{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Strategy Analysis with **Pandas TA** and AI/ML\n",
    "* This is a **Work in Progress** and subject to change!\n",
    "* Contributions are welcome and accepted!\n",
    "* Examples below are for **educational purposes only**.\n",
    "* **NOTE:** The **watchlist** module is independent of Pandas TA. To easily use it, copy it from your local pandas_ta installation directory into your project directory."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Required Packages\n",
    "##### Uncomment the packages you need to install or are missing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip install numpy\n",
    "#!pip install pandas\n",
    "#!pip install mplfinance\n",
    "#!pip install pandas-datareader\n",
    "#!pip install requests_cache\n",
    "#!pip install tqdm\n",
    "#!pip install alphaVantage-api # Required for Watchlist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n",
      "Numpy v1.20.2\n",
      "Pandas v1.2.4\n",
      "mplfinance v0.12.7a12\n",
      "\n",
      "Pandas TA v0.2.74b0\n",
      "To install the Latest Version:\n",
      "$ pip install -U git+https://github.com/twopirllc/pandas-ta\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "import datetime as dt\n",
    "import random as rnd\n",
    "from sys import float_info as sflt\n",
    "\n",
    "from tqdm import tqdm\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "pd.set_option(\"max_rows\", 100)\n",
    "pd.set_option(\"max_columns\", 20)\n",
    "\n",
    "import mplfinance as mpf\n",
    "import pandas_ta as ta\n",
    "\n",
    "from tqdm.notebook import trange, tqdm\n",
    "\n",
    "from watchlist import colors, Watchlist # Is this failing? If so, copy it locally. See above.\n",
    "\n",
    "print(f\"Numpy v{np.__version__}\")\n",
    "print(f\"Pandas v{pd.__version__}\")\n",
    "print(f\"mplfinance v{mpf.__version__}\")\n",
    "print(f\"\\nPandas TA v{ta.version}\\nTo install the Latest Version:\\n$ pip install -U git+https://github.com/twopirllc/pandas-ta\\n\")\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MISC Function(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def recent_bars(df, tf: str = \"1y\"):\n",
    "    # All Data: 0, Last Four Years: 0.25, Last Two Years: 0.5, This Year: 1, Last Half Year: 2, Last Quarter: 4\n",
    "    yearly_divisor = {\"all\": 0, \"10y\": 0.1, \"5y\": 0.2, \"4y\": 0.25, \"3y\": 1./3, \"2y\": 0.5, \"1y\": 1, \"6mo\": 2, \"3mo\": 4}\n",
    "    yd = yearly_divisor[tf] if tf in yearly_divisor.keys() else 0\n",
    "    return int(ta.RATE[\"TRADING_DAYS_PER_YEAR\"] / yd) if yd > 0 else df.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Collection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[!] Loading All: SPY, QQQ, AAPL, TSLA, BTC-USD\n",
      "[+] Downloading[yahoo]: SPY[D]\n",
      "[+] Saving: /Users/kj/av_data/SPY_D.csv\n",
      "[i] Runtime: 514.4232 ms (0.5144 s)\n",
      "[+] Downloading[yahoo]: QQQ[D]\n",
      "[+] Saving: /Users/kj/av_data/QQQ_D.csv\n",
      "[i] Runtime: 1018.9260 ms (1.0189 s)\n",
      "[+] Downloading[yahoo]: AAPL[D]\n",
      "[+] Saving: /Users/kj/av_data/AAPL_D.csv\n",
