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",
      "[+] yf | SPY(7310, 7): 3552.4306 ms (3.5524 s)\n",
      "[+] Saving: /Users/kj/av_data/SPY_D.csv\n",
      "[i] Analysis Time: 33.4526 ms (0.0335 s)\n",
      "[+] Downloading[yahoo]: QQQ[D]\n",
      "[+] yf | QQQ(5768, 7): 3149.0533 ms (3.1491 s)\n",
      "[+] Saving: /Users/kj/av_data/QQQ_D.csv\n",
      "[i] Analysis Time: 3.2938 ms (0.0033 s)\n",
      "[+] Downloading[yahoo]: AAPL[D]\n",
      "[+] yf | AAPL(10377, 7): 3140.3905 ms (3.1404 s)\n",
      "[+] Saving: /Users/kj/av_data/AAPL_D.csv\n",
      "[i] Analysis Time: 3.6440 ms (0.0036 s)\n",
      "[+] Downloading[yahoo]: TSLA[D]\n",
      "[+] yf | TSLA(2924, 7): 2794.6956 ms (2.7947 s)\n",
      "[+] Saving: /Users/kj/av_data/TSLA_D.csv\n",
      "[i] Analysis Time: 2.8422 ms (0.0028 s)\n",
      "[+] Downloading[yahoo]: BTC-USD[D]\n",
      "[+] yf | BTC-USD(2701, 7): 3494.6843 ms (3.4947 s)\n",
      "[+] Saving: /Users/kj/av_data/BTC-USD_D.csv\n",
      "[i] Analysis Time: 3.6090 ms (0.0036 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": [
      "QQQ (5768, 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>Date</th>\n",
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       "      <th>2017-02-07</th>\n",
       "      <td>121.609821</td>\n",
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       "      <th>2017-02-08</th>\n",
       "      <td>121.638777</td>\n",
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       "      <td>121.407299</td>\n",
       "      <td>122.005272</td>\n",
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       "      <td>120.477544</td>\n",
       "      <td>117.390999</td>\n",
       "      <td>111.057047</td>\n",
       "      <td>16610210.0</td>\n",
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       "    <tr>\n",
       "      <th>2017-02-13</th>\n",
       "      <td>123.230132</td>\n",
       "      <td>123.702720</td>\n",
       "      <td>123.181913</td>\n",
       "      <td>123.548416</td>\n",
       "      <td>19120200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>121.721710</td>\n",
       "      <td>120.715768</td>\n",
       "      <td>117.602149</td>\n",
       "      <td>111.166413</td>\n",
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       "      <th>2022-02-01</th>\n",
       "      <td>364.429993</td>\n",
       "      <td>366.190002</td>\n",
       "      <td>359.140015</td>\n",
       "      <td>365.519989</td>\n",
       "      <td>74433000</td>\n",
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       "    <tr>\n",
       "      <th>2022-02-02</th>\n",
       "      <td>369.760010</td>\n",
       "      <td>370.100006</td>\n",
       "      <td>364.290009</td>\n",
       "      <td>368.489990</td>\n",
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       "    <tr>\n",
       "      <th>2022-02-03</th>\n",
       "      <td>358.529999</td>\n",
       "      <td>361.929993</td>\n",
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       "      <th>2022-02-04</th>\n",
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       "      <td>361.399994</td>\n",
       "      <td>351.970001</td>\n",
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       "      <th>2022-02-07</th>\n",
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       "      <td>354.950012</td>\n",
       "      <td>358.165009</td>\n",
       "      <td>42674328</td>\n",
       "      <td>0.0</td>\n",
       "      <td>354.936496</td>\n",
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       "      <td>380.749953</td>\n",
       "      <td>365.812890</td>\n",
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      "text/plain": [
       "                  open        high         low       close    volume  \\\n",
       "Date                                                                   \n",
       "2017-02-07  121.609821  122.053483  121.494090  121.802719  17541100   \n",
       "2017-02-08  121.638777  122.178877  121.407299  122.005272  12569100   \n",
       "2017-02-09  122.130652  122.718979  122.063140  122.448929  17542700   \n",
       "2017-02-10  122.718971  123.027601  122.506787  122.853996  13915700   \n",
       "2017-02-13  123.230132  123.702720  123.181913  123.548416  19120200   \n",
       "...                ...         ...         ...         ...       ...   \n",
