pandas-ta/examples/TA_Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TA Analysis with **Pandas TA**\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 v0.3.63b0\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",
      "[+] yf | SPY(7367, 7): 3196.9914 ms (3.1970 s)\n",
      "[+] Saving: /Users/kj/av_data/SPY_D.csv\n",
      "[i] Analysis Time: 34.3883 ms (0.0344 s) for 5 columns (avg 6.8791 ms / col)\n",
      "[+] Downloading[yahoo]: QQQ[D]\n",
      "[+] yf | QQQ(5825, 7): 4333.8306 ms (4.3338 s)\n",
      "[+] Saving: /Users/kj/av_data/QQQ_D.csv\n",
      "[i] Analysis Time: 3.3304 ms (0.0033 s) for 5 columns (avg 0.6667 ms / col)\n",
      "[+] Downloading[yahoo]: AAPL[D]\n",
      "[+] yf | AAPL(10434, 7): 4274.9140 ms (4.2749 s)\n",
      "[+] Saving: /Users/kj/av_data/AAPL_D.csv\n",
      "[i] Analysis Time: 3.6997 ms (0.0037 s) for 5 columns (avg 0.7406 ms / col)\n",
      "[+] Downloading[yahoo]: TSLA[D]\n",
      "[+] yf | TSLA(2981, 7): 3129.0620 ms (3.1291 s)\n",
      "[+] Saving: /Users/kj/av_data/TSLA_D.csv\n",
      "[i] Analysis Time: 3.0117 ms (0.0030 s) for 5 columns (avg 0.6030 ms / col)\n",
      "[+] Downloading[yahoo]: BTC-USD[D]\n",
      "[+] yf | BTC-USD(2784, 7): 3533.1249 ms (3.5331 s)\n",
      "[+] Saving: /Users/kj/av_data/BTC-USD_D.csv\n",
      "[i] Analysis Time: 3.6089 ms (0.0036 s) for 5 columns (avg 0.7226 ms / col)\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": [
      "QQQ (5825, 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[1] # 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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       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
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       "      <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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       "    <tr>\n",
       "      <th>2017-05-01</th>\n",
       "      <td>131.702961</td>\n",
       "      <td>132.610327</td>\n",
       "      <td>131.645046</td>\n",
       "      <td>132.436569</td>\n",
       "      <td>24815500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>129.452889</td>\n",
       "      <td>128.293103</td>\n",
       "      <td>127.098378</td>\n",
       "      <td>117.352839</td>\n",
       "      <td>20653180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-02</th>\n",
       "      <td>132.600685</td>\n",
       "      <td>132.716529</td>\n",
       "      <td>132.262846</td>\n",
       "      <td>132.658600</td>\n",
       "      <td>18345100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>130.046537</td>\n",
       "      <td>128.540698</td>\n",
       "      <td>127.250689</td>\n",
       "      <td>117.480589</td>\n",
       "      <td>20385420.0</td>\n",
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       "    <tr>\n",
       "      <th>2017-05-03</th>\n",
       "      <td>132.359333</td>\n",
       "      <td>132.407600</td>\n",
       "      <td>131.876692</td>\n",
       "      <td>132.233856</td>\n",
       "      <td>23827600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>130.577444</td>\n",
       "      <td>128.756921</td>\n",
       "      <td>127.382175</td>\n",
       "      <td>117.602671</td>\n",
       "      <td>20906800.0</td>\n",
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       "    <tr>\n",
       "      <th>2017-05-04</th>\n",
       "      <td>132.214573</td>\n",
       "      <td>132.658594</td>\n",
       "      <td>131.818804</td>\n",
       "      <td>132.282135</td>\n",
       "      <td>14630100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>131.006993</td>\n",
       "      <td>129.001620</td>\n",
       "      <td>127.513663</td>\n",
       "      <td>117.726958</td>\n",
       "      <td>20037745.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-05</th>\n",
       "      <td>132.619938</td>\n",
       "      <td>132.764725</td>\n",
       "      <td>132.127651</td>\n",
       "      <td>132.764725</td>\n",
       "      <td>19330700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>131.487700</td>\n",
       "      <td>129.267070</td>\n",
       "      <td>127.664244</td>\n",
       "      <td>117.847383</td>\n",
       "      <td>20062670.0</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",
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       "    <tr>\n",
       "      <th>2022-04-25</th>\n",
       "      <td>323.730011</td>\n",
       "      <td>329.899994</td>\n",
       "      <td>322.429993</td>\n",
       "      <td>329.579987</td>\n",
       "      <td>101755900</td>\n",
       "      <td>0.0</td>\n",
       "      <td>338.041000</td>\n",
       "      <td>349.745001</td>\n",
       "      <td>344.924885</td>\n",
       "      <td>367.586838</td>\n",
       "      <td>67700730.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-26</th>\n",
       "      <td>327.470001</td>\n",
       "      <td>327.660004</td>\n",
       "      <td>316.859985</td>\n",
