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: 844.9887 ms (0.8450 s)\n",
      "[+] Downloading[yahoo]: QQQ[D]\n",
      "[+] Saving: /Users/kj/av_data/QQQ_D.csv\n",
      "[i] Runtime: 696.5108 ms (0.6965 s)\n",
      "[+] Downloading[yahoo]: AAPL[D]\n",
      "[+] Saving: /Users/kj/av_data/AAPL_D.csv\n",
      "[i] Runtime: 722.0278 ms (0.7220 s)\n",
      "[+] Downloading[yahoo]: TSLA[D]\n",
      "[+] Saving: /Users/kj/av_data/TSLA_D.csv\n",
      "[i] Runtime: 681.2581 ms (0.6813 s)\n",
      "[+] Downloading[yahoo]: BTC-USD[D]\n",
      "[+] Saving: /Users/kj/av_data/BTC-USD_D.csv\n",
      "[i] Runtime: 670.3770 ms (0.6704 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": [
      "AAPL (10362, 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": 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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\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>112564755.0</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>108153655.0</td>\n",
       "    </tr>\n",
       "    <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>108098620.0</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>105376350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-25</th>\n",
       "      <td>142.193417</td>\n",
       "      <td>144.201029</td>\n",
       "      <td>135.703412</td>\n",
       "      <td>142.044327</td>\n",
       "      <td>157611700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>131.533128</td>\n",
       "      <td>131.358704</td>\n",
       "      <td>125.350640</td>\n",
       "      <td>104.935266</td>\n",
       "      <td>108845750.0</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>2022-01-10</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>102863650.0</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>99008715.0</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>74805200</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>95779955.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-13</th>\n",
       "      <td>175.779999</td>\n",
       "      <td>176.619995</td>\n",
       "      <td>171.789993</td>\n",
       "      <td>172.190002</td>\n",
       "      <td>84505800</td>\n",
       "      <td>0.0</td>\n",
       "      <td>175.336000</td>\n",
       "      <td>175.431000</td>\n",
       "      <td>166.677985</td>\n",
       "      <td>146.105657</td>\n",
       "      <td>93452080.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-14</th>\n",
       "      <td>171.339996</td>\n",
       "      <td>173.779999</td>\n",
       "      <td>171.089996</td>\n",
       "      <td>173.070007</td>\n",
       "      <td>80355000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>174.886000</td>\n",
       "      <td>175.471500</td>\n",
       "      <td>167.114001</td>\n",
       "      <td>146.358862</td>\n",
       "      <td>89960540.0</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",
       "2021-01-19  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",
       "2021-01-25  142.193417  144.201029  135.703412  142.044327  157611700   \n",
       "...                ...         ...         ...         ...        ...   \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   74805200   \n",
       "2022-01-13  175.779999  176.619995  171.789993  172.190002   84505800   \n",
       "2022-01-14  171.339996  173.779999  171.089996  173.070007   80355000   \n",
       "\n",
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "date                                                                       \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",
       "2021-01-25           0.0  131.533128  131.358704  125.350640  104.935266   \n",
       "...                  ...         ...         ...         ...         ...   \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  175.336000  175.431000  166.677985  146.105657   \n",
       "2022-01-14           0.0  174.886000  175.471500  167.114001  146.358862   \n",
       "\n",
       "             vol_sma_20  \n",
       "date                     \n",
       "2021-01-19  112564755.0  \n",
       "2021-01-20  108153655.0  \n",
       "2021-01-21  108098620.0  \n",
       "2021-01-22  105376350.0  \n",
       "2021-01-25  108845750.0  \n",
       "...                 ...  \n",
       "2022-01-10  102863650.0  \n",
       "2022-01-11   99008715.0  \n",
       "2022-01-12   95779955.0  \n",
       "2022-01-13   93452080.0  \n",
       "2022-01-14   89960540.0  \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"
     ]
    },
    {
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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",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-01-10</th>\n",