      "[i] Runtime: 549.0323 ms (0.5490 s)\n",
      "[+] Downloading[yahoo]: TSLA[D]\n",
      "[+] Saving: /Users/kj/av_data/TSLA_D.csv\n",
      "[i] Runtime: 560.7261 ms (0.5607 s)\n",
      "[+] Downloading[yahoo]: BTC-USD[D]\n",
      "[+] Saving: /Users/kj/av_data/BTC-USD_D.csv\n",
      "[i] Runtime: 560.1060 ms (0.5601 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 (7116, 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": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>sma_10</th>\n",
       "      <th>sma_20</th>\n",
       "      <th>sma_50</th>\n",
       "      <th>sma_200</th>\n",
       "      <th>vol_sma_20</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>2020-05-04</th>\n",
       "      <td>276.308950</td>\n",
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       "      <td>1.261295e+08</td>\n",
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       "    <tr>\n",
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       "      <td>282.115822</td>\n",
       "      <td>284.684613</td>\n",
       "      <td>279.232045</td>\n",
       "      <td>281.672913</td>\n",
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       "      <td>280.518433</td>\n",
       "      <td>276.816301</td>\n",
       "      <td>268.688249</td>\n",
       "      <td>292.679706</td>\n",
       "      <td>1.207049e+08</td>\n",
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       "    <tr>\n",
       "      <th>2020-05-06</th>\n",
       "      <td>283.493739</td>\n",
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       "      <td>279.763550</td>\n",
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       "      <td>281.025305</td>\n",
       "      <td>277.757211</td>\n",
       "      <td>268.165192</td>\n",
       "      <td>292.634901</td>\n",
       "      <td>1.143152e+08</td>\n",
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       "    <tr>\n",
       "      <th>2020-05-07</th>\n",
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       "      <td>1.103890e+08</td>\n",
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       "      <th>2020-05-08</th>\n",
       "      <td>286.495581</td>\n",
       "      <td>288.326240</td>\n",
       "      <td>285.284984</td>\n",
       "      <td>287.824280</td>\n",
       "      <td>76452400</td>\n",
       "      <td>282.803787</td>\n",
       "      <td>279.129703</td>\n",
       "      <td>267.666591</td>\n",
       "      <td>292.574995</td>\n",
       "      <td>1.047116e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2021-04-27</th>\n",
       "      <td>417.929993</td>\n",
       "      <td>418.140015</td>\n",
       "      <td>416.299988</td>\n",
       "      <td>417.519989</td>\n",
       "      <td>51303100</td>\n",
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       "      <td>410.370996</td>\n",
       "      <td>397.164135</td>\n",
       "      <td>361.136033</td>\n",
       "      <td>7.178964e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-28</th>\n",
       "      <td>417.809998</td>\n",
       "      <td>419.010010</td>\n",
       "      <td>416.899994</td>\n",
       "      <td>417.399994</td>\n",