       "      <td>317.140015</td>\n",
       "      <td>105819600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>335.666000</td>\n",
       "      <td>347.356502</td>\n",
       "      <td>344.335056</td>\n",
       "      <td>367.366986</td>\n",
       "      <td>70150015.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-27</th>\n",
       "      <td>317.239990</td>\n",
       "      <td>322.880005</td>\n",
       "      <td>315.000000</td>\n",
       "      <td>316.760010</td>\n",
       "      <td>111204200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>333.397000</td>\n",
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       "      <td>343.729037</td>\n",
       "      <td>367.145234</td>\n",
       "      <td>72306575.0</td>\n",
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       "    <tr>\n",
       "      <th>2022-04-28</th>\n",
       "      <td>321.850006</td>\n",
       "      <td>329.890015</td>\n",
       "      <td>317.519989</td>\n",
       "      <td>328.010010</td>\n",
       "      <td>99450000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>331.563000</td>\n",
       "      <td>342.681003</td>\n",
       "      <td>343.175432</td>\n",
       "      <td>366.976494</td>\n",
       "      <td>73841190.0</td>\n",
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       "    <tr>\n",
       "      <th>2022-04-29</th>\n",
       "      <td>323.700012</td>\n",
       "      <td>327.230011</td>\n",
       "      <td>312.600006</td>\n",
       "      <td>313.250000</td>\n",
       "      <td>91856700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>329.045001</td>\n",
       "      <td>340.216502</td>\n",
       "      <td>342.328425</td>\n",
       "      <td>366.746658</td>\n",
       "      <td>75083455.0</td>\n",
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       "  </tbody>\n",
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       "<p>1260 rows × 11 columns</p>\n",
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      ],
      "text/plain": [
       "                  open        high         low       close     volume  \\\n",
       "Date                                                                    \n",
       "2017-05-01  131.702961  132.610327  131.645046  132.436569   24815500   \n",
       "2017-05-02  132.600685  132.716529  132.262846  132.658600   18345100   \n",
       "2017-05-03  132.359333  132.407600  131.876692  132.233856   23827600   \n",
       "2017-05-04  132.214573  132.658594  131.818804  132.282135   14630100   \n",
       "2017-05-05  132.619938  132.764725  132.127651  132.764725   19330700   \n",
       "...                ...         ...         ...         ...        ...   \n",
       "2022-04-25  323.730011  329.899994  322.429993  329.579987  101755900   \n",
       "2022-04-26  327.470001  327.660004  316.859985  317.140015  105819600   \n",
       "2022-04-27  317.239990  322.880005  315.000000  316.760010  111204200   \n",
       "2022-04-28  321.850006  329.890015  317.519989  328.010010   99450000   \n",
       "2022-04-29  323.700012  327.230011  312.600006  313.250000   91856700   \n",
       "\n",
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "Date                                                                       \n",
       "2017-05-01           0.0  129.452889  128.293103  127.098378  117.352839   \n",
       "2017-05-02           0.0  130.046537  128.540698  127.250689  117.480589   \n",
       "2017-05-03           0.0  130.577444  128.756921  127.382175  117.602671   \n",
       "2017-05-04           0.0  131.006993  129.001620  127.513663  117.726958   \n",
       "2017-05-05           0.0  131.487700  129.267070  127.664244  117.847383   \n",
       "...                  ...         ...         ...         ...         ...   \n",
       "2022-04-25           0.0  338.041000  349.745001  344.924885  367.586838   \n",
       "2022-04-26           0.0  335.666000  347.356502  344.335056  367.366986   \n",
       "2022-04-27           0.0  333.397000  344.635002  343.729037  367.145234   \n",
       "2022-04-28           0.0  331.563000  342.681003  343.175432  366.976494   \n",
       "2022-04-29           0.0  329.045001  340.216502  342.328425  366.746658   \n",
       "\n",
       "            vol_sma_20  \n",
       "Date                    \n",
       "2017-05-01  20653180.0  \n",
       "2017-05-02  20385420.0  \n",
       "2017-05-03  20906800.0  \n",
       "2017-05-04  20037745.0  \n",
       "2017-05-05  20062670.0  \n",
       "...                ...  \n",
       "2022-04-25  67700730.0  \n",
       "2022-04-26  70150015.0  \n",
       "2022-04-27  72306575.0  \n",
       "2022-04-28  73841190.0  \n",
       "2022-04-29  75083455.0  \n",
       "\n",
       "[1260 rows x 11 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duration = \"5y\"\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",
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       "    <tr>\n",
