{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating a Simple Strategy\n",
    "\n",
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/MiniXC/simple-back/blob/master/docs/intro/quickstart.ipynb)\n",
    "\n",
    "In this tutorial, we will build a [crossover strategy](https://www.investopedia.com/articles/active-trading/052014/how-use-moving-average-buy-stocks.asp) that exclusively buys and sells JNUG. It will enter a long position whenever the price goes above its 20-day MA and enter a short position when it goes below."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Building a Backtest\n",
    "Use `.BacktesterBuilder`{.interpreted-text role=\"class\"} to configure and create a `.Backtester`{.interpreted-text role=\"class\"} object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "nbsphinx": "hidden"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Exception reporting mode: Minimal\n"
     ]
    }
   ],
   "source": [
    "%xmode Minimal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "nbsphinx": "hidden"
   },
   "outputs": [],
   "source": [
    "%%capture\n",
    "!pip install --upgrade simple_back"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from simple_back.backtester import BacktesterBuilder\n",
    "\n",
    "builder = (\n",
    "   BacktesterBuilder()\n",
    "   .name('JNUG 20-Day Crossover')\n",
    "   .balance(10_000)\n",
    "   .calendar('NYSE')\n",
    "   .compare(['JNUG']) # strategies to compare with\n",
    "   .live_progress() # show a progress bar using tqdm\n",
    "   .live_plot() # we assume we are running this in a Jupyter Notebook\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the Backtest\n",
    "We can now treat the *bt* object like an iterator with a date index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x468 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bt = builder.build()\n",
    "for day, event, b in bt['2019-1-1':'2020-1-1']:\n",
    "    pass\n",
    "    # code here will be called\n",
    "    # on 'open' and 'close' events on trading days"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that we wrote `.compare(['JNUG'])` before so we could compare our strategy to just buying and holding **JNUG**. Because we do not do anything so far, the *JNUG 20-Day Crossover* strategy results in a flat line."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note:**\n",
    "\n",
    "`.BacktesterBuilder.compare`{.interpreted-text role=\"meth\"} normally only accepts a list of `.Strategy`{.interpreted-text role=\"class\"} objects, but for each string that is passed, it automatically creates a `.BuyAndHold`{.interpreted-text role=\"class\"} strategy for the symbol represented by the string.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating a Strategy\n",
    "We are now ready to create the strategy. Although not necessary for this strategy, we will only act on market open by checking that `event == 'open'`\n",
    "\n",
    "We then calculate the 20-day moving average of **JNUGs** close prices."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%|██████████| 504/504 [00:02<00:00, 179.12it/s]\n"
     ]
    }
   ],
   "source": [
    "bt = builder.no_live_plot().build()\n",
    "for day, event, b in bt['2019-1-1':'2020-1-1']:\n",
    "    if event == 'open':\n",
    "        jnug_ma = b.prices['JNUG',-20:]['close'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note:**\n",
    "\n",
    "The second indexer of `b.prices` (implemented in `.DailyPriceProvider`{.interpreted-text role=\"class\"}) can be a date range or single date that allows you to use `int`{.interpreted-text role=\"class\"}, `dateutil.relativedelta.relativedelta`{.interpreted-text role=\"class\"} or `datetime.date`{.interpreted-text role=\"class\"} values.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can check if the current price is above or below the moving average using `b.price('JNUG')`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100%|██████████| 504/504 [00:01<00:00, 285.25it/s]\n"
     ]
    }
   ],
   "source": [
    "bt = builder.no_live_plot().build()\n",
    "for day, event, b in bt['2019-1-1':'2020-1-1']:\n",
    "    if event == 'open':\n",
    "        jnug_ma = b.prices['JNUG',-20:]['close'].mean()\n",
    "        if b.price('JNUG') > jnug_ma:\n",
    "            pass\n",
    "            # price is above MA\n",
    "        if b.price('JNUG') < jnug_ma:\n",
    "            pass\n",
    "            # price is below MA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we should only need to buy when the price is above, and sell when the price is below the MA."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  1%|          | 3/504 [00:00<00:06, 79.13it/s]\n"
     ]
    },
    {
