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 v0.2.81b0\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: 564.8906 ms (0.5649 s)\n",
      "[+] Downloading[yahoo]: QQQ[D]\n",
      "[+] Saving: /Users/kj/av_data/QQQ_D.csv\n",
      "[i] Runtime: 480.6391 ms (0.4806 s)\n",
      "[+] Downloading[yahoo]: AAPL[D]\n",
      "[+] Saving: /Users/kj/av_data/AAPL_D.csv\n",
      "[i] Runtime: 487.6218 ms (0.4876 s)\n",
      "[+] Downloading[yahoo]: TSLA[D]\n",
      "[+] Saving: /Users/kj/av_data/TSLA_D.csv\n",
      "[i] Runtime: 480.0870 ms (0.4801 s)\n",
      "[+] Downloading[yahoo]: BTC-USD[D]\n",
      "[+] Saving: /Users/kj/av_data/BTC-USD_D.csv\n",
      "[i] Runtime: 504.6003 ms (0.5046 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 (7133, 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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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>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",
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       "      <th></th>\n",
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       "      <th>2020-05-28</th>\n",
       "      <td>299.841556</td>\n",
       "      <td>301.996993</td>\n",
       "      <td>297.469591</td>\n",
       "      <td>298.188080</td>\n",
       "      <td>90405200</td>\n",
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       "      <td>286.368619</td>\n",
       "      <td>270.969386</td>\n",
       "      <td>292.811961</td>\n",
       "      <td>95713570.00</td>\n",
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       "    <tr>\n",
       "      <th>2020-05-29</th>\n",
       "      <td>297.686126</td>\n",
       "      <td>300.146668</td>\n",
       "      <td>294.743328</td>\n",
       "      <td>299.516785</td>\n",
       "      <td>119090800</td>\n",
       "      <td>292.351669</td>\n",
       "      <td>287.049696</td>\n",
       "      <td>272.263101</td>\n",
       "      <td>292.891848</td>\n",
       "      <td>95523025.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-01</th>\n",
       "      <td>298.827795</td>\n",
       "      <td>301.376912</td>\n",
       "      <td>298.276636</td>\n",
       "      <td>300.727325</td>\n",
       "      <td>55758300</td>\n",
       "      <td>294.248248</td>\n",
       "      <td>288.169734</td>\n",
       "      <td>273.571046</td>\n",
       "      <td>293.019705</td>\n",
       "      <td>92051940.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-02</th>\n",
       "      <td>301.711527</td>\n",
       "      <td>303.266606</td>\n",
       "      <td>300.284431</td>\n",
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       "      <td>275.131618</td>\n",
       "      <td>293.156378</td>\n",
       "      <td>91721640.00</td>\n",
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       "    <tr>\n",
       "      <th>2020-06-03</th>\n",
       "      <td>305.343334</td>\n",
       "      <td>308.276310</td>\n",
       "      <td>305.048081</td>\n",
       "      <td>307.252716</td>\n",
       "      <td>92567600</td>\n",
       "      <td>297.524707</td>\n",
       "      <td>290.654878</td>\n",
       "      <td>276.888051</td>\n",
       "      <td>293.292875</td>\n",
       "      <td>92371525.00</td>\n",
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       "    <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>2021-05-20</th>\n",
       "      <td>411.799988</td>\n",
       "      <td>416.630005</td>\n",
       "      <td>411.670013</td>\n",
       "      <td>415.279999</td>\n",
       "      <td>78022200</td>\n",
       "      <td>414.013995</td>\n",
       "      <td>415.770496</td>\n",
       "      <td>407.448546</td>\n",
       "      <td>369.283551</td>\n",
       "      <td>78755260.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-21</th>\n",
       "      <td>416.869995</td>\n",
       "      <td>418.200012</td>\n",
       "      <td>414.450012</td>\n",
       "      <td>414.940002</td>\n",
       "      <td>76519100</td>\n",
       "      <td>413.295996</td>\n",
       "      <td>415.680496</td>\n",
       "      <td>407.902440</td>\n",
       "      <td>369.716719</td>\n",
       "      <td>78920755.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-24</th>\n",
       "      <td>417.339996</td>\n",