       "      <th>2022-04-25</th>\n",
       "      <td>0.0</td>\n",
       "      <td>338.041000</td>\n",
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       "      <td>344.924885</td>\n",
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       "      <td>348.865113</td>\n",
       "      <td>0.012846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-26</th>\n",
       "      <td>0.0</td>\n",
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       "      <td>347.356502</td>\n",
       "      <td>344.335056</td>\n",
       "      <td>367.366986</td>\n",
       "      <td>70150015.0</td>\n",
       "      <td>332.164260</td>\n",
       "      <td>341.146136</td>\n",
       "      <td>347.620992</td>\n",
       "      <td>-0.037745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-27</th>\n",
       "      <td>0.0</td>\n",
       "      <td>333.397000</td>\n",
       "      <td>344.635002</td>\n",
       "      <td>343.729037</td>\n",
       "      <td>367.145234</td>\n",
       "      <td>72306575.0</td>\n",
       "      <td>328.741093</td>\n",
       "      <td>338.929215</td>\n",
       "      <td>346.410757</td>\n",
       "      <td>-0.001198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-28</th>\n",
       "      <td>0.0</td>\n",
       "      <td>331.563000</td>\n",
       "      <td>342.681003</td>\n",
       "      <td>343.175432</td>\n",
       "      <td>366.976494</td>\n",
       "      <td>73841190.0</td>\n",
       "      <td>328.578630</td>\n",
       "      <td>337.936560</td>\n",
       "      <td>345.689159</td>\n",
       "      <td>0.035516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-29</th>\n",
       "      <td>0.0</td>\n",
       "      <td>329.045001</td>\n",
       "      <td>340.216502</td>\n",
       "      <td>342.328425</td>\n",
       "      <td>366.746658</td>\n",
       "      <td>75083455.0</td>\n",
       "      <td>325.172268</td>\n",
       "      <td>335.692328</td>\n",
       "      <td>344.417035</td>\n",
       "      <td>-0.044999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "Date                                                                       \n",
       "2022-04-25           0.0  338.041000  349.745001  344.924885  367.586838   \n",
       "2022-04-26           0.0  335.666000  347.356502  344.335056  367.366986   \n",
       "2022-04-27           0.0  333.397000  344.635002  343.729037  367.145234   \n",
       "2022-04-28           0.0  331.563000  342.681003  343.175432  366.976494   \n",
       "2022-04-29           0.0  329.045001  340.216502  342.328425  366.746658   \n",
       "\n",
       "            vol_sma_20       EMA_8      EMA_21      EMA_50  PCTRET_1  \n",
       "Date                                                                  \n",
       "2022-04-25  67700730.0  336.456901  343.546748  348.865113  0.012846  \n",
       "2022-04-26  70150015.0  332.164260  341.146136  347.620992 -0.037745  \n",
       "2022-04-27  72306575.0  328.741093  338.929215  346.410757 -0.001198  \n",
       "2022-04-28  73841190.0  328.578630  337.936560  345.689159  0.035516  \n",
       "2022-04-29  75083455.0  325.172268  335.692328  344.417035 -0.044999  "
      ]
     },
     "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, 20) > ta.sma(asset.close, 50) # SMA(20) > SMA(50)\n",
    "# long = ta.ema(asset.close, 8) > ta.ema(asset.close, 21) # EMA(8) > EMA(21)\n",
    "# long = ta.increasing(ta.ema(asset.close, 20))\n",
    "# long = ta.macd(asset.close).iloc[:,1] > 0 # MACD Histogram is positive\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, cumulative=False)\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": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tsignals\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\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>2022-04-25</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-26</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-27</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-28</th>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-29</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            TS_Trends  TS_Trades  TS_Entries  TS_Exits\n",
       "Date                                                  \n",
       "2022-04-25          1          0           0         0\n",
       "2022-04-26          1          0           0         0\n",
       "2022-04-27          1          0           0         0\n",
       "2022-04-28          0         -1           0         1\n",
       "2022-04-29          0          0           0         0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trendy = asset.ta.tsignals(long, asbool=False, append=True)\n",
    "trendy.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trend Entries & Exits & Trade Table\n",
    "This is a simple way to reduce the Asset DataFrame to a Trade Table with Dates, Signals, and Entries and Exits. Gives you an idea what to expect before running through a backtester such as [**vectorbt**](https://github.com/polakowo/vectorbt)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Trades Total | Round Trip:\t22 | 11\n",
