pandas-ta/examples/AIExample.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Strategy 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",
      "[i] Loaded SPY[D]: SPY_D.csv\n",
      "[i] Runtime: 736.1327 ms (0.7361 s)\n",
      "[+] Downloading[yahoo]: QQQ[D]\n",
      "[+] Saving: /Users/kj/av_data/QQQ_D.csv\n",
      "[i] Runtime: 697.6427 ms (0.6976 s)\n",
      "[+] Downloading[yahoo]: AAPL[D]\n",
      "[+] Saving: /Users/kj/av_data/AAPL_D.csv\n",
      "[i] Runtime: 679.9694 ms (0.6800 s)\n",
      "[+] Downloading[yahoo]: TSLA[D]\n",
      "[+] Saving: /Users/kj/av_data/TSLA_D.csv\n",
      "[i] Runtime: 738.0908 ms (0.7381 s)\n",
      "[+] Downloading[yahoo]: BTC-USD[D]\n",
      "[+] Saving: /Users/kj/av_data/BTC-USD_D.csv\n",
      "[i] Runtime: 755.3894 ms (0.7554 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.strategy = ta.CommonStrategy # If you have a Custom Strategy, 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": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AAPL (10361, 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[2] # 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": 17,
   "metadata": {},
   "outputs": [
    {
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       "  <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",
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       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-01-15</th>\n",
       "      <td>127.990959</td>\n",
       "      <td>129.422138</td>\n",
       "      <td>126.221866</td>\n",
       "      <td>126.361008</td>\n",
       "      <td>111598500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>128.677734</td>\n",
       "      <td>129.754095</td>\n",
       "      <td>123.478919</td>\n",
       "      <td>103.135757</td>\n",
       "      <td>1.127449e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-19</th>\n",
       "      <td>126.997087</td>\n",
       "      <td>127.921397</td>\n",
       "      <td>126.162237</td>\n",
       "      <td>127.046783</td>\n",
       "      <td>90757300</td>\n",
       "      <td>0.0</td>\n",
       "      <td>128.520701</td>\n",
       "      <td>129.710862</td>\n",
       "      <td>123.738876</td>\n",
       "      <td>103.468593</td>\n",
       "      <td>1.125648e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-20</th>\n",
       "      <td>127.871707</td>\n",
       "      <td>131.678242</td>\n",
       "      <td>127.762380</td>\n",
       "      <td>131.221054</td>\n",
       "      <td>104319500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>128.622076</td>\n",
       "      <td>129.977717</td>\n",
       "      <td>124.001358</td>\n",
       "      <td>103.826647</td>\n",
       "      <td>1.081537e+08</td>\n",
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       "    <tr>\n",
       "      <th>2021-01-21</th>\n",
       "      <td>132.980205</td>\n",
       "      <td>138.814235</td>\n",
       "      <td>132.771485</td>\n",
       "      <td>136.031387</td>\n",
       "      <td>120150900</td>\n",
       "      <td>0.0</td>\n",
       "      <td>129.642783</td>\n",
       "      <td>130.407070</td>\n",
       "      <td>124.362730</td>\n",
       "      <td>104.182751</td>\n",
       "      <td>1.080986e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-22</th>\n",
       "      <td>135.445012</td>\n",
       "      <td>138.993146</td>\n",
       "      <td>134.192737</td>\n",
       "      <td>138.217926</td>\n",
       "      <td>114459400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>130.452789</td>\n",
       "      <td>130.764368</td>\n",
       "      <td>124.814942</td>\n",
       "      <td>104.553542</td>\n",
       "      <td>1.053764e+08</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",
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       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>172.889999</td>\n",
       "      <td>174.139999</td>\n",
       "      <td>171.029999</td>\n",
       "      <td>172.169998</td>\n",
       "      <td>86580100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>177.556999</td>\n",
       "      <td>176.122500</td>\n",
       "      <td>164.787658</td>\n",
       "      <td>145.042709</td>\n",
       "      <td>1.032868e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>169.080002</td>\n",
       "      <td>172.500000</td>\n",
       "      <td>168.169998</td>\n",
       "      <td>172.190002</td>\n",
       "      <td>106765600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>176.742999</td>\n",
       "      <td>175.759500</td>\n",
       "      <td>165.184505</td>\n",
       "      <td>145.300422</td>\n",
       "      <td>1.028636e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-11</th>\n",
       "      <td>172.320007</td>\n",
       "      <td>175.179993</td>\n",
       "      <td>170.820007</td>\n",
       "      <td>175.080002</td>\n",
       "      <td>76138300</td>\n",
       "      <td>0.0</td>\n",
       "      <td>176.322000</td>\n",
       "      <td>175.726500</td>\n",
       "      <td>165.694471</td>\n",
       "      <td>145.571689</td>\n",
       "      <td>9.900872e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-12</th>\n",
       "      <td>176.119995</td>\n",