       "2022-02-01  364.429993  366.190002  359.140015  365.519989  74433000   \n",
       "2022-02-02  369.760010  370.100006  364.290009  368.489990  78777100   \n",
       "2022-02-03  358.529999  361.929993  352.459991  353.549988  95384800   \n",
       "2022-02-04  354.079987  361.399994  351.970001  358.010010  86127500   \n",
       "2022-02-07  358.619995  361.040009  354.950012  358.165009  42674328   \n",
       "\n",
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "Date                                                                       \n",
       "2017-02-07           0.0  121.014753  119.871375  116.896796  110.775148   \n",
       "2017-02-08           0.0  121.117952  120.059447  117.052081  110.863883   \n",
       "2017-02-09           0.0  121.252978  120.253788  117.221432  110.957372   \n",
       "2017-02-10           0.0  121.405363  120.477544  117.390999  111.057047   \n",
       "2017-02-13           0.0  121.721710  120.715768  117.602149  111.166413   \n",
       "...                  ...         ...         ...         ...         ...   \n",
       "2022-02-01           0.0  354.433997  368.523997  383.935446  365.349531   \n",
       "2022-02-02           0.0  354.634995  367.124997  383.235753  365.515881   \n",
       "2022-02-03           0.0  353.817993  365.587996  382.330939  365.593182   \n",
       "2022-02-04           0.0  354.449994  364.287497  381.551680  365.713161   \n",
       "2022-02-07           0.0  354.936496  363.202748  380.749953  365.812890   \n",
       "\n",
       "            vol_sma_20  \n",
       "Date                    \n",
       "2017-02-07  17233090.0  \n",
       "2017-02-08  17052715.0  \n",
       "2017-02-09  16895550.0  \n",
       "2017-02-10  16610210.0  \n",
       "2017-02-13  16719680.0  \n",
       "...                ...  \n",
       "2022-02-01  94048835.0  \n",
       "2022-02-02  95086330.0  \n",
       "2022-02-03  96068580.0  \n",
       "2022-02-04  96834240.0  \n",
       "2022-02-07  95337256.4  \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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       "      <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",
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       "      <td>365.515881</td>\n",
       "      <td>95086330.0</td>\n",
       "      <td>360.123876</td>\n",
       "      <td>367.098553</td>\n",
       "      <td>376.316749</td>\n",
       "      <td>0.008125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-03</th>\n",
       "      <td>0.0</td>\n",
       "      <td>353.817993</td>\n",
       "      <td>365.587996</td>\n",
       "      <td>382.330939</td>\n",
       "      <td>365.593182</td>\n",
       "      <td>96068580.0</td>\n",
       "      <td>358.663012</td>\n",
       "      <td>365.866866</td>\n",
       "      <td>375.423935</td>\n",
       "      <td>-0.040544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-04</th>\n",
       "      <td>0.0</td>\n",
       "      <td>354.449994</td>\n",
       "      <td>364.287497</td>\n",
       "      <td>381.551680</td>\n",
       "      <td>365.713161</td>\n",
       "      <td>96834240.0</td>\n",
       "      <td>358.517901</td>\n",
       "      <td>365.152606</td>\n",
       "      <td>374.741036</td>\n",
       "      <td>0.012615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-07</th>\n",
       "      <td>0.0</td>\n",
       "      <td>354.936496</td>\n",
       "      <td>363.202748</td>\n",
       "      <td>380.749953</td>\n",
       "      <td>365.812890</td>\n",
       "      <td>95337256.4</td>\n",
       "      <td>358.439480</td>\n",
       "      <td>364.517370</td>\n",
       "      <td>374.090995</td>\n",
       "      <td>0.000433</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            stock splits      sma_10      sma_20      sma_50     sma_200  \\\n",
       "Date                                                                       \n",
       "2022-02-01           0.0  354.433997  368.523997  383.935446  365.349531   \n",
       "2022-02-02           0.0  354.634995  367.124997  383.235753  365.515881   \n",
       "2022-02-03           0.0  353.817993  365.587996  382.330939  365.593182   \n",
       "2022-02-04           0.0  354.449994  364.287497  381.551680  365.713161   \n",
       "2022-02-07           0.0  354.936496  363.202748  380.749953  365.812890   \n",