     "ename": "InsufficientCapitalError",
     "evalue": "\n                        not enough capital available:\n                        ordered 1 * 10563.648455632008\n                        with only 449.31090733719975 available\n                        ",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31mInsufficientCapitalError\u001b[0m\u001b[0;31m:\u001b[0m \n                        not enough capital available:\n                        ordered 1 * 10563.648455632008\n                        with only 449.31090733719975 available\n                        \n"
     ]
    }
   ],
   "source": [
    "bt = builder.no_live_plot().build()\n",
    "for day, event, b in bt['2019-1-1':'2020-1-1']:\n",
    "    if event == 'open':\n",
    "        jnug_ma = b.prices['JNUG',-20:]['close'].mean()\n",
    "        if b.price('JNUG') > jnug_ma:\n",
    "            b.long('JNUG', percent=1) # as percent of total value\n",
    "        if b.price('JNUG') < jnug_ma:\n",
    "            b.short('JNUG', percent=1) # as percent of total value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But as you might already have expected, this fails with an `.InsufficientCapitalError`{.interpreted-text role=\"class\"} This is because we repeatedly try to invest 100% of our assets into **JNUG**, even when we already hold **JNUG** shares."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-info\">\n",
    "\n",
    "**Note:**\n",
    "    \n",
    "`.Backtester.long`{.interpreted-text role=\"meth\"} and `.Backtester.short`{.interpreted-text role=\"meth\"} allow for use of the following arguments: **percent**: order as percent of total value; **percent_available**: order as percent of the available cash; **absolute**: order as absolute cash value; **nshares**: order as number of shares.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To fix the previous error we now check if the corresponding positions are already in our portfolio, and liquidate positions of the wrong kind. We liquidate long positions before we go short and vice versa:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x468 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bt = builder.build()\n",
    "for day, event, b in bt['2019-1-1':'2020-1-1']:\n",
    "    if event == 'open':\n",
    "        jnug_ma = b.prices['JNUG',-20:]['close'].mean()\n",
    "\n",
    "        if b.price('JNUG') > jnug_ma:\n",
    "            if not b.portfolio['JNUG'].long: # check if we already are long JNUG\n",
    "                b.portfolio['JNUG'].short.liquidate() # liquidate any/all short JNUG positions\n",
    "                b.long('JNUG', percent=1) # long JNUG\n",
    "\n",
    "        if b.price('JNUG') < jnug_ma:\n",
    "            if not b.portfolio['JNUG'].short: # check if we already are short JNUG\n",
    "                b.portfolio['JNUG'].long.liquidate() # liquidate any/all long JNUG positions\n",
    "                b.short('JNUG', percent=1) # short JNUG"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While running, the ``.Backtester.portfolio`` (with the shorthand ``.Backtester.pf``) object keeps track of positions. If we hold a position at the very end of the backtest, it will remain in this object. ``.Backtester.portfolio.df`` holds a dataframe of said positions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>event</th>\n",
       "      <th>initial_value</th>\n",
       "      <th>nshares</th>\n",
       "      <th>order_type</th>\n",
       "      <th>price</th>\n",
       "      <th>profit_loss_abs</th>\n",
       "      <th>profit_loss_pct</th>\n",
       "      <th>start_price</th>\n",
       "      <th>symbol</th>\n",
       "      <th>value</th>\n",
       "      <th>value_pershare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-12-24</td>\n",
       "      <td>open</td>\n",
       "      <td>4238.278808</td>\n",
       "      <td>6.0</td>\n",
       "      <td>long</td>\n",
       "      <td>832.202148</td>\n",
       "      <td>754.934082</td>\n",
       "      <td>0.178123</td>\n",
       "      <td>706.379801</td>\n",
       "      <td>JNUG</td>\n",
       "      <td>4993.212891</td>\n",
       "      <td>832.202148</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date event  initial_value  nshares order_type       price  \\\n",
       "0  2019-12-24  open    4238.278808      6.0       long  832.202148   \n",
       "\n",
       "   profit_loss_abs  profit_loss_pct  start_price symbol        value  \\\n",
       "0       754.934082         0.178123   706.379801   JNUG  4993.212891   \n",
       "\n",
       "   value_pershare  \n",
       "0      832.202148  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b.portfolio.df # shorthand: b.pf.df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inspecting Metrics\n",
