pandas-ta/examples/AIExample.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TA Analysis with **Pandas TA** and AI/ML\n",
    "* This is a **Work in Progress** and subject to change!\n",
    "* Contributions are welcome and accepted!\n",
    "* Examples below are for **educational purposes only**.\n",
    "* **NOTE:** The **watchlist** module is independent of Pandas TA. To easily use it, copy it from your local pandas_ta installation directory into your project directory."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Required Packages\n",
    "##### Uncomment the packages you need to install or are missing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install numpy\n",
    "#!pip install pandas\n",
    "#!pip install mplfinance\n",
    "#!pip install pandas-datareader\n",
    "#!pip install requests_cache\n",
    "#!pip install tqdm\n",
    "#!pip install alphaVantage-api # Required for Watchlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n",
      "Numpy v1.20.3\n",
      "Pandas v1.3.0\n",
      "mplfinance v0.12.7a17\n",
      "\n",
      "Pandas TA v0.3.32b0\n",
      "To install the Latest Version:\n",
      "$ pip install -U git+https://github.com/twopirllc/pandas-ta\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "import datetime as dt\n",
    "import random as rnd\n",
    "from sys import float_info as sflt\n",
    "\n",
    "from tqdm import tqdm\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "pd.set_option(\"max_rows\", 100)\n",
    "pd.set_option(\"max_columns\", 20)\n",
    "\n",
    "import mplfinance as mpf\n",
    "import pandas_ta as ta\n",
    "\n",
    "from tqdm.notebook import trange, tqdm\n",
    "\n",
    "from watchlist import colors, Watchlist # Is this failing? If so, copy it locally. See above.\n",
    "\n",
    "print(f\"Numpy v{np.__version__}\")\n",
    "print(f\"Pandas v{pd.__version__}\")\n",
    "print(f\"mplfinance v{mpf.__version__}\")\n",
    "print(f\"\\nPandas TA v{ta.version}\\nTo install the Latest Version:\\n$ pip install -U git+https://github.com/twopirllc/pandas-ta\\n\")\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MISC Function(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def recent_bars(df, tf: str = \"1y\"):\n",
    "    # All Data: 0, Last Four Years: 0.25, Last Two Years: 0.5, This Year: 1, Last Half Year: 2, Last Quarter: 4\n",
    "    yearly_divisor = {\"all\": 0, \"10y\": 0.1, \"5y\": 0.2, \"4y\": 0.25, \"3y\": 1./3, \"2y\": 0.5, \"1y\": 1, \"6mo\": 2, \"3mo\": 4}\n",
    "    yd = yearly_divisor[tf] if tf in yearly_divisor.keys() else 0\n",
    "    return int(ta.RATE[\"TRADING_DAYS_PER_YEAR\"] / yd) if yd > 0 else df.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Collection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[!] Loading All: SPY, QQQ, AAPL, TSLA, BTC-USD\n",
      "[+] Downloading[yahoo]: SPY[D]\n",
      "[+] Saving: /Users/kj/av_data/SPY_D.csv\n",
      "[i] Runtime: 707.3915 ms (0.7074 s)\n",
      "[+] Downloading[yahoo]: QQQ[D]\n",
      "[+] Saving: /Users/kj/av_data/QQQ_D.csv\n",
      "[i] Runtime: 696.6895 ms (0.6967 s)\n",
      "[+] Downloading[yahoo]: AAPL[D]\n",
      "[+] Saving: /Users/kj/av_data/AAPL_D.csv\n",
      "[i] Runtime: 856.9906 ms (0.8570 s)\n",
      "[+] Downloading[yahoo]: TSLA[D]\n",
      "[+] Saving: /Users/kj/av_data/TSLA_D.csv\n",
      "[i] Runtime: 719.1806 ms (0.7192 s)\n",
      "[+] Downloading[yahoo]: BTC-USD[D]\n",
      "[+] Saving: /Users/kj/av_data/BTC-USD_D.csv\n",
      "[i] Runtime: 811.2178 ms (0.8112 s)\n"
     ]
    }
   ],
   "source": [
    "tf = \"D\"\n",
    "tickers = [\"SPY\", \"QQQ\", \"AAPL\", \"TSLA\", \"BTC-USD\"]\n",
    "watch = Watchlist(tickers, tf=tf, ds_name=\"yahoo\", timed=True)\n",
    "# watch.study = ta.CommonStudy # If you have a Custom Study, you can use it here.\n",
    "watch.load(tickers, analyze=True, verbose=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Asset Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SPY (7299, 12)\n",