       "      <td>420.320007</td>\n",
       "      <td>417.079987</td>\n",
       "      <td>419.170013</td>\n",
       "      <td>51376700</td>\n",
       "      <td>413.418997</td>\n",
       "      <td>415.758498</td>\n",
       "      <td>408.430369</td>\n",
       "      <td>370.160063</td>\n",
       "      <td>78880470.00</td>\n",
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       "    <tr>\n",
       "      <th>2021-05-25</th>\n",
       "      <td>420.329987</td>\n",
       "      <td>420.709991</td>\n",
       "      <td>417.619995</td>\n",
       "      <td>418.239990</td>\n",
       "      <td>57365100</td>\n",
       "      <td>413.821997</td>\n",
       "      <td>415.794498</td>\n",
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       "      <td>370.597571</td>\n",
       "      <td>79183570.00</td>\n",
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       "    <tr>\n",
       "      <th>2021-05-26</th>\n",
       "      <td>418.869995</td>\n",
       "      <td>419.609985</td>\n",
       "      <td>417.760010</td>\n",
       "      <td>419.070007</td>\n",
       "      <td>40093573</td>\n",
       "      <td>415.187997</td>\n",
       "      <td>415.877998</td>\n",
       "      <td>409.381901</td>\n",
       "      <td>371.034286</td>\n",
       "      <td>78626303.65</td>\n",
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       "<p>252 rows × 10 columns</p>\n",
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      ],
      "text/plain": [
       "                  open        high         low       close     volume  \\\n",
       "date                                                                    \n",
       "2020-05-28  299.841556  301.996993  297.469591  298.188080   90405200   \n",
       "2020-05-29  297.686126  300.146668  294.743328  299.516785  119090800   \n",
       "2020-06-01  298.827795  301.376912  298.276636  300.727325   55758300   \n",
       "2020-06-02  301.711527  303.266606  300.284431  303.217377   74267200   \n",
       "2020-06-03  305.343334  308.276310  305.048081  307.252716   92567600   \n",
       "...                ...         ...         ...         ...        ...   \n",
       "2021-05-20  411.799988  416.630005  411.670013  415.279999   78022200   \n",
       "2021-05-21  416.869995  418.200012  414.450012  414.940002   76519100   \n",
       "2021-05-24  417.339996  420.320007  417.079987  419.170013   51376700   \n",
       "2021-05-25  420.329987  420.709991  417.619995  418.239990   57365100   \n",
       "2021-05-26  418.869995  419.609985  417.760010  419.070007   40093573   \n",
       "\n",
       "                sma_10      sma_20      sma_50     sma_200   vol_sma_20  \n",
       "date                                                                     \n",
       "2020-05-28  290.447211  286.368619  270.969386  292.811961  95713570.00  \n",
       "2020-05-29  292.351669  287.049696  272.263101  292.891848  95523025.00  \n",
       "2020-06-01  294.248248  288.169734  273.571046  293.019705  92051940.00  \n",
       "2020-06-02  295.535602  289.375888  275.131618  293.156378  91721640.00  \n",
       "2020-06-03  297.524707  290.654878  276.888051  293.292875  92371525.00  \n",
       "...                ...         ...         ...         ...          ...  \n",
       "2021-05-20  414.013995  415.770496  407.448546  369.283551  78755260.00  \n",
       "2021-05-21  413.295996  415.680496  407.902440  369.716719  78920755.00  \n",
       "2021-05-24  413.418997  415.758498  408.430369  370.160063  78880470.00  \n",
       "2021-05-25  413.821997  415.794498  408.892851  370.597571  79183570.00  \n",
       "2021-05-26  415.187997  415.877998  409.381901  371.034286  78626303.65  \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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       "  <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>2021-05-20</th>\n",
       "      <td>414.013995</td>\n",
       "      <td>415.770496</td>\n",
       "      <td>407.448546</td>\n",
       "      <td>369.283551</td>\n",
       "      <td>78755260.00</td>\n",
       "      <td>413.742619</td>\n",
       "      <td>413.623932</td>\n",
       "      <td>407.207921</td>\n",
       "      <td>0.010758</td>\n",
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       "    <tr>\n",
       "      <th>2021-05-21</th>\n",
       "      <td>413.295996</td>\n",
       "      <td>415.680496</td>\n",
       "      <td>407.902440</td>\n",
       "      <td>369.716719</td>\n",
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       "      <td>414.008705</td>\n",
       "      <td>413.743574</td>\n",
       "      <td>407.511140</td>\n",
       "      <td>-0.000819</td>\n",
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       "    <tr>\n",
       "      <th>2021-05-24</th>\n",
       "      <td>413.418997</td>\n",
       "      <td>415.758498</td>\n",
       "      <td>408.430369</td>\n",
       "      <td>370.160063</td>\n",
       "      <td>78880470.00</td>\n",
       "      <td>415.155662</td>\n",
       "      <td>414.236887</td>\n",
       "      <td>407.968350</td>\n",
       "      <td>0.010194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-25</th>\n",
       "      <td>413.821997</td>\n",
       "      <td>415.794498</td>\n",
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       "      <td>-0.002219</td>\n",
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       "    <tr>\n",
       "      <th>2021-05-26</th>\n",
       "      <td>415.187997</td>\n",
       "      <td>415.877998</td>\n",
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       "      <td>371.034286</td>\n",
       "      <td>78626303.65</td>\n",
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       "      <td>415.007097</td>\n",
       "      <td>408.790723</td>\n",
       "      <td>0.001985</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",
       "2021-05-20  414.013995  415.770496  407.448546  369.283551  78755260.00   \n",
       "2021-05-21  413.295996  415.680496  407.902440  369.716719  78920755.00   \n",
       "2021-05-24  413.418997  415.758498  408.430369  370.160063  78880470.00   \n",
       "2021-05-25  413.821997  415.794498  408.892851  370.597571  79183570.00   \n",
       "2021-05-26  415.187997  415.877998  409.381901  371.034286  78626303.65   \n",
       "\n",
       "                 EMA_8      EMA_21      EMA_50  PCTRET_1  \n",
       "date                                                      \n",
       "2021-05-20  413.742619  413.623932  407.207921  0.010758  \n",
       "2021-05-21  414.008705  413.743574  407.511140 -0.000819  \n",
       "2021-05-24  415.155662  414.236887  407.968350  0.010194  \n",
       "2021-05-25  415.841068  414.600805  408.371160 -0.002219  \n",
       "2021-05-26  416.558610  415.007097  408.790723  0.001985  "
      ]
     },
     "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",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TS_Trends</th>\n",
       "      <th>TS_Trades</th>\n",
       "      <th>TS_Entries</th>\n",
       "      <th>TS_Exits</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-05-20</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-21</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-24</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-25</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-26</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            TS_Trends  TS_Trades  TS_Entries  TS_Exits\n",
       "date                                                  \n",
       "2021-05-20          1          1           1         0\n",
       "2021-05-21          1          0           0         0\n",
       "2021-05-24          1          0           0         0\n",
       "2021-05-25          1          0           0         0\n",
       "2021-05-26          1          0           0         0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trendy = asset.ta.tsignals(long, asbool=False, append=True)\n",
    "trendy.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trend Entries & Exits & Trade Table\n",
    "This is a simple way to reduce the Asset DataFrame to a Trade Table with Dates, Signals, and Entries and Exits. Gives you an idea what to expect before running through a backtester such as [**vectorbt**](https://github.com/polakowo/vectorbt)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current Trade:\n",
      "Price Entry | Last:\t415.2800 | 419.0700\n",
      "Unrealized PnL | %:\t3.7900 | 0.9126%\n",
      "\n",
      "Trades Total | Round Trip:\t9 | 4\n",
      "Trade Coverage: 78.57%\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>2020-07-06</th>\n",