       "      <td>177.179993</td>\n",
       "      <td>174.820007</td>\n",
       "      <td>175.529999</td>\n",
       "      <td>74711100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>175.937000</td>\n",
       "      <td>175.786500</td>\n",
       "      <td>166.230213</td>\n",
       "      <td>145.852622</td>\n",
       "      <td>9.577525e+07</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-13</th>\n",
       "      <td>175.779999</td>\n",
       "      <td>176.619995</td>\n",
       "      <td>174.529999</td>\n",
       "      <td>175.199997</td>\n",
       "      <td>29711051</td>\n",
       "      <td>0.0</td>\n",
       "      <td>175.637000</td>\n",
       "      <td>175.581499</td>\n",
       "      <td>166.738185</td>\n",
       "      <td>146.120707</td>\n",
       "      <td>9.070764e+07</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",
       "2021-01-15  127.990959  129.422138  126.221866  126.361008  111598500   \n",
       "2021-01-19  126.997087  127.921397  126.162237  127.046783   90757300   \n",
       "2021-01-20  127.871707  131.678242  127.762380  131.221054  104319500   \n",
       "2021-01-21  132.980205  138.814235  132.771485  136.031387  120150900   \n",
       "2021-01-22  135.445012  138.993146  134.192737  138.217926  114459400   \n",
       "...                ...         ...         ...         ...        ...   \n",
       "2022-01-07  172.889999  174.139999  171.029999  172.169998   86580100   \n",
       "2022-01-10  169.080002  172.500000  168.169998  172.190002  106765600   \n",
       "2022-01-11  172.320007  175.179993  170.820007  175.080002   76138300   \n",
       "2022-01-12  176.119995  177.179993  174.820007  175.529999   74711100   \n",
       "2022-01-13  175.779999  176.619995  174.529999  175.199997   29711051   \n",
       "\n",
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "Date                                                                       \n",
       "2021-01-15           0.0  128.677734  129.754095  123.478919  103.135757   \n",
       "2021-01-19           0.0  128.520701  129.710862  123.738876  103.468593   \n",
       "2021-01-20           0.0  128.622076  129.977717  124.001358  103.826647   \n",
       "2021-01-21           0.0  129.642783  130.407070  124.362730  104.182751   \n",
       "2021-01-22           0.0  130.452789  130.764368  124.814942  104.553542   \n",
       "...                  ...         ...         ...         ...         ...   \n",
       "2022-01-07           0.0  177.556999  176.122500  164.787658  145.042709   \n",
       "2022-01-10           0.0  176.742999  175.759500  165.184505  145.300422   \n",
       "2022-01-11           0.0  176.322000  175.726500  165.694471  145.571689   \n",
       "2022-01-12           0.0  175.937000  175.786500  166.230213  145.852622   \n",
       "2022-01-13           0.0  175.637000  175.581499  166.738185  146.120707   \n",
       "\n",
       "              vol_sma_20  \n",
       "Date                      \n",
       "2021-01-15  1.127449e+08  \n",
       "2021-01-19  1.125648e+08  \n",
       "2021-01-20  1.081537e+08  \n",
       "2021-01-21  1.080986e+08  \n",
       "2021-01-22  1.053764e+08  \n",
       "...                  ...  \n",
       "2022-01-07  1.032868e+08  \n",
       "2022-01-10  1.028636e+08  \n",
       "2022-01-11  9.900872e+07  \n",
       "2022-01-12  9.577525e+07  \n",
       "2022-01-13  9.070764e+07  \n",
       "\n",
       "[252 rows x 11 columns]"
      ]
     },
     "execution_count": 17,
     "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": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TA Columns Added:\n"
     ]
    },
    {
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       "  <thead>\n",
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       "      <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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       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>0.0</td>\n",
       "      <td>177.556999</td>\n",
       "      <td>176.122500</td>\n",
       "      <td>164.787658</td>\n",
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       "      <td>175.550651</td>\n",
       "      <td>174.090649</td>\n",
       "      <td>166.893160</td>\n",
       "      <td>0.000988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>0.0</td>\n",
       "      <td>176.742999</td>\n",
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       "      <td>167.100879</td>\n",
       "      <td>0.000116</td>\n",
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       "    <tr>\n",
       "      <th>2022-01-11</th>\n",
       "      <td>0.0</td>\n",
       "      <td>176.322000</td>\n",
       "      <td>175.726500</td>\n",
       "      <td>165.694471</td>\n",
       "      <td>145.571689</td>\n",
       "      <td>9.900872e+07</td>\n",
       "      <td>174.865210</td>\n",
       "      <td>174.023512</td>\n",
       "      <td>167.413786</td>\n",
       "      <td>0.016784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-12</th>\n",
       "      <td>0.0</td>\n",
       "      <td>175.937000</td>\n",
       "      <td>175.786500</td>\n",
       "      <td>166.230213</td>\n",
       "      <td>145.852622</td>\n",