      "Columns: open, high, low, close, volume, dividends, stock splits, SMA_10, SMA_20, SMA_50, SMA_200, VOL_SMA_20\n"
     ]
    }
   ],
   "source": [
    "ticker = tickers[0] # change tickers by changing the index\n",
    "print(f\"{ticker} {watch.data[ticker].shape}\\nColumns: {', '.join(list(watch.data[ticker].columns))}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trim it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>stock splits</th>\n",
       "      <th>sma_10</th>\n",
       "      <th>sma_20</th>\n",
       "      <th>sma_50</th>\n",
       "      <th>sma_200</th>\n",
       "      <th>vol_sma_20</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-01-25</th>\n",
       "      <td>378.623058</td>\n",
       "      <td>379.708564</td>\n",
       "      <td>373.481570</td>\n",
       "      <td>379.333588</td>\n",
       "      <td>70402000</td>\n",
       "      <td>0</td>\n",
       "      <td>375.540128</td>\n",
       "      <td>371.941592</td>\n",
       "      <td>363.642487</td>\n",
       "      <td>325.851111</td>\n",
       "      <td>63120030.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-26</th>\n",
       "      <td>380.340140</td>\n",
       "      <td>380.774354</td>\n",
       "      <td>378.494744</td>\n",
       "      <td>378.741455</td>\n",
       "      <td>42665300</td>\n",
       "      <td>0</td>\n",
       "      <td>376.043420</td>\n",
       "      <td>372.671364</td>\n",
       "      <td>364.207632</td>\n",
       "      <td>326.389357</td>\n",
       "      <td>63930400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-27</th>\n",
       "      <td>375.218403</td>\n",
       "      <td>375.317093</td>\n",
       "      <td>367.116410</td>\n",
       "      <td>369.484833</td>\n",
       "      <td>123351100</td>\n",
       "      <td>0</td>\n",
       "      <td>375.613156</td>\n",
       "      <td>372.781891</td>\n",
       "      <td>364.655645</td>\n",
       "      <td>326.893695</td>\n",
       "      <td>68147935.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-28</th>\n",
       "      <td>371.409193</td>\n",
       "      <td>376.905930</td>\n",
       "      <td>370.945404</td>\n",
       "      <td>372.662506</td>\n",
       "      <td>94198100</td>\n",
       "      <td>0</td>\n",
       "      <td>375.400000</td>\n",
       "      <td>373.086334</td>\n",
       "      <td>365.071107</td>\n",
       "      <td>327.374311</td>\n",
       "      <td>70173815.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-29</th>\n",
       "      <td>370.688763</td>\n",
       "      <td>371.715090</td>\n",
       "      <td>363.425564</td>\n",
       "      <td>365.201904</td>\n",
       "      <td>126765100</td>\n",
       "      <td>0</td>\n",
       "      <td>374.572037</td>\n",
       "      <td>372.991595</td>\n",
       "      <td>365.249507</td>\n",
       "      <td>327.847003</td>\n",
       "      <td>74039305.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-14</th>\n",
       "      <td>461.190002</td>\n",
       "      <td>465.089996</td>\n",
       "      <td>459.899994</td>\n",
       "      <td>464.720001</td>\n",
       "      <td>95849600</td>\n",
       "      <td>0</td>\n",
       "      <td>469.319998</td>\n",
       "      <td>469.606500</td>\n",
       "      <td>465.989207</td>\n",
       "      <td>438.476059</td>\n",
       "      <td>78776895.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-18</th>\n",
       "      <td>459.739990</td>\n",
       "      <td>459.959991</td>\n",
       "      <td>455.309998</td>\n",
       "      <td>456.489990</td>\n",
       "      <td>109709100</td>\n",
       "      <td>0</td>\n",
       "      <td>467.197998</td>\n",
       "      <td>469.437500</td>\n",
       "      <td>465.813499</td>\n",
       "      <td>438.746869</td>\n",
