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 v1.20.2\n",
      "Pandas v1.2.4\n",
      "mplfinance v0.12.7a12\n",
      "\n",
      "Pandas TA v0.2.74b0\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: 525.9195 ms (0.5259 s)\n",
      "[+] Downloading[yahoo]: QQQ[D]\n",
      "[+] Saving: /Users/kj/av_data/QQQ_D.csv\n",
      "[i] Runtime: 480.6160 ms (0.4806 s)\n",
      "[+] Downloading[yahoo]: AAPL[D]\n",
      "[+] Saving: /Users/kj/av_data/AAPL_D.csv\n",
      "[i] Runtime: 508.6772 ms (0.5087 s)\n",
      "[+] Downloading[yahoo]: TSLA[D]\n",
      "[+] Saving: /Users/kj/av_data/TSLA_D.csv\n",
      "[i] Runtime: 477.4917 ms (0.4775 s)\n",
      "[+] Downloading[yahoo]: BTC-USD[D]\n",
      "[+] Saving: /Users/kj/av_data/BTC-USD_D.csv\n",
      "[i] Runtime: 497.8067 ms (0.4978 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": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SPY (7128, 12)\n",
      "Columns: open, high, low, close, volume, dividends, split, 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": [
    {
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       "    <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>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",
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       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>2020-05-20</th>\n",
       "      <td>291.150942</td>\n",
       "      <td>293.168574</td>\n",
       "      <td>290.904888</td>\n",
       "      <td>292.243408</td>\n",
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       "      <td>266.659134</td>\n",
       "      <td>292.472755</td>\n",
       "      <td>98976520.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-21</th>\n",
       "      <td>292.105626</td>\n",
       "      <td>292.971742</td>\n",
       "      <td>289.054549</td>\n",
       "      <td>290.225769</td>\n",
       "      <td>78293900</td>\n",
       "      <td>285.741672</td>\n",
       "      <td>283.806703</td>\n",
       "      <td>267.094627</td>\n",
       "      <td>292.529205</td>\n",
       "      <td>97655730.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-22</th>\n",
       "      <td>289.920683</td>\n",
       "      <td>290.963951</td>\n",
       "      <td>288.591985</td>\n",
       "      <td>290.776947</td>\n",
       "      <td>63958200</td>\n",
       "      <td>286.036938</td>\n",
       "      <td>284.420363</td>\n",
       "      <td>268.054838</td>\n",
       "      <td>292.587587</td>\n",
       "      <td>96600480.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-26</th>\n",
       "      <td>297.164459</td>\n",
       "      <td>297.420365</td>\n",
       "      <td>290.796577</td>\n",
       "      <td>294.359436</td>\n",
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       "    <tr>\n",
       "      <th>2020-05-27</th>\n",
       "      <td>297.351478</td>\n",
       "      <td>298.778604</td>\n",
       "      <td>292.184342</td>\n",
       "      <td>298.739227</td>\n",
       "      <td>104817400</td>\n",
       "      <td>288.343939</td>\n",
       "      <td>285.888319</td>\n",
       "      <td>269.952733</td>\n",
       "      <td>292.717008</td>\n",
       "      <td>97130590.00</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",
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       "    <tr>\n",
       "      <th>2021-05-13</th>\n",
       "      <td>407.070007</td>\n",
       "      <td>412.350006</td>\n",
       "      <td>407.019989</td>\n",
       "      <td>410.279999</td>\n",
       "      <td>106394000</td>\n",
       "      <td>415.589999</td>\n",
       "      <td>415.910498</td>\n",
       "      <td>404.295667</td>\n",
       "      <td>367.011310</td>\n",
       "      <td>79515840.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-14</th>\n",
       "      <td>413.209991</td>\n",
       "      <td>417.489990</td>\n",
       "      <td>413.179993</td>\n",
       "      <td>416.579987</td>\n",
       "      <td>82123100</td>\n",
       "      <td>415.517999</td>\n",
       "      <td>415.876497</td>\n",
       "      <td>405.117861</td>\n",
       "      <td>367.487226</td>\n",
       "      <td>79520130.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-17</th>\n",
       "      <td>415.390015</td>\n",
       "      <td>416.390015</td>\n",
       "      <td>413.359985</td>\n",
       "      <td>415.519989</td>\n",
       "      <td>65129200</td>\n",
       "      <td>415.249997</td>\n",
       "      <td>415.891997</td>\n",
       "      <td>405.780709</td>\n",
       "      <td>367.963577</td>\n",
       "      <td>78851665.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-18</th>\n",
       "      <td>415.799988</td>\n",
       "      <td>416.059998</td>\n",
       "      <td>411.769989</td>\n",