    "Now that our Backtest is complete, we can use `.Backtester.metrics`{.interpreted-text role=\"class\"} and `.Backtester.summary`{.interpreted-text role=\"class\"} to get more details. Both of these will return DataFrames."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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></th>\n",
       "      <th></th>\n",
       "      <th>Max Drawdown (%)</th>\n",
       "      <th>Annual Return</th>\n",
       "      <th>Portfolio Value</th>\n",
       "      <th>Total Value</th>\n",
       "      <th>Total Return (%)</th>\n",
       "      <th>Daily Profit/Loss</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Backtest</th>\n",
       "      <th>Date</th>\n",
       "      <th>Event</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 rowspan=\"5\" valign=\"top\">JNUG 20-Day Crossover</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">2019-01-02</th>\n",
       "      <th>open</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>close</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>9696.819855</td>\n",
       "      <td>10146.130762</td>\n",
       "      <td>1.461308</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2019-01-03</th>\n",
       "      <th>open</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>10114.337548</td>\n",
       "      <td>10563.648456</td>\n",
       "      <td>5.636485</td>\n",
       "      <td>563.648456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>close</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>10751.050232</td>\n",
       "      <td>11200.361139</td>\n",
       "      <td>12.003611</td>\n",
       "      <td>1054.230377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-04</th>\n",
       "      <th>open</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>10197.839717</td>\n",
       "      <td>10647.150624</td>\n",
       "      <td>6.471506</td>\n",
       "      <td>83.502169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">JNUG (Buy &amp; Hold)</th>\n",
       "      <th>2019-12-27</th>\n",
       "      <th>close</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>16358.200195</td>\n",
       "      <td>16807.511103</td>\n",
       "      <td>68.075111</td>\n",
       "      <td>-718.145142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2019-12-30</th>\n",
       "      <th>open</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>16615.727700</td>\n",
       "      <td>17065.038607</td>\n",
       "      <td>70.650386</td>\n",
       "      <td>-343.369146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>close</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>17553.713379</td>\n",
       "      <td>18003.024286</td>\n",
       "      <td>80.030243</td>\n",
       "      <td>1195.513184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2019-12-31</th>\n",
       "      <th>open</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>18221.607392</td>\n",
       "      <td>18670.918299</td>\n",
       "      <td>86.709183</td>\n",
       "      <td>1605.879692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>close</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>17476.245117</td>\n",
       "      <td>17925.556025</td>\n",
       "      <td>79.255560</td>\n",
       "      <td>-77.468262</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1008 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Max Drawdown (%)  Annual Return  \\\n",
       "Backtest              Date       Event                                    \n",
       "JNUG 20-Day Crossover 2019-01-02 open         -71.121124       0.525525   \n",
       "                                 close        -71.121124       0.525525   \n",
       "                      2019-01-03 open         -71.121124       0.525525   \n",
       "                                 close        -71.121124       0.525525   \n",
       "                      2019-01-04 open         -71.121124       0.525525   \n",
       "...                                                  ...            ...   \n",
       "JNUG (Buy & Hold)     2019-12-27 close        -49.921226       1.799052   \n",
       "                      2019-12-30 open         -49.921226       1.799052   \n",
       "                                 close        -49.921226       1.799052   \n",
       "                      2019-12-31 open         -49.921226       1.799052   \n",
       "                                 close        -49.921226       1.799052   \n",
       "\n",
       "                                        Portfolio Value   Total Value  \\\n",
       "Backtest              Date       Event                                  \n",
       "JNUG 20-Day Crossover 2019-01-02 open          0.000000  10000.000000   \n",