       "      <td>77486770.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-19</th>\n",
       "      <td>458.130005</td>\n",
       "      <td>459.609985</td>\n",
       "      <td>451.459991</td>\n",
       "      <td>451.750000</td>\n",
       "      <td>109357600</td>\n",
       "      <td>0</td>\n",
       "      <td>464.617999</td>\n",
       "      <td>469.275999</td>\n",
       "      <td>465.510704</td>\n",
       "      <td>438.995168</td>\n",
       "      <td>77597910.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-20</th>\n",
       "      <td>453.750000</td>\n",
       "      <td>458.739990</td>\n",
       "      <td>444.500000</td>\n",
       "      <td>446.750000</td>\n",
       "      <td>122379700</td>\n",
       "      <td>0</td>\n",
       "      <td>462.454999</td>\n",
       "      <td>468.460500</td>\n",
       "      <td>465.099938</td>\n",
       "      <td>439.216139</td>\n",
       "      <td>80226580.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-21</th>\n",
       "      <td>445.559998</td>\n",
       "      <td>448.059998</td>\n",
       "      <td>437.950012</td>\n",
       "      <td>437.980011</td>\n",
       "      <td>201913500</td>\n",
       "      <td>0</td>\n",
       "      <td>459.459000</td>\n",
       "      <td>466.975000</td>\n",
       "      <td>464.544664</td>\n",
       "      <td>439.383707</td>\n",
       "      <td>87377745.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  open        high         low       close     volume  \\\n",
       "date                                                                    \n",
       "2021-01-25  378.623058  379.708564  373.481570  379.333588   70402000   \n",
       "2021-01-26  380.340140  380.774354  378.494744  378.741455   42665300   \n",
       "2021-01-27  375.218403  375.317093  367.116410  369.484833  123351100   \n",
       "2021-01-28  371.409193  376.905930  370.945404  372.662506   94198100   \n",
       "2021-01-29  370.688763  371.715090  363.425564  365.201904  126765100   \n",
       "...                ...         ...         ...         ...        ...   \n",
       "2022-01-14  461.190002  465.089996  459.899994  464.720001   95849600   \n",
       "2022-01-18  459.739990  459.959991  455.309998  456.489990  109709100   \n",
       "2022-01-19  458.130005  459.609985  451.459991  451.750000  109357600   \n",
       "2022-01-20  453.750000  458.739990  444.500000  446.750000  122379700   \n",
       "2022-01-21  445.559998  448.059998  437.950012  437.980011  201913500   \n",
       "\n",
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "date                                                                       \n",
       "2021-01-25             0  375.540128  371.941592  363.642487  325.851111   \n",
       "2021-01-26             0  376.043420  372.671364  364.207632  326.389357   \n",
       "2021-01-27             0  375.613156  372.781891  364.655645  326.893695   \n",
       "2021-01-28             0  375.400000  373.086334  365.071107  327.374311   \n",
       "2021-01-29             0  374.572037  372.991595  365.249507  327.847003   \n",
       "...                  ...         ...         ...         ...         ...   \n",
       "2022-01-14             0  469.319998  469.606500  465.989207  438.476059   \n",
       "2022-01-18             0  467.197998  469.437500  465.813499  438.746869   \n",
       "2022-01-19             0  464.617999  469.275999  465.510704  438.995168   \n",
       "2022-01-20             0  462.454999  468.460500  465.099938  439.216139   \n",
       "2022-01-21             0  459.459000  466.975000  464.544664  439.383707   \n",
       "\n",
       "            vol_sma_20  \n",
       "date                    \n",
       "2021-01-25  63120030.0  \n",
       "2021-01-26  63930400.0  \n",
       "2021-01-27  68147935.0  \n",
       "2021-01-28  70173815.0  \n",
       "2021-01-29  74039305.0  \n",
       "...                ...  \n",