      "Trade Coverage: 71.19%\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\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>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>2020-10-16</th>\n",
       "      <td>1</td>\n",
       "      <td>286.253357</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-11</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>316.124359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-13</th>\n",
       "      <td>1</td>\n",
       "      <td>338.976044</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-26</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>332.536896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-16</th>\n",
       "      <td>1</td>\n",
       "      <td>339.384125</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-10-05</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>356.483398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-02</th>\n",
       "      <td>1</td>\n",
       "      <td>388.073944</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-07</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>379.390961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-05</th>\n",
       "      <td>1</td>\n",
       "      <td>361.100006</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-28</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>328.010010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Signal       Entry        Exit\n",
       "Date                                      \n",
       "2020-10-16       1  286.253357         NaN\n",
       "2021-03-11      -1         NaN  316.124359\n",
       "2021-04-13       1  338.976044         NaN\n",
       "2021-05-26      -1         NaN  332.536896\n",
       "2021-06-16       1  339.384125         NaN\n",
       "2021-10-05      -1         NaN  356.483398\n",
       "2021-11-02       1  388.073944         NaN\n",
       "2022-01-07      -1         NaN  379.390961\n",
       "2022-04-05       1  361.100006         NaN\n",
       "2022-04-28      -1         NaN  328.010010"
      ]
     },
     "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",
    "tradelist = trades\n",
    "if rt_trades > 10:\n",
    "    tradelist = trades.tail(10)\n",
    "tradelist"
   ]
  },
  {
   "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",
    "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",
    "_oc_change = asset.iloc[-1].open - asset.iloc[-1].close\n",
    "_oc_change_pct = _oc_change / asset.iloc[-1].open\n",
    "oc_change = f\"{_oc_change:.4f} ({100 * _oc_change_pct:.4f} %)\"\n",
    "ptitle = f\"\\n{ticker} [{tf} for {duration}({recent} bars)]\\n{last_ohlcv}, Change (%): {oc_change}\\n{extime}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trade Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'\\nQQQ [D for 5y(1260 bars)]\\nLast OHLCV: (323.7000, 327.2300, 312.6000, 313.2500, 91856700), Change (%): 10.4500 (3.2283 %)\\nSunday May 1, 2022, NYSE: 14:15:43, Local: 18:15:43 PDT, Day 121/365 (33.00%)'}, 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=[\"limegreen\"], alpha=0.65) # Green Area\n",
    "short_trend.plot(figsize=(16, 0.85), kind=\"area\", stacked=True, color=[\"orangered\"], alpha=0.65) # 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 0x132855d00>"
      ]
     },
     "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=[\"gray\", \"limegreen\"], alpha=1, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Buy and Hold Returns (*PCTRET_1*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x13206da60>"
      ]
     },
     "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 + 1).cumprod() - 1).plot(figsize=(16, 3), kind=\"area\", stacked=False, color=[\"limegreen\"], title=\"B&H Percent Returns\", alpha=0.9, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cum. Active Returns (*ACTRET_1*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x133835ee0>"
      ]
     },
     "execution_count": 16,
     "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 + 1).cumprod() - 1).plot(figsize=(16, 3), kind=\"area\", stacked=False, color=colors(\"GyOr\")[-1], title=\"B&H Cum. Active Returns\", alpha=0.4, grid=True).axhline(0, color=\"black\")\n",
    "((asset.ACTRET_1 + 1).cumprod() - 1).plot(figsize=(16, 3), kind=\"area\", stacked=False, color=[\"limegreen\"], title=\"B&H Cum. Active Returns\", alpha=0.65, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Disclaimer\n",
    "* All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.\n",
    "\n",
    "* Any opinions, news, research, analyses, prices, or other information offered is provided as general market commentary, and does not constitute investment advice. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from use of or reliance on such information."
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