       "      <td>51238900</td>\n",
       "      <td>415.811996</td>\n",
       "      <td>411.504495</td>\n",
       "      <td>397.691748</td>\n",
       "      <td>361.666862</td>\n",
       "      <td>7.053848e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-29</th>\n",
       "      <td>420.320007</td>\n",
       "      <td>420.720001</td>\n",
       "      <td>416.440002</td>\n",
       "      <td>420.059998</td>\n",
       "      <td>78544300</td>\n",
       "      <td>416.230997</td>\n",
       "      <td>412.690996</td>\n",
       "      <td>398.270767</td>\n",
       "      <td>362.190824</td>\n",
       "      <td>6.882898e+07</td>\n",
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       "    <tr>\n",
       "      <th>2021-04-30</th>\n",
       "      <td>417.630005</td>\n",
       "      <td>418.540009</td>\n",
       "      <td>416.339996</td>\n",
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       "      <td>398.827877</td>\n",
       "      <td>362.686503</td>\n",
       "      <td>6.811726e+07</td>\n",
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       "    <tr>\n",
       "      <th>2021-05-03</th>\n",
       "      <td>419.429993</td>\n",
       "      <td>419.839996</td>\n",
       "      <td>417.665009</td>\n",
       "      <td>418.200012</td>\n",
       "      <td>63554369</td>\n",
       "      <td>416.533997</td>\n",
       "      <td>414.117497</td>\n",
       "      <td>399.416743</td>\n",
       "      <td>363.191922</td>\n",
       "      <td>6.671073e+07</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  open        high         low       close    volume  \\\n",
       "date                                                                   \n",
       "2020-05-04  276.308950  279.419078  274.724375  279.094299  80873200   \n",
       "2020-05-05  282.115822  284.684613  279.232045  281.672913  79569900   \n",
       "2020-05-06  283.493739  283.907093  279.300967  279.763550  73632600   \n",
       "2020-05-07  283.208307  285.206265  282.598097  283.139404  75250400   \n",
       "2020-05-08  286.495581  288.326240  285.284984  287.824280  76452400   \n",
       "...                ...         ...         ...         ...       ...   \n",
       "2021-04-27  417.929993  418.140015  416.299988  417.519989  51303100   \n",
       "2021-04-28  417.809998  419.010010  416.899994  417.399994  51238900   \n",
       "2021-04-29  420.320007  420.720001  416.440002  420.059998  78544300   \n",
       "2021-04-30  417.630005  418.540009  416.339996  417.299988  85448400   \n",
       "2021-05-03  419.429993  419.839996  417.665009  418.200012  63554369   \n",
       "\n",
       "                sma_10      sma_20      sma_50     sma_200    vol_sma_20  \n",
       "date                                                                      \n",
       "2020-05-04  279.224188  275.766634  269.364310  292.711427  1.261295e+08  \n",
       "2020-05-05  280.518433  276.816301  268.688249  292.679706  1.207049e+08  \n",
       "2020-05-06  281.025305  277.757211  268.165192  292.634901  1.143152e+08  \n",
       "2020-05-07  281.871735  278.428940  267.732156  292.596652  1.103890e+08  \n",