       "2022-01-14  78776895.0  \n",
       "2022-01-18  77486770.0  \n",
       "2022-01-19  77597910.0  \n",
       "2022-01-20  80226580.0  \n",
       "2022-01-21  87377745.0  \n",
       "\n",
       "[252 rows x 11 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duration = \"1y\"\n",
    "asset = watch.data[ticker]\n",
    "recent = recent_bars(asset, duration)\n",
    "asset.columns = asset.columns.str.lower()\n",
    "asset.drop(columns=[\"dividends\", \"split\"], errors=\"ignore\", inplace=True)\n",
    "asset = asset.copy().tail(recent)\n",
    "asset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Trend Creation\n",
    "A **Trend** is the result of some calculation or condition of one or more indicators. For simplicity, a _Trend_ is either ```True``` or ```1``` and _No Trend_ is ```False``` or ```0```. Using the **Hello World** of Trends, the **Golden/Death Cross**, it's Trend is _Long_ when ```long = ma(close, 50) > ma(close, 200) ``` and _Short_ when ```short = ma(close, 50) < ma(close, 200) ```. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TA Columns Added:\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>stock splits</th>\n",
       "      <th>sma_10</th>\n",
       "      <th>sma_20</th>\n",
       "      <th>sma_50</th>\n",
       "      <th>sma_200</th>\n",
       "      <th>vol_sma_20</th>\n",
       "      <th>EMA_8</th>\n",
       "      <th>EMA_21</th>\n",
       "      <th>EMA_50</th>\n",
       "      <th>PCTRET_1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-14</th>\n",
       "      <td>0</td>\n",
       "      <td>469.319998</td>\n",
       "      <td>469.606500</td>\n",
       "      <td>465.989207</td>\n",
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       "      <td>467.864562</td>\n",
       "      <td>468.366344</td>\n",
       "      <td>464.226269</td>\n",
       "      <td>0.000409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-18</th>\n",
       "      <td>0</td>\n",
       "      <td>467.197998</td>\n",
       "      <td>469.437500</td>\n",
       "      <td>465.813499</td>\n",
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       "      <td>77486770.0</td>\n",
       "      <td>465.336880</td>\n",
       "      <td>467.286675</td>\n",
       "      <td>463.922886</td>\n",
       "      <td>-0.017710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-19</th>\n",
       "      <td>0</td>\n",
       "      <td>464.617999</td>\n",
       "      <td>469.275999</td>\n",
       "      <td>465.510704</td>\n",
       "      <td>438.995168</td>\n",
       "      <td>77597910.0</td>\n",
       "      <td>462.317573</td>\n",
       "      <td>465.874250</td>\n",
       "      <td>463.445517</td>\n",
       "      <td>-0.010384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-20</th>\n",
       "      <td>0</td>\n",
       "      <td>462.454999</td>\n",
       "      <td>468.460500</td>\n",
       "      <td>465.099938</td>\n",
       "      <td>439.216139</td>\n",
       "      <td>80226580.0</td>\n",
       "      <td>458.858112</td>\n",
       "      <td>464.135682</td>\n",
       "      <td>462.790791</td>\n",
       "      <td>-0.011068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-21</th>\n",
       "      <td>0</td>\n",
       "      <td>459.459000</td>\n",
       "      <td>466.975000</td>\n",
       "      <td>464.544664</td>\n",
       "      <td>439.383707</td>\n",
       "      <td>87377745.0</td>\n",
       "      <td>454.218534</td>\n",
       "      <td>461.757894</td>\n",
       "      <td>461.817820</td>\n",
       "      <td>-0.019631</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "date                                                                       \n",
       "2022-01-14             0  469.319998  469.606500  465.989207  438.476059   \n",
       "2022-01-18             0  467.197998  469.437500  465.813499  438.746869   \n",