       "\n",
       "            vol_sma_20       EMA_8      EMA_21      EMA_50  PCTRET_1  \n",
       "Date                                                                  \n",
       "2022-02-01  94048835.0  357.733558  366.959410  376.636208  0.006803  \n",
       "2022-02-02  95086330.0  360.123876  367.098553  376.316749  0.008125  \n",
       "2022-02-03  96068580.0  358.663012  365.866866  375.423935 -0.040544  \n",
       "2022-02-04  96834240.0  358.517901  365.152606  374.741036  0.012615  \n",
       "2022-02-07  95337256.4  358.439480  364.517370  374.090995  0.000433  "
      ]
     },
     "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": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TS_Trends</th>\n",
       "      <th>TS_Trades</th>\n",
       "      <th>TS_Entries</th>\n",
       "      <th>TS_Exits</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2022-02-01</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-02</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-03</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-04</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-07</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",
       "2022-02-01          0          0           0         0\n",
       "2022-02-02          0          0           0         0\n",
       "2022-02-03          0          0           0         0\n",
       "2022-02-04          0          0           0         0\n",
       "2022-02-07          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: 74.29%\n"
     ]
    },
    {
     "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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       "        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>2020-04-27</th>\n",
       "      <td>1</td>\n",
       "      <td>213.766617</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-01</th>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>280.388519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-16</th>\n",
       "      <td>1</td>\n",
       "      <td>286.607269</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>316.515167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-13</th>\n",
       "      <td>1</td>\n",
       "      <td>339.395111</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>332.947998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-16</th>\n",
       "      <td>1</td>\n",
       "      <td>339.803650</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>356.924133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-02</th>\n",
       "      <td>1</td>\n",
       "      <td>388.553711</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>379.859985</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Signal       Entry        Exit\n",
       "Date                                      \n",
       "2020-04-27       1  213.766617         NaN\n",
       "2020-10-01      -1         NaN  280.388519\n",
       "2020-10-16       1  286.607269         NaN\n",
       "2021-03-11      -1         NaN  316.515167\n",
       "2021-04-13       1  339.395111         NaN\n",
       "2021-05-26      -1         NaN  332.947998\n",
       "2021-06-16       1  339.803650         NaN\n",
       "2021-10-05      -1         NaN  356.924133\n",
       "2021-11-02       1  388.553711         NaN\n",
       "2022-01-07      -1         NaN  379.859985"
      ]
     },
     "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",
    "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':'\\nQQQ [D for 5y(1260 bars)] from Tuesday 2-7-2017 to Monday 2-7-2022\\nLast OHLCV: (358.6200, 361.0400, 354.9500, 358.1650, 42674328)\\nMonday February 7, 2022, NYSE: 7:58:00, Local: 11:58:00 PST, Day 38/365 (10.00%)'}, 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 0x1301d8c10>"
      ]
     },
     "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*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x1301e6430>"
      ]
     },
     "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=colors(\"GyOr\"), title=\"B&H Percent Returns\", alpha=0.4, 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 0x1302d8a00>"
      ]
     },
     "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\")"
   ]
  },
  {
   "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 (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
}