       "2020-05-08  282.803787  279.129703  267.666591  292.574995  1.047116e+08  \n",
       "...                ...         ...         ...         ...           ...  \n",
       "2021-04-27  415.216998  410.370996  397.164135  361.136033  7.178964e+07  \n",
       "2021-04-28  415.811996  411.504495  397.691748  361.666862  7.053848e+07  \n",
       "2021-04-29  416.230997  412.690996  398.270767  362.190824  6.882898e+07  \n",
       "2021-04-30  416.234995  413.525496  398.827877  362.686503  6.811726e+07  \n",
       "2021-05-03  416.533997  414.117497  399.416743  363.191922  6.671073e+07  \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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       "      <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",
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       "      <td>399.521651</td>\n",
       "      <td>-0.000216</td>\n",
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       "    <tr>\n",
       "      <th>2021-04-28</th>\n",
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       "      <td>-0.000287</td>\n",
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       "    <tr>\n",
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       "      <td>411.279275</td>\n",
       "      <td>401.000693</td>\n",
       "      <td>0.006373</td>\n",
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       "      <td>-0.006571</td>\n",
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       "      <th>2021-05-03</th>\n",
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       "      <td>66710733.45</td>\n",
       "      <td>417.156067</td>\n",
       "      <td>412.406012</td>\n",
       "      <td>402.289298</td>\n",
       "      <td>0.002157</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",
       "2021-04-27  415.216998  410.370996  397.164135  361.136033  71789640.00   \n",
       "2021-04-28  415.811996  411.504495  397.691748  361.666862  70538475.00   \n",
       "2021-04-29  416.230997  412.690996  398.270767  362.190824  68828980.00   \n",
       "2021-04-30  416.234995  413.525496  398.827877  362.686503  68117255.00   \n",
       "2021-05-03  416.533997  414.117497  399.416743  363.191922  66710733.45   \n",
       "\n",
       "                 EMA_8      EMA_21      EMA_50  PCTRET_1  \n",
       "date                                                      \n",
       "2021-04-27  415.317718  409.701323  399.521651 -0.000216  \n",
       "2021-04-28  415.780446  410.401203  400.222762 -0.000287  \n",
       "2021-04-29  416.731457  411.279275  401.000693  0.006373  \n",
       "2021-04-30  416.857798  411.826612  401.639881 -0.006571  \n",
       "2021-05-03  417.156067  412.406012  402.289298  0.002157  "
      ]
     },
     "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": [
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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>2021-04-27</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-28</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-29</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-04-30</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-05-03</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",