       "2022-01-19             0  464.617999  469.275999  465.510704  438.995168   \n",
       "2022-01-20             0  462.454999  468.460500  465.099938  439.216139   \n",
       "2022-01-21             0  459.459000  466.975000  464.544664  439.383707   \n",
       "\n",
       "            vol_sma_20       EMA_8      EMA_21      EMA_50  PCTRET_1  \n",
       "date                                                                  \n",
       "2022-01-14  78776895.0  467.864562  468.366344  464.226269  0.000409  \n",
       "2022-01-18  77486770.0  465.336880  467.286675  463.922886 -0.017710  \n",
       "2022-01-19  77597910.0  462.317573  465.874250  463.445517 -0.010384  \n",
       "2022-01-20  80226580.0  458.858112  464.135682  462.790791 -0.011068  \n",
       "2022-01-21  87377745.0  454.218534  461.757894  461.817820 -0.019631  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Example Long Trends\n",
    "# long = ta.sma(asset.close, 50) > ta.sma(asset.close, 200) # SMA(50) > SMA(200) \"Golden/Death Cross\"\n",
    "# long = ta.sma(asset.close, 10) > ta.sma(asset.close, 20) # SMA(10) > SMA(20)\n",
    "long = ta.ema(asset.close, 8) > ta.ema(asset.close, 21) # EMA(8) > EMA(21)\n",
    "# long = ta.increasing(ta.ema(asset.close, 50))\n",
    "# long = ta.macd(asset.close).iloc[:,1] > 0 # MACD Histogram is positive\n",
    "# long = ta.amat(asset.close, 50, 200).AMATe_LR_2  # Long Run of AMAT(50, 200) with lookback of 2 bars\n",
    "\n",
    "# long &= ta.increasing(ta.ema(asset.close, 50), 2) # Uncomment for further long restrictions, in this case when EMA(50) is increasing/sloping upwards\n",
    "# long = 1 - long # uncomment to create a short signal of the trend\n",
    "\n",
    "asset.ta.ema(length=8, sma=False, append=True)\n",
    "asset.ta.ema(length=21, sma=False, append=True)\n",
    "asset.ta.ema(length=50, sma=False, append=True)\n",
    "asset.ta.percent_return(append=True)\n",
    "print(\"TA Columns Added:\")\n",
    "asset[asset.columns[5:]].tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Trend Signals** \n",
    "Given a _Trend_, **Trend Signals** returns the _Trend_, _Trades_, _Entries_ and _Exits_ as boolean integers. When ```asbool=True```, it returns _Trends_, _Entries_ and _Exits_ as boolean values which is helpful when combined with the [**vectorbt**](https://github.com/polakowo/vectorbt) backtesting package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TS_Trends</th>\n",
       "      <th>TS_Trades</th>\n",
       "      <th>TS_Entries</th>\n",
       "      <th>TS_Exits</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-14</th>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-18</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-19</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-20</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-21</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            TS_Trends  TS_Trades  TS_Entries  TS_Exits\n",
       "date                                                  \n",
       "2022-01-14          0         -1           0         1\n",
       "2022-01-18          0          0           0         0\n",
       "2022-01-19          0          0           0         0\n",
       "2022-01-20          0          0           0         0\n",
       "2022-01-21          0          0           0         0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trendy = asset.ta.tsignals(long, asbool=False, append=True)\n",
    "trendy.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trend Entries & Exits & Trade Table\n",
    "This is a simple way to reduce the Asset DataFrame to a Trade Table with Dates, Signals, and Entries and Exits. Gives you an idea what to expect before running through a backtester such as [**vectorbt**](https://github.com/polakowo/vectorbt)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Trades Total | Round Trip:\t12 | 6\n",