       "      <td>0.0</td>\n",
       "      <td>176.742999</td>\n",
       "      <td>175.7595</td>\n",
       "      <td>165.184505</td>\n",
       "      <td>145.300422</td>\n",
       "      <td>102863650.0</td>\n",
       "      <td>174.803840</td>\n",
       "      <td>173.917863</td>\n",
       "      <td>167.100948</td>\n",
       "      <td>0.000116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-11</th>\n",
       "      <td>0.0</td>\n",
       "      <td>176.322000</td>\n",
       "      <td>175.7265</td>\n",
       "      <td>165.694471</td>\n",
       "      <td>145.571689</td>\n",
       "      <td>99008715.0</td>\n",
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       "      <td>167.413852</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>175.7865</td>\n",
       "      <td>166.230213</td>\n",
       "      <td>145.852622</td>\n",
       "      <td>95779955.0</td>\n",
       "      <td>175.012941</td>\n",
       "      <td>174.160465</td>\n",
       "      <td>167.732132</td>\n",
       "      <td>0.002570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-13</th>\n",
       "      <td>0.0</td>\n",
       "      <td>175.336000</td>\n",
       "      <td>175.4310</td>\n",
       "      <td>166.677985</td>\n",
       "      <td>146.105657</td>\n",
       "      <td>93452080.0</td>\n",
       "      <td>174.385621</td>\n",
       "      <td>173.981332</td>\n",
       "      <td>167.906951</td>\n",
       "      <td>-0.019028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-14</th>\n",
       "      <td>0.0</td>\n",
       "      <td>174.886000</td>\n",
       "      <td>175.4715</td>\n",
       "      <td>167.114001</td>\n",
       "      <td>146.358862</td>\n",
       "      <td>89960540.0</td>\n",
       "      <td>174.093262</td>\n",
       "      <td>173.898484</td>\n",
       "      <td>168.109424</td>\n",
       "      <td>0.005111</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            stock splits      sma_10    sma_20      sma_50     sma_200  \\\n",
       "date                                                                     \n",
       "2022-01-10           0.0  176.742999  175.7595  165.184505  145.300422   \n",
       "2022-01-11           0.0  176.322000  175.7265  165.694471  145.571689   \n",
       "2022-01-12           0.0  175.937000  175.7865  166.230213  145.852622   \n",
       "2022-01-13           0.0  175.336000  175.4310  166.677985  146.105657   \n",
       "2022-01-14           0.0  174.886000  175.4715  167.114001  146.358862   \n",
       "\n",
       "             vol_sma_20       EMA_8      EMA_21      EMA_50  PCTRET_1  \n",
       "date                                                                   \n",
       "2022-01-10  102863650.0  174.803840  173.917863  167.100948  0.000116  \n",
       "2022-01-11   99008715.0  174.865210  174.023512  167.413852  0.016784  \n",
       "2022-01-12   95779955.0  175.012941  174.160465  167.732132  0.002570  \n",
       "2022-01-13   93452080.0  174.385621  173.981332  167.906951 -0.019028  \n",
       "2022-01-14   89960540.0  174.093262  173.898484  168.109424  0.005111  "
      ]
     },
     "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",
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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>2022-01-10</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",
       "    <tr>\n",
       "      <th>2022-01-14</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",
       "2022-01-10          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\n",
       "2022-01-14          1          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": [
      "Current Trade:\n",
      "Price Entry | Last:\t148.5432 | 173.0700\n",
      "Unrealized PnL | %:\t24.5268 | 16.5116%\n",
      "\n",
      "Trades Total | Round Trip:\t5 | 2\n",
      "Trade Coverage: 59.52%\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>2021-04-06</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": 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':'\\nAAPL [D for 1y(252 bars)] from Tuesday 1-19-2021 to Friday 1-14-2022\\nLast OHLCV: (171.3400, 173.7800, 171.0900, 173.0700, 80355000)\\nSunday January 16, 2022, NYSE: 11:49:14, Local: 15:49:14 PST, Day 16/365 (4.00%)'}, 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 0x12fd80970>"
      ]
     },
     "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 0x12feedb20>"
      ]
     },
     "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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}