       "      <td>9.577525e+07</td>\n",
       "      <td>175.012941</td>\n",
       "      <td>174.160465</td>\n",
       "      <td>167.732069</td>\n",
       "      <td>0.002570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-13</th>\n",
       "      <td>0.0</td>\n",
       "      <td>175.637000</td>\n",
       "      <td>175.581499</td>\n",
       "      <td>166.738185</td>\n",
       "      <td>146.120707</td>\n",
       "      <td>9.070764e+07</td>\n",
       "      <td>175.054509</td>\n",
       "      <td>174.254968</td>\n",
       "      <td>168.024929</td>\n",
       "      <td>-0.001880</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "Date                                                                       \n",
       "2022-01-07           0.0  177.556999  176.122500  164.787658  145.042709   \n",
       "2022-01-10           0.0  176.742999  175.759500  165.184505  145.300422   \n",
       "2022-01-11           0.0  176.322000  175.726500  165.694471  145.571689   \n",
       "2022-01-12           0.0  175.937000  175.786500  166.230213  145.852622   \n",
       "2022-01-13           0.0  175.637000  175.581499  166.738185  146.120707   \n",
       "\n",
       "              vol_sma_20       EMA_8      EMA_21      EMA_50  PCTRET_1  \n",
       "Date                                                                    \n",
       "2022-01-07  1.032868e+08  175.550651  174.090649  166.893160  0.000988  \n",
       "2022-01-10  1.028636e+08  174.803840  173.917863  167.100879  0.000116  \n",
       "2022-01-11  9.900872e+07  174.865210  174.023512  167.413786  0.016784  \n",
       "2022-01-12  9.577525e+07  175.012941  174.160465  167.732069  0.002570  \n",
       "2022-01-13  9.070764e+07  175.054509  174.254968  168.024929 -0.001880  "
      ]
     },
     "execution_count": 18,
     "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": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>2022-01-07</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-11</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-12</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-13</th>\n",
       "      <td>1</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",
       "2022-01-07          1          0           0         0\n",
       "2022-01-10          1          0           0         0\n",
       "2022-01-11          1          0           0         0\n",
       "2022-01-12          1          0           0         0\n",
       "2022-01-13          1          0           0         0"
      ]
     },
     "execution_count": 19,
     "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": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current Trade:\n",
      "Price Entry | Last:\t148.5432 | 175.2000\n",
      "Unrealized PnL | %:\t26.6568 | 17.9455%\n",
      "\n",
      "Trades Total | Round Trip:\t5 | 2\n",
      "Trade Coverage: 59.13%\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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>2021-04-06</th>\n",
       "      <td>1</td>\n",
       "      <td>125.624153</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-06</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>129.137772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-14</th>\n",
       "      <td>1</td>\n",
       "      <td>130.094925</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-16</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>148.573151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-19</th>\n",
       "      <td>1</td>\n",
       "      <td>148.543198</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Signal       Entry        Exit\n",
       "Date                                      \n",
       "2021-04-06       1  125.624153         NaN\n",
       "2021-05-06      -1         NaN  129.137772\n",
       "2021-06-14       1  130.094925         NaN\n",
       "2021-09-16      -1         NaN  148.573151\n",
       "2021-10-19       1  148.543198         NaN"
      ]
     },
     "execution_count": 20,
     "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": 21,
   "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": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'\\nAAPL [D for 1y(252 bars)] from Friday 1-15-2021 to Thursday 1-13-2022\\nLast OHLCV: (175.7800, 176.6200, 174.5300, 175.2000, 29711051)\\nThursday January 13, 2022, NYSE: 4:44:17, Local: 8:44:17 PST, Day 13/365 (4.00%)'}, xlabel='Date'>"
      ]
     },
     "execution_count": 22,
     "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": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 23,
     "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": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 24,
     "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": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x13447fd30>"
      ]
     },
     "execution_count": 25,
     "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": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x13445c610>"
      ]
     },
     "execution_count": 26,
     "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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
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