      "Trade Coverage: 77.78%\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Signal</th>\n",
       "      <th>Entry</th>\n",
       "      <th>Exit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-02-23</th>\n",
       "      <td>1</td>\n",
       "      <td>382.402618</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-04</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>371.744690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-10</th>\n",
       "      <td>1</td>\n",
       "      <td>384.455292</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-19</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>406.783295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-20</th>\n",
       "      <td>1</td>\n",
       "      <td>411.159454</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-17</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>439.854675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-15</th>\n",
       "      <td>1</td>\n",
       "      <td>444.309021</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-01</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>448.922821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-08</th>\n",
       "      <td>1</td>\n",
       "      <td>467.876221</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-20</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>454.980011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-21</th>\n",
       "      <td>1</td>\n",
       "      <td>463.059998</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-14</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>464.720001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Signal       Entry        Exit\n",
       "date                                      \n",
       "2021-02-23       1  382.402618         NaN\n",
       "2021-03-04      -1         NaN  371.744690\n",
       "2021-03-10       1  384.455292         NaN\n",
       "2021-05-19      -1         NaN  406.783295\n",
       "2021-05-20       1  411.159454         NaN\n",
       "2021-09-17      -1         NaN  439.854675\n",
       "2021-10-15       1  444.309021         NaN\n",
       "2021-12-01      -1         NaN  448.922821\n",
       "2021-12-08       1  467.876221         NaN\n",
       "2021-12-20      -1         NaN  454.980011\n",
       "2021-12-21       1  463.059998         NaN\n",
       "2022-01-14      -1         NaN  464.720001"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entries = trendy.TS_Entries * asset.close\n",
    "entries = entries[~np.isclose(entries, 0)]\n",
    "entries.dropna(inplace=True)\n",
    "entries.name = \"Entry\"\n",
    "\n",
    "exits = trendy.TS_Exits * asset.close\n",
    "exits = exits[~np.isclose(exits, 0)]\n",
    "exits.dropna(inplace=True)\n",
    "exits.name = \"Exit\"\n",
    "\n",
    "total_trades = trendy.TS_Trades.abs().sum()\n",
    "rt_trades = int(trendy.TS_Trades.abs().sum() // 2)\n",
    "\n",
    "all_trades = trendy.TS_Trades.copy().fillna(0)\n",
    "all_trades = all_trades[all_trades != 0]\n",
    "\n",
    "trades = pd.DataFrame({\n",
    "    \"Signal\": all_trades,\n",
    "    entries.name: entries,\n",
    "    exits.name: exits\n",
    "})\n",
    "\n",
    "# Show some stats if there is an active trade (when there is an odd number of round trip trades)\n",
    "if total_trades % 2 != 0:\n",
    "    unrealized_pnl = asset.close.iloc[-1] - entries.iloc[-1]\n",
    "    unrealized_pnl_pct_change = 100 * ((asset.close.iloc[-1] / entries.iloc[-1]) - 1)\n",
    "    print(\"Current Trade:\")\n",
    "    print(f\"Price Entry | Last:\\t{entries.iloc[-1]:.4f} | {asset.close.iloc[-1]:.4f}\")\n",
    "    print(f\"Unrealized PnL | %:\\t{unrealized_pnl:.4f} | {unrealized_pnl_pct_change:.4f}%\")\n",
    "print(f\"\\nTrades Total | Round Trip:\\t{total_trades} | {rt_trades}\")\n",
    "print(f\"Trade Coverage: {100 * asset.TS_Trends.sum() / asset.shape[0]:.2f}%\")\n",
    "\n",
