msg) {\n // This is the function which gets called when the mpl process\n // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n var id = msg.content.data.id;\n // Get hold of the div created by the display call when the Comm\n // socket was opened in Python.\n var element = $(\"#\" + id);\n var ws_proxy = comm_websocket_adapter(comm)\n\n function ondownload(figure, format) {\n window.open(figure.imageObj.src);\n }\n\n var fig = new mpl.figure(id, ws_proxy,\n ondownload,\n element.get(0));\n\n // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n // web socket which is closed, not our websocket->open comm proxy.\n ws_proxy.onopen();\n\n fig.parent_element = element.get(0);\n fig.cell_info = mpl.find_output_cell(\"\");\n if (!fig.cell_info) {\n console.error(\"Failed to find cell for figure\", id, fig);\n return;\n }\n\n var output_index = fig.cell_info[2]\n var cell = fig.cell_info[0];\n\n};\n\nmpl.figure.prototype.handle_close = function(fig, msg) {\n var width = fig.canvas.width/mpl.ratio\n fig.root.unbind('remove')\n\n // Update the output cell to use the data from the current canvas.\n fig.push_to_output();\n var dataURL = fig.canvas.toDataURL();\n // Re-enable the keyboard manager in IPython - without this line, in FF,\n // the notebook keyboard shortcuts fail.\n IPython.keyboard_manager.enable()\n $(fig.parent_element).html('');\n fig.close_ws(fig, msg);\n}\n\nmpl.figure.prototype.close_ws = function(fig, msg){\n fig.send_message('closing', msg);\n // fig.ws.close()\n}\n\nmpl.figure.prototype.push_to_output = function(remove_interactive) {\n // Turn the data on the canvas into data in the output cell.\n var width = this.canvas.width/mpl.ratio\n var dataURL = this.canvas.toDataURL();\n this.cell_info[1]['text/html'] = '';\n}\n\nmpl.figure.prototype.updated_canvas_event = function() {\n // Tell IPython that the notebook contents must change.\n IPython.notebook.set_dirty(true);\n this.send_message(\"ack\", {});\n var fig = this;\n // Wait a second, then push the new image to the DOM so\n // that it is saved nicely (might be nice to debounce this).\n setTimeout(function () { fig.push_to_output() }, 1000);\n}\n\nmpl.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) { 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\nmpl.figure.prototype._root_extra_style = function(el){\n var fig = this\n el.on(\"remove\", function(){\n\tfig.close_ws(fig, {});\n });\n}\n\nmpl.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\nmpl.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 // select the cell after this one\n var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n IPython.notebook.select(index + 1);\n }\n}\n\nmpl.figure.prototype.handle_save = function(fig, msg) {\n fig.ondownload(fig, null);\n}\n\n\nmpl.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.\nif (IPython.notebook.kernel != null) {\n IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n}\n",
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