       "2021-04-27          1          0           0         0\n",
       "2021-04-28          1          0           0         0\n",
       "2021-04-29          1          0           0         0\n",
       "2021-04-30          1          0           0         0\n",
       "2021-05-03          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:\t388.3082 | 418.2000\n",
      "Unrealized PnL | %:\t29.8918 | 7.6980%\n",
      "\n",
      "Trades Total | Round Trip:\t7 | 3\n",
      "Trade Coverage: 81.35%\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>2020-06-02</th>\n",
       "      <td>1</td>\n",
       "      <td>303.217377</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Signal       Entry        Exit\n",
       "date                                      \n",
       "2020-06-02       1  303.217377         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"
      ]
     },
     "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 Monday 5-4-2020 to Monday 5-3-2021\\nLast OHLCV: (419.4300, 419.8400, 417.6650, 418.2000, 63554369)\\nMonday May 3, 2021, NYSE: 12:02:17, Local: 16:02:17 PDT, Day 123/365 (34.00%)'}, 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": "iVBORw0KGgoAAAANSUhEUgAAA6AAAACKCAYAAAC0Gid8AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Z1A+gAAAACXBIWXMAAAsTAAALEwEAmpwYAAAdwUlEQVR4nO3de3Scd33n8fdXsuWa2NhjHGwSNnaSUlgcoE0MKXBonTahbCENhWUL9BTSQlJgoTdKLylhuW6X08tpod22Pk2htAdCSkoKaWp6mhMHSMNFkwvlEpzECdgJWztoLGJjhC19949nRh7J0li2Hs0zGr1f5+TEmmc087Xm459+3+fyeyIzkSRJkiRpoQ1UXYAkSZIkaWmwAZUkSZIkdYUNqCRJkiSpK2xAJUmSJEldYQMqSZIkSeoKG1BJkiRJUlcsK+NFIuJvgBcB+zLzvBM9f/369bl58+Yy3npeDh06xGmnnVZ1GepR5kNzYU7UiflQJ+ZD7cyDOlmM+ajX649k5unTHy+lAQU+CPwZ8KG5PHnz5s0MDw+X9NanbufOnWzbtq3qMtSjzIfmwpyoE/OhTsyH2pkHdbIY8xER35jp8VJOwc3MTwMjZbyWqrd7924++clPVl2GpD5z8803c/fdd1ddRk8ZHh7ms5/9bNVlSOoz119/PXv27Km6DGlGkZnlvFDEZuDG2U7BjYgrgSsBNmzYcMG1115byvvOx8GDB1m1alXVZfSc973vfdx0003s2LGj6lIqZT40F+ZkbjKTl770pZx33nm8853vrLqcrjlRPt7ylrcwOjrK9u3bu1iVeoXjh9qVlYfx8XGe//zn8/KXv5wrrriihMrUCxbjeHHRRRfVM3Pr9MfLOgX3hDJzO7AdYOvWrdkLh5AX46Hsbti+fTtjY2NceOGFrFy5supyKmM+NBfmZG727t1Lo9EgIpbUz+tE+RgfH2dsbGxJ/Ux0jOOH2pWVh/379zMxMcGqVavMVx/pp/HCVXB1nEajMeX/kjRf9XodcFyZrtFo+DORVCrncep1NqA6jgOXpLLZgM6s0Wjw6KOPcvTo0apLkdQnnMep15XSgEbER4DbgSdHxN6IeE0Zr6tqOHBJKltr5XPHlWPGx8cZHR0F4MCBA9UWI6lvOI9TryvlGtDMfEUZr6Pe4MAlqUyZOXkE9NChQxw5coTly5dXXFX1Ws0nFOPt+vXrK6xGUr9wHqde5ym4miIzHbgkleqhhx5i3759POUpTwEcW1rafw7+TCSVxXmcep0NqKY4dOjQ5LVIDlySytA6+nnxxRcDji0tNqCSFkJrPDlw4AATExMVVyMdzwZUUzghklS24eFhBgYGJpePd2wpON5KWgit8SQz+c53vlNxNdLxbEA1hRMiSWWr1+ts2bKFM888E3BsaXG8lbQQHFvU62xANYWDlqQytRYguuCCC6jVagCMjIxUXFVvcLyVtBDax1jHW/UiG1BN0ZoEDQ4OOiGSNG979+5l3759UxpQx5aC462khdBoNBgcHJz8s9RrbEA1RWugOuussxy0JM1bawGirVu32oBO02g0GBoa4vGPf7w/E0mlaTQanHXWWZN/lnqNDaimaA1U5557roOWpHmr1+sMDg7yjGc8g+XLl3Paaac5tjQ1Gg3WrVvHunXr/JlIKk2j0eDcc8+d/LPUa2xANcXIyAgDAwNs2rTJ6wYkzVu9XuepT30qK1euBKBWqzkhahoZGaFWq1Gr1RxvJZXGBlS9zgZUUzQaDdauXeseeUnzlpkMDw+zdevWycdsQI9pNBqTDag/E0llOHLkCAcPHuSMM85gaGjIsUU9yQZUU7RPiMbGxjh8+HDVJUlapPbu3cv+/fu54IILJh+z2TrGBlRS2Q4cOADg2KKeZgOqKdonRK2vJelUtBYgam9APbviGBtQSWVrjSWOLeplNqCawgZUUlmGh4cnFyBqcUJ0TPt4++ijj3L06NGqS5K0yNmAajGwAdUUNqCSylKv19myZcvkAkRgA9oyPj7O6OjolPG2deqcJJ0qG1AtBjagmsIGVFIZMpN6vT7l9FsoJkWHDh3i+9//fkWV9YbR0VEAx1tJpWqtqL1u3TpX2FbPsgHVpMy0AZVUipkWIAIcW5qmH6Vof0ySTpVHQLUY2IBq0qFDhzh69KgTIknzNjw8DDDlFixgA9piAyppIUwfW0ZHR5mYmKi4KmkqG1BNah+01q5dO+UxSToZ9XqdwcFBnv70p0953GarYAMqaSE0Gg0e85jHMDQ0RK1WIzMnT/mXeoUNqCa1Jj/r1q1jcHCQNWvWOCGSdEpmWoAIbEBb2sfbdevWTXlMkk5V61IqwLFFPcsGVJPa98i3/u+gJelkZSbDw8PHnX4LNqAtHgGVtBDaG1DHFvUqG1BNsgGVVIY9e/bwyCOPHLcAEbhHvqV9vF2xYgUrV65c8j8TSfNnA6rFwAZUk1pLdbcPXC7fLelk1et1gBkbUK8vL4yMjEw2nuB4K6kcjUZjckefDah6lQ2oJnkEVFIZ6vU6y5YtO24BIoDly5ezatWqJT+2tB+lAMdbSeXwCKgWAxtQTWo0GgwMDLB69WrACZGkUzM8PDzjAkQtHu2zAZW0MEZGRo5rQJf6eKveYwOqSY1Gg7Vr1zIwUMTCCZGkk5WZ1Ov1GU+/bXFssQGVVL4jR45w6NChybFl5cqVDA0NObao55TSgEbECyLi6xFxX0T8Thmvqe6baUI0NjbG4cOHK6xK0mLSWoBophVwW2y2bEAllW/6pVQR4diinrRsvi8QEYPAnwOXAHuBL0bEJzLzq/N97SocPnyYvXv3Vl1GJR5++OHjJkQAd955J6effnpVZVVm79693HvvvVWXoR5Xdk42bNjAYx/72Fm3HzlyhAcffLC09yvbzTffDMy8AFFLrVbjq1/96qL997Vp0yaGhoYmv967d++sO+pmy8f+/fvZsmXL5Net05IX689Ep8bfM2rXysPmzZtZvnz55OPf/OY3GRsbO+H3t343TJ/L7dmzx5z1genjxeDgIOecc06FFZ26eTegwLOA+zJzN0BEXAtcBizKBvTuu+/m2c9+dtVlVOaFL3zh5J83btwIwHOf+9yqypGWnCc96Uns2rVr1u2vf/3rueaaa7pY0clbsWLFjAsQtWzcuJEbbriBH/qhH+piVeV5xStewYc//GEAdu7cyUUXXXRKr7Nhw4bJP2/cuJGDBw8u2p+JpPJcccUVbN++HYAbb7yRSy+99KS+f/rYsmPHDseWPrR+/Xr2799fdRmnpIwG9ExgT9vXe4ELpz8pIq4EroTiH8bOnTtLeOv5OXjw4HF1jI6OctVVV1VTUA942tOeNvkzOe2003jHO94xp71u/WhsbIwVK1ZUXYZ6XJk5ufXWW7n99tu55ZZbiIgZn7Njxw62bNnCZZddVsp7LoQzzjiDz33uc7Nuv+SSS3jc4x5HZnaxqnJ89KMf5a677pocJ2+66SYA3vjGN8545Hq2fEQEz3zmMydf57zzzuPqq69mfHx8wWpX7/H3jNqNjY1x3XXXUa/XJ8eGHTt2APDmN795TllZuXIlETH5/a997Wt5znOes1Alq4umjxdDQ0M90U+dijIa0DnJzO3AdoCtW7fmtm3buvXWs9q5cycz1dHLE7tuu+SSS6ouoTKz5UNqV2ZO/uAP/oDbbruNrVu3Tq5G3e7AgQM89NBDvOENb1j0O8pe8pKXVF3CKbn//vu58847Jz/z1j1P3/Oe98zYgJ5MPl70oheVVaYWCX/PqN3OnTu55557+Na3vjWZi1aD8d73vpfBwcHqilPl+mm8KGMRooeA/9L29RObj0mSTsKJ7tl2xx13AJ2vr9TCmr6gR6PRYHBwcMYdBpJ0smYaY9asWWPzqb5SRgP6ReBJEXF2RAwBLwc+UcLrStKScqIGtHW0zQa0Oq3JYev04dbtq2Y7ZVqSTsZMDWj7okJSP5h3A5qZR4E3Ap8CvgZcl5lfme/rStJSM5cGdNOmTaxfv76bZalNrVbj6NGjHDp0CJh603dJmq9arcbo6CgTExOADaj6UynXgGbmTcBNZbyWJC1VJ2pAh4eHPfpZsfbPaNWqVU4OJZWqVquRmYyOjk4eDXWMUb8p4xRcSVIJWpOMkZGR47YdOHCA+++/3wa0YtM/IyeHkso0fYzxLAv1IxtQSeoRnY6AthYg2rp1a1dr0lTTPyMbUEllcozRUmADKkk9YvXq1QwMDMzYgA4PDwMuQFQ1J4eSFpJjjJYCG1BJ6hEDAwOsXbt2xga0tQDR4x73uAoqU0v75DAznRxKKlX7GHP48GHGxsYcY9R3bEAlqYesW7du1gbU02+rt27dOqCYHB48eJDx8fHJxyRpvtob0NbvAhtQ9RsbUEnqIdPvAQfFRMQFiHrD6tWrGRwcpNFoTC4S4uRQUllsQLUU2IBKUg+ZqQFtLUBkA1q9iJg8TdrJoaSyrVy5kqGhIccY9TUbUEnqITM1oPV6HbAB7RWtz8jJoaSyRYRjjPqeDagk9ZDZGtDNmze7AFGPcHIoaSG11gJojTFeZ65+YwMqST2k1dxk5uRjw8PDHv3sITagkhaSY4z6nQ2oJPWQWq3G+Pg4Bw8eBIqFKHbv3u0KuD3EyaGkhTR9jFmzZk3FFUnlsgGVpB4y/SbkLkDUe2q1GiMjIzQaDQYHB1m9enXVJUnqI60xZmRkhDVr1jA4OFh1SVKpbEAlqYdMb0CHh4cBOP/88yurSVO1jk6MjIywdu1aIqLqkiT1kfYjoJ5hoX5kAypJPaQ12WjdY9IFiHpP6zTpPXv2ODmUVLparcbo6Cjf/va3HWPUl2xAJamHtFY7bB0BrdfrXv/ZY1qf0e7du12dUlLpWk3ngw8+aAOqvmQDKkk9pP0U3JGREXbv3u31nz2m9Rk98MADTg4llc4xRv3OBlSSekh7A+oCRL2p9Rl973vfc3IoqXSOMep3NqCS1ENWr17N4OAgjUaDer0O2ID2mvYJoZNDSWVzjFG/W1Z1AZKkYyKCtWvX0mg02LVrF2effbbXGfYYJ4eSFpJjjPqdR0Alqce0luCv1+se/exBTg4lLSTHGPU7G1BJ6jG1Wo3du3fzwAMPuAJuD2qdJg1ODiWVzwZU/c4GVJJ6TK1WY3h4GPD6z17UOk0anBxKKt/KlSsZGhoCHGPUn2xAJanH1Go1JiYmADj//PMrrkYzaU0KnRxKKltETF777xoA6kc2oJLUY1oTjnPOOcfJR49ycihpIbmTS/1sXg1oRLwsIr4SERMR4YVKklSC1oTD0297l5NDSQvJMUb9bL5HQL8MvAT4dAm1SJKwAV0MnBxKWkitsWXNmjUVVyKVb173Ac3Mr0FxrrokqRw2oL2vVqsxODjIqlWrqi5FUh+q1WqsWbNmcsVtqZ9EZs7/RSJ2Ar+ZmcMdnnMlcCXAhg0bLrj22mvn/b7zdfDgQScPmpX50FwsRE727dvHhz70Id70pjexYsWKUl9b5fjSl77EHXfcweWXX97xeY4j6sR8qF17HoaHh9m1axevfOUrK65KvWIxjhcXXXRRPTOPu0zzhA1oRPwbsHGGTb+Xmf/UfM5OTtCAttu6dWu2bjFQpZ07d7Jt27aqy1CPMh+aC3OiTsyHOjEfamce1MlizEdEzNiAnvAU3My8eGFKkiRJkiQtJfO6BvRU1ev1RyLiG1W89zTrgUeqLkI9y3xoLsyJOjEf6sR8qJ15UCeLMR+bZnpwXteARsTPAu8HTgcOAHdl5k+d8gt2WUQMz3RYWALzobkxJ+rEfKgT86F25kGd9FM+5rsK7seBj5dUiyRJkiSpj833PqCSJEmSJM3JUm9At1ddgHqa+dBcmBN1Yj7UiflQO/OgTvomH6XcB1SSJEmSpBNZ6kdAJUmSJEldYgMqSZIkSeoKG1BJOoGIiKprkCQtfv4+kZZAAxoRZ1Zdg3pXRPxMRJxbdR2SJGlJmLwFos2o2kXEkyOi73sz6OMGNCIujog68Lqqa1HvaebjduAa4AlV16PeFBGXRsRHgN+JiE1V16PeEhEvjoh3VV2HepP5ULuIeEFEfAr4w4j4WYB0JVABEXFJRHweeC193Ju1W3bipywezT1Jy4E/AZ4DvD0zb2jf7j/2pauZj9OAjwCrgbcCvwZsAj4bEQOZOVFdheolEXExcDXwNuCZwJsi4pbM/GezsrQ191D/EvA7wKaI+NfM/EzFZakHNH/PDAC/iPlY8trmpf8beDbwXuCJwMsi4suZeW+V9ak6zWwso5hnvAL47cz8x/bt/dyz9FWXnYXvA48BbsjMGyJiICKe0dpebYWqUjMfB4G/z8xtmXkz8CngsuZ2Gwq1uxi4MTN3AH9FsdPilyLiNLOytDU//3uBHwHeAHiUS8Dk75lx4D7Mx5LXNi/dAfx4Zn4C+HfgCPBApcWpUs1sHAEmgI+1ms+IeF5ELK+2uoXXF/cBjYhfAc4A7szMjzav6dsO3EkxidwDfAu4PjM/VV2lqkJbPuqZ+Q9tjw9Q7HU6H7gqM8cqKlE9oC0nd2TmdRHxM8D/BC7LzO9FxJ9SHC2/OTPfX2Wt6r6I+O/Ansz8fPPr5c3JAxHxReAvM/Maj44vTc3x42nA5zPzr9uPXpiPpWd6Htoe/2ngz4B9wKcp5iUf7fejXTqmLRtfzMztEbER+D9AAluBB4EGcGtzzOjLbCzqI6BR+HXg54Bh4O0R8ZrMvB+4AXhKc9srgS8DPxsR66uqV901Qz7eGRGXR8TpMHkU4wHghTafS9cMOXlHRLwauAd4GLguIm4BHgv8E7B6qSwSIIiIx0fErcD7gN9t++yPtv35bcBvRETN5mLpiYjLKeYZ1wO/EBG/C5zT9hTzsYTMkIerIuIHm5sfAV6QmT8K3EJxVs3mfmwwdLxp2fj5iHgrMEbRswwBLwN+prn9JRFxVr9mY1FPopofykXAWzPzY8CvA8+IiP/RPELx8sz8emY+CtxFMYH8bmUFq6tmywfwgrbn/Duwt3m0S0vQDDn5DeCHKbLyWuB/AX+Ymb8IfB8420nk0pGZ+yh2PLyA4kyaX25uisycaO6d/hfga8CVEbE6Il5WUbmqxk8C722erv9m4AeAn29tNB9LzvQ8DNHMQ2Z+ITN3NZ/3NWA/cLSSKlWF6dlYAfxyc72aKzPznuac5EvAAYpTtfvSom1A2/Y8DwPPA2h+oF8DLoiIJzev92u5hKL5/F5XC1UlOuRjF7AlIp7SfN5jKY509e0/cs1ulpz8C0VOngn8YGbemZn/3HzeBcDnu16oKtGWj/cDXwX+FXhhRDyh2XwOcOz36G8Dv09xbejGrherrmvLx53AiwAycxi4HTgzIp7b9nTz0ec65OFzwBnT8gBwOcWaJd/uVo2qRods3AacHRHPzcxDbd/yamAlxam4fWnRNKARMdj8f8CUBWPuozgl7mnNr2+lONK5uvn8l0fElymu3brKIxf96STzsQZY1XzedyhWpNvQ1YJViZPMyWqOjSM/HRFfoBhHru9q0eqa2fKRmUcy8yjF4iH3AL/S2p6Z4811B/6C4jSq871GuH+1n37fNn7cBgxExI81v/4yxdHyM5rf84PA/8V89J2TyMPDHMvDq5rz0rOB12fm4S6WrC45xbHipRFxN8Up/K/PzL49aNbzDWhEPDci/hZ4a0Ssa7uov7VC1BcoTl94fkQsy8yvAmdSXMgL8A2KD/FVzVOp1EdKyAcUp2p/sJt1q7vmkZNnNrffC7wuM1+amX27R3Kp6pCPwVYz2vQI8AngyRHxxIhY3zyL4hHgjZn5ksx8uPt/Ay2kiHhWc+GQKault00w7wW+AvxcRAxm5l6KnZqbm9tHMR994xTzsJGi4YTi9MorM/PVmfmfXSxdC2weY0UrG7so5hqv6vds9HQDGhHnUOw1vIXiyMO7olhBjNbqg5l5H8Xpc+dS3HMLigt6v9Hcfnt6/62+NM98PNh6nX7ew6RycpKZ92bmHd2tXN1wgnyMZ2ZGxIqIWNH8+tMUE4gvA58BNmTmaNt1XeojEfFrwMcpdk78t+ZjgzBlgvkoRRZWAH/Y3LFVo3lqZWbuT+/32BfmmYdHms+7q7n+hPpISdn4j8y8vculV6KnG1DgWcDXmkenfpNiIaFLI+IJABHx7oi4BqhTrFD4rIioAyMU93dUf5tPPv61kopVBccRdXKifLwT+Gug9fXrKBYi+ivg6TYWfe8Bimu2Xk9z51QW9/kEICLeAXyY4ijn1RSTyc80v/7bbherBWceNBuzcRJ66j6gEXEpxR7o4cz8XHPP9N8Br8jMb0bEU4FXAf8JfJHiBs9vax69ICJWAcsy80AlfwEtKPOhuTAn6qSEfFwMPNj6Wv1lhnwMNjctB/4R2JGZ72ueUrcF+F3g6ixu/9Y61e60LFbf1yJnHjQbszE/PXEENCKeEBGfBH6LYo/AByLipzJzN8Vqcq0ly79OcerTY4H/yMxXZuZ9rXOrM/Ogk8b+Yz40F+ZEnZSQj9apVP9m89l/OuRjHJhoXqrxR8BrImJ9cwGqVj7ubxs/JpbqhLKfmAfNxmyUoycaUIoFYT6Tmc/LzHcBfwpc2dz2GeBpEXFh88N9CPixzByFYg9CurJtvzMfmgtzok7mm4/xGV9V/WJ6Pv4EeB1M3isYiuuEPwe8CYoFR5r/D8ePvmMeNBuzUYLKGtAolqHeFhErgJspToFq+TbFSlBQ3HPvTuCPm6fGbQG+ERGPgamrTKl/mA/NhTlRJ+ZDnZwgHyMU9xWfXMGymYN3A78dEaPA+c0JZe9cy6RTZh40G7NRvmXdfLOICIqlqD8MTAD3A1cAv5qZ34qI5VmsSvkEisPaZOb/A/40IjYBf0NxvvWrMvO73axdC898aC7MiToxH+rkFPMx0fy+c4EPUNzL79cy8z+q+DuoPOZBszEbC6trR0CjuN9NUtzY/aHM/EmKlaJGgO3Np7X2Ml8CfKz5fY9vPvZbwGsy88LM/Hq36lZ3mA/NhTlRJ+ZDnZxCPq5vfl/r3rDfoViQ6iedUC5+5kGzMRsLb8GPgDYXbngXMBgRN1Es7DAOxfLEEfGrwMMR8eOZeWtEDAH7gV0R8R7gRRGxLYubvy/Zi3X7lfnQXJgTdWI+1ElJ+bgoM/cB+yr6a6gk5kGzMRvds6BHQCPixynurVcD7qP4UI8AF0XzgtzmedJvB97R/LYfAC6nOMd6NXBxc1KgPmM+NBfmRJ2YD3VSYj5Gulq4FoR50GzMRnct9BHQCeCPMvPvACLiR4CzgbcBfwFcEMUFuzcAPxERTwTOAP4e+OPMvGuB61O1zIfmwpyoE/OhTsyH2pkHzcZsdNFCXwNaB66LYzdnvQ04KzM/SHF4+03NvQlPpLh3zt7M/EJmvsoPckkwH5oLc6JOzIc6MR9qZx40G7PRRQvagGbmdzNzLI/dP+0SinOlAX4R+K8RcSPwEYoPvrXqlJYA86G5MCfqxHyoE/OhduZBszEb3dWV27A09yYksAH4RPPhR4GrgPOABzLzIZhyE1ctEeZDc2FO1In5UCfmQ+3Mg2ZjNrqjW7dhmQCWA48AT2/uQbia4hD2Z1sfpJYs86G5MCfqxHyoE/OhduZBszEbXRDdat4j4keBf2/+94HMvKYrb6xFwXxoLsyJOjEf6sR8qJ150GzMxsLrZgP6ROAXKFaKGuvKm2rRMB+aC3OiTsyHOjEfamceNBuzsfC61oBKkiRJkpa2bl0DKkmSJEla4mxAJUmSJEldYQMqSZIkSeoKG1BJkiRJUlfYgEqSJEmSusIGVJKkkkTE2yPiNztsf3FEPLWbNUmS1EtsQCVJ6p4XAzagkqQly/uASpI0DxHxe8CrgX3AHqAOjAJXAkPAfRQ3Nf9h4MbmtlHgpc2X+HPgdOC7wBWZeU8Xy5ckqatsQCVJOkURcQHwQeBCYBlwB/CXwAcy89vN57wb+M/MfH9EfBC4MTM/1tx2M/C6zLw3Ii4Efj8zf6L7fxNJkrpjWdUFSJK0iD0P+HhmfhcgIj7RfPy8ZuO5FlgFfGr6N0bEKuA5wD9EROvhFQtdsCRJVbIBlSSpfB8EXpyZd0fE5cC2GZ4zABzIzB/uXlmSJFXLRYgkSTp1nwZeHBErI2I1cGnz8dXAtyJiOfDzbc9/tLmNzPwO8EBEvAwgCs/oXumSJHWfDagkSacoM+8APgrcDfwL8MXmpquBzwO3Ae2LCl0LvCUi7oyIcyma09dExN3AV4DLulW7JElVcBEiSZIkSVJXeARUkiRJktQVNqCSJEmSpK6wAZUkSZIkdYUNqCRJkiSpK2xAJUmSJEldYQMqSZIkSeoKG1BJkiRJUlf8f9bEidW5tFUYAAAAAElFTkSuQmCC\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 0x130bf2ca0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "asset[\"ACTRET_1\"] = trendy.TS_Trends * asset.PCTRET_1\n",
    "asset[[\"PCTRET_1\", \"ACTRET_1\"]].plot(figsize=(16, 3), color=colors(\"GyOr\"), alpha=1, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Buy and Hold Returns (*PCTRET_1*) vs. Cum. Active Returns (*ACTRET_1*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x1312c6250>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "asset[[\"PCTRET_1\", \"ACTRET_1\"]].cumsum().plot(figsize=(16, 3), kind=\"area\", stacked=False, color=colors(\"GyOr\"), title=\"B&H vs. Cum. Active Returns\", alpha=.4, grid=True).axhline(0, color=\"black\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Disclaimer\n",
    "* All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, or individual’s trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.\n",
    "\n",
    "* Any opinions, news, research, analyses, prices, or other information offered is provided as general market commentary, and does not constitute investment advice. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from use of or reliance on such information."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}