       "      <td>411.940002</td>\n",
       "      <td>59266000</td>\n",
       "      <td>414.881998</td>\n",
       "      <td>415.880496</td>\n",
       "      <td>406.410032</td>\n",
       "      <td>368.409374</td>\n",
       "      <td>77722375.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-19</th>\n",
       "      <td>406.920013</td>\n",
       "      <td>410.250000</td>\n",
       "      <td>405.329987</td>\n",
       "      <td>408.234985</td>\n",
       "      <td>66477971</td>\n",
       "      <td>414.130496</td>\n",
       "      <td>415.488745</td>\n",
       "      <td>406.856610</td>\n",
       "      <td>368.825426</td>\n",
       "      <td>77706623.55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  open        high         low       close     volume  \\\n",
       "date                                                                    \n",
       "2020-05-20  291.150942  293.168574  290.904888  292.243408   85861700   \n",
       "2020-05-21  292.105626  292.971742  289.054549  290.225769   78293900   \n",
       "2020-05-22  289.920683  290.963951  288.591985  290.776947   63958200   \n",
       "2020-05-26  297.164459  297.420365  290.796577  294.359436   88951400   \n",
       "2020-05-27  297.351478  298.778604  292.184342  298.739227  104817400   \n",
       "...                ...         ...         ...         ...        ...   \n",
       "2021-05-13  407.070007  412.350006  407.019989  410.279999  106394000   \n",
       "2021-05-14  413.209991  417.489990  413.179993  416.579987   82123100   \n",
       "2021-05-17  415.390015  416.390015  413.359985  415.519989   65129200   \n",
       "2021-05-18  415.799988  416.059998  411.769989  411.940002   59266000   \n",
       "2021-05-19  406.920013  410.250000  405.329987  408.234985   66477971   \n",
       "\n",
       "                sma_10      sma_20      sma_50     sma_200   vol_sma_20  \n",
       "date                                                                     \n",
       "2020-05-20  285.033035  283.029170  266.659134  292.472755  98976520.00  \n",
       "2020-05-21  285.741672  283.806703  267.094627  292.529205  97655730.00  \n",
       "2020-05-22  286.036938  284.420363  268.054838  292.587587  96600480.00  \n",
       "2020-05-26  286.684552  285.012367  268.671635  292.636502  97153220.00  \n",
       "2020-05-27  288.343939  285.888319  269.952733  292.717008  97130590.00  \n",
       "...                ...         ...         ...         ...          ...  \n",
       "2021-05-13  415.589999  415.910498  404.295667  367.011310  79515840.00  \n",
       "2021-05-14  415.517999  415.876497  405.117861  367.487226  79520130.00  \n",
       "2021-05-17  415.249997  415.891997  405.780709  367.963577  78851665.00  \n",
       "2021-05-18  414.881998  415.880496  406.410032  368.409374  77722375.00  \n",
       "2021-05-19  414.130496  415.488745  406.856610  368.825426  77706623.55  \n",
       "\n",
       "[252 rows x 10 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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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-05-13</th>\n",
       "      <td>415.589999</td>\n",
       "      <td>415.910498</td>\n",
       "      <td>404.295667</td>\n",
       "      <td>367.011310</td>\n",
       "      <td>79515840.00</td>\n",
       "      <td>413.680581</td>\n",
       "      <td>413.448932</td>\n",
       "      <td>405.708303</td>\n",
       "      <td>0.012013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-14</th>\n",
       "      <td>415.517999</td>\n",
       "      <td>415.876497</td>\n",
       "      <td>405.117861</td>\n",
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       "      <td>414.324894</td>\n",
       "      <td>413.733573</td>\n",
       "      <td>406.134643</td>\n",
       "      <td>0.015355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-17</th>\n",
       "      <td>415.249997</td>\n",
       "      <td>415.891997</td>\n",
       "      <td>405.780709</td>\n",
       "      <td>367.963577</td>\n",
       "      <td>78851665.00</td>\n",
       "      <td>414.590470</td>\n",
       "      <td>413.895974</td>\n",
       "      <td>406.502696</td>\n",
       "      <td>-0.002545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-18</th>\n",
       "      <td>414.881998</td>\n",
       "      <td>415.880496</td>\n",
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       "      <td>414.001478</td>\n",
       "      <td>413.718159</td>\n",
       "      <td>406.715924</td>\n",
       "      <td>-0.008616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-19</th>\n",
       "      <td>414.130496</td>\n",
       "      <td>415.488745</td>\n",
       "      <td>406.856610</td>\n",
       "      <td>368.825426</td>\n",
       "      <td>77706623.55</td>\n",