    "trades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Chart Display Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "extime = ta.get_time(to_string=True)\n",
    "first_date, last_date = asset.index[0], asset.index[-1]\n",
    "f_date = f\"{first_date.day_name()} {first_date.month}-{first_date.day}-{first_date.year}\"\n",
    "l_date = f\"{last_date.day_name()} {last_date.month}-{last_date.day}-{last_date.year}\"\n",
    "last_ohlcv = f\"Last OHLCV: ({asset.iloc[-1].open:.4f}, {asset.iloc[-1].high:.4f}, {asset.iloc[-1].low:.4f}, {asset.iloc[-1].close:.4f}, {int(asset.iloc[-1].volume)})\"\n",
    "ptitle = f\"\\n{ticker} [{tf} for {duration}({recent} bars)] from {f_date} to {l_date}\\n{last_ohlcv}\\n{extime}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trade Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'\\nSPY [D for 1y(252 bars)] from Monday 1-25-2021 to Friday 1-21-2022\\nLast OHLCV: (445.5600, 448.0600, 437.9500, 437.9800, 201913500)\\nSunday January 23, 2022, NYSE: 11:44:28, Local: 15:44:28 PST, Day 23/365 (6.00%)'}, xlabel='date'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# chart = asset[\"close\"] #asset[[\"close\", \"SMA_10\", \"SMA_20\", \"SMA_50\", \"SMA_200\"]]\n",
    "# chart = asset[[\"close\", \"SMA_10\", \"SMA_20\"]]\n",
    "chart = asset[[\"close\", \"EMA_8\", \"EMA_21\", \"EMA_50\"]]\n",
    "chart.plot(figsize=(16, 10), color=colors(\"BkGrOrRd\"), title=ptitle, grid=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Long and Short Trends\n",
    "**Trends** are either a _Trend_ (```1```) or _No Trend_ (```0```) depending on the **Trend** passed into ***Trend Signals**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x61.2 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "long_trend = trendy.TS_Trends\n",
    "short_trend = 1 - long_trend\n",
    "\n",
    "long_trend.plot(figsize=(16, 0.85), kind=\"area\", stacked=True, color=colors()[0], alpha=0.25) # Green Area\n",
    "short_trend.plot(figsize=(16, 0.85), kind=\"area\", stacked=True, color=colors()[1], alpha=0.25) # Red Area"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trades or Trade Signals\n",
    "The **Trades** are either _Enter_ (```1```) or _Exit_ (```-1```) or _No Position/Action_ (```0```). These are based on the **Trend** passed into **Trend Signals** whether they are _Long_ or _Short_ Trends."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x108 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "trendy.TS_Trades.plot(figsize=(16, 1.5), color=colors(\"BkBl\")[0], grid=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Active Returns\n",
    "**Active Returns** are returns made during the course of the _Trend_. They are simply the product of the returns and the _Trend_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x130230a60>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "asset[\"ACTRET_1\"] = trendy.TS_Trends.shift(1) * asset.PCTRET_1\n",
    "asset[[\"PCTRET_1\", \"ACTRET_1\"]].plot(figsize=(16, 3), color=colors(\"GyOr\"), alpha=1, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Buy and Hold Returns (*PCTRET_1*) vs. Cum. Active Returns (*ACTRET_1*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x1304c2610>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "((asset[[\"PCTRET_1\", \"ACTRET_1\"]] + 1).cumprod() - 1).plot(figsize=(16, 3), kind=\"area\", stacked=False, color=colors(\"GyOr\"), title=\"B&H vs. Cum. Active Returns\", alpha=.4, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Disclaimer\n",
    "* All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.\n",
    "\n",
    "* Any opinions, news, research, analyses, prices, or other information offered is provided as general market commentary, and does not constitute investment advice. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from use of or reliance on such information."
   ]
  },
  {
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