       "      <td>1</td>\n",
       "      <td>313.419037</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>410.859985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-20</th>\n",
       "      <td>1</td>\n",
       "      <td>415.279999</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Signal       Entry        Exit\n",
       "date                                      \n",
       "2020-07-06       1  313.419037         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  410.859985\n",
       "2021-05-20       1  415.279999         NaN"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entries = trendy.TS_Entries * asset.close\n",
    "entries = entries[~np.isclose(entries, 0)]\n",
    "entries.dropna(inplace=True)\n",
    "entries.name = \"Entry\"\n",
    "\n",
    "exits = trendy.TS_Exits * asset.close\n",
    "exits = exits[~np.isclose(exits, 0)]\n",
    "exits.dropna(inplace=True)\n",
    "exits.name = \"Exit\"\n",
    "\n",
    "total_trades = trendy.TS_Trades.abs().sum()\n",
    "rt_trades = int(trendy.TS_Trades.abs().sum() // 2)\n",
    "\n",
    "all_trades = trendy.TS_Trades.copy().fillna(0)\n",
    "all_trades = all_trades[all_trades != 0]\n",
    "\n",
    "trades = pd.DataFrame({\n",
    "    \"Signal\": all_trades,\n",
    "    entries.name: entries,\n",
    "    exits.name: exits\n",
    "})\n",
    "\n",
    "# Show some stats if there is an active trade (when there is an odd number of round trip trades)\n",
    "if total_trades % 2 != 0:\n",
    "    unrealized_pnl = asset.close.iloc[-1] - entries.iloc[-1]\n",
    "    unrealized_pnl_pct_change = 100 * ((asset.close.iloc[-1] / entries.iloc[-1]) - 1)\n",
    "    print(\"Current Trade:\")\n",
    "    print(f\"Price Entry | Last:\\t{entries.iloc[-1]:.4f} | {asset.close.iloc[-1]:.4f}\")\n",
    "    print(f\"Unrealized PnL | %:\\t{unrealized_pnl:.4f} | {unrealized_pnl_pct_change:.4f}%\")\n",
    "print(f\"\\nTrades Total | Round Trip:\\t{total_trades} | {rt_trades}\")\n",
    "print(f\"Trade Coverage: {100 * asset.TS_Trends.sum() / asset.shape[0]:.2f}%\")\n",
    "\n",
    "trades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Chart Display Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "extime = ta.get_time(to_string=True)\n",
    "first_date, last_date = asset.index[0], asset.index[-1]\n",
    "f_date = f\"{first_date.day_name()} {first_date.month}-{first_date.day}-{first_date.year}\"\n",
    "l_date = f\"{last_date.day_name()} {last_date.month}-{last_date.day}-{last_date.year}\"\n",
    "last_ohlcv = f\"Last OHLCV: ({asset.iloc[-1].open:.4f}, {asset.iloc[-1].high:.4f}, {asset.iloc[-1].low:.4f}, {asset.iloc[-1].close:.4f}, {int(asset.iloc[-1].volume)})\"\n",
    "ptitle = f\"\\n{ticker} [{tf} for {duration}({recent} bars)] from {f_date} to {l_date}\\n{last_ohlcv}\\n{extime}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Trade Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'\\nSPY [D for 1y(252 bars)] from Thursday 5-28-2020 to Wednesday 5-26-2021\\nLast OHLCV: (418.8700, 419.6100, 417.7600, 419.0700, 40093573)\\nWednesday May 26, 2021, NYSE: 10:58:34, Local: 14:58:34 PDT, Day 146/365 (40.00%)'}, 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 0x12d5dbe20>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "asset[\"ACTRET_1\"] = trendy.TS_Trends.shift(1) * asset.PCTRET_1\n",
    "asset[[\"PCTRET_1\", \"ACTRET_1\"]].plot(figsize=(16, 3), color=colors(\"GyOr\"), alpha=1, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Buy and Hold Returns (*PCTRET_1*) vs. Cum. Active Returns (*ACTRET_1*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x12d8ad940>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "((asset[[\"PCTRET_1\", \"ACTRET_1\"]] + 1).cumprod() - 1).plot(figsize=(16, 3), kind=\"area\", stacked=False, color=colors(\"GyOr\"), title=\"B&H vs. Cum. Active Returns\", alpha=.4, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Disclaimer\n",
    "* All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.\n",
    "\n",
    "* Any opinions, news, research, analyses, prices, or other information offered is provided as general market commentary, and does not constitute investment advice. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from use of or reliance on such information."
   ]
  }
 ],
 "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
}