       "      <td>412.720035</td>\n",
       "      <td>413.219688</td>\n",
       "      <td>406.775495</td>\n",
       "      <td>-0.008994</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                sma_10      sma_20      sma_50     sma_200   vol_sma_20  \\\n",
       "date                                                                      \n",
       "2021-05-13  415.589999  415.910498  404.295667  367.011310  79515840.00   \n",
       "2021-05-14  415.517999  415.876497  405.117861  367.487226  79520130.00   \n",
       "2021-05-17  415.249997  415.891997  405.780709  367.963577  78851665.00   \n",
       "2021-05-18  414.881998  415.880496  406.410032  368.409374  77722375.00   \n",
       "2021-05-19  414.130496  415.488745  406.856610  368.825426  77706623.55   \n",
       "\n",
       "                 EMA_8      EMA_21      EMA_50  PCTRET_1  \n",
       "date                                                      \n",
       "2021-05-13  413.680581  413.448932  405.708303  0.012013  \n",
       "2021-05-14  414.324894  413.733573  406.134643  0.015355  \n",
       "2021-05-17  414.590470  413.895974  406.502696 -0.002545  \n",
       "2021-05-18  414.001478  413.718159  406.715924 -0.008616  \n",
       "2021-05-19  412.720035  413.219688  406.775495 -0.008994  "
      ]
     },
     "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>2021-05-13</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-14</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-17</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-18</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-19</th>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            TS_Trends  TS_Trades  TS_Entries  TS_Exits\n",
       "date                                                  \n",
       "2021-05-13          1          0           0         0\n",
       "2021-05-14          1          0           0         0\n",
       "2021-05-17          1          0           0         0\n",
       "2021-05-18          1          0           0         0\n",
       "2021-05-19          0         -1           0         1"
      ]
     },
     "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:\t10 | 5\n",
      "Trade Coverage: 80.56%\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>2020-06-18</th>\n",
       "      <td>1</td>\n",
       "      <td>306.859009</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-29</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>300.973206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>1</td>\n",
       "      <td>304.828522</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-11</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>330.234192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-05</th>\n",
       "      <td>1</td>\n",
       "      <td>337.213409</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-28</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>324.211609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-05</th>\n",
       "      <td>1</td>\n",
       "      <td>347.614868</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-03</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>380.174835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-10</th>\n",
       "      <td>1</td>\n",
       "      <td>388.308197</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>408.234985</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Signal       Entry        Exit\n",
       "date                                      \n",
       "2020-06-18       1  306.859009         NaN\n",
       "2020-06-29      -1         NaN  300.973206\n",
       "2020-06-30       1  304.828522         NaN\n",
       "2020-09-11      -1         NaN  330.234192\n",
       "2020-10-05       1  337.213409         NaN\n",
       "2020-10-28      -1         NaN  324.211609\n",
       "2020-11-05       1  347.614868         NaN\n",
       "2021-03-03      -1         NaN  380.174835\n",
       "2021-03-10       1  388.308197         NaN\n",
       "2021-05-19      -1         NaN  408.234985"
      ]
     },
     "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 Wednesday 5-20-2020 to Wednesday 5-19-2021\\nLast OHLCV: (406.9200, 410.2500, 405.3300, 408.2350, 66477971)\\nWednesday May 19, 2021, NYSE: 7:20:10, Local: 11:20:10 PDT, Day 139/365 (38.00%)'}, 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 0x12f2f8fa0>"
      ]
     },
     "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 * 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 0x12f280af0>"
      ]
     },
     "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\"]].cumsum().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."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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
}