       "                                 close      9696.819855  10146.130762   \n",
       "                      2019-01-03 open      10114.337548  10563.648456   \n",
       "                                 close     10751.050232  11200.361139   \n",
       "                      2019-01-04 open      10197.839717  10647.150624   \n",
       "...                                                 ...           ...   \n",
       "JNUG (Buy & Hold)     2019-12-27 close     16358.200195  16807.511103   \n",
       "                      2019-12-30 open      16615.727700  17065.038607   \n",
       "                                 close     17553.713379  18003.024286   \n",
       "                      2019-12-31 open      18221.607392  18670.918299   \n",
       "                                 close     17476.245117  17925.556025   \n",
       "\n",
       "                                        Total Return (%)  Daily Profit/Loss  \n",
       "Backtest              Date       Event                                       \n",
       "JNUG 20-Day Crossover 2019-01-02 open           0.000000           0.000000  \n",
       "                                 close          1.461308           0.000000  \n",
       "                      2019-01-03 open           5.636485         563.648456  \n",
       "                                 close         12.003611        1054.230377  \n",
       "                      2019-01-04 open           6.471506          83.502169  \n",
       "...                                                  ...                ...  \n",
       "JNUG (Buy & Hold)     2019-12-27 close         68.075111        -718.145142  \n",
       "                      2019-12-30 open          70.650386        -343.369146  \n",
       "                                 close         80.030243        1195.513184  \n",
       "                      2019-12-31 open          86.709183        1605.879692  \n",
       "                                 close         79.255560         -77.468262  \n",
       "\n",
       "[1008 rows x 6 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Max Drawdown (%)</th>\n",
       "      <th>Annual Return</th>\n",
       "      <th>Portfolio Value (Last Value)</th>\n",
       "      <th>Total Value (Last Value)</th>\n",
       "      <th>Total Return (%) (Last Value)</th>\n",
       "      <th>Daily Profit/Loss (Last Value)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Backtest</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>JNUG 20-Day Crossover</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>4993.212891</td>\n",
       "      <td>5276.118290</td>\n",
       "      <td>-47.238817</td>\n",
       "      <td>-22.133789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JNUG (Buy &amp; Hold)</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>17476.245117</td>\n",
       "      <td>17925.556025</td>\n",
       "      <td>79.255560</td>\n",
       "      <td>-77.468262</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Max Drawdown (%)  Annual Return  \\\n",
       "Backtest                                                 \n",
       "JNUG 20-Day Crossover        -71.121124       0.525525   \n",
       "JNUG (Buy & Hold)            -49.921226       1.799052   \n",
       "\n",
       "                       Portfolio Value (Last Value)  Total Value (Last Value)  \\\n",
       "Backtest                                                                        \n",
       "JNUG 20-Day Crossover                   4993.212891               5276.118290   \n",
       "JNUG (Buy & Hold)                      17476.245117              17925.556025   \n",
       "\n",
       "                       Total Return (%) (Last Value)  \\\n",
       "Backtest                                               \n",
       "JNUG 20-Day Crossover                     -47.238817   \n",
       "JNUG (Buy & Hold)                          79.255560   \n",
       "\n",
       "                       Daily Profit/Loss (Last Value)  \n",
       "Backtest                                               \n",
       "JNUG 20-Day Crossover                      -22.133789  \n",
       "JNUG (Buy & Hold)                          -77.468262  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Strategies\n",
    "You can also use `.Backtester.strategies`{.interpreted-text role=\"meth\"} which returns a `.StrategySequence`{.interpreted-text role=\"class\"}, with their own `.Backtester.metrics`{.interpreted-text role=\"obj\"} and `.Backtester.summary`{.interpreted-text role=\"obj\"}."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Max Drawdown (%)</th>\n",
       "      <th>Annual Return</th>\n",
       "      <th>Portfolio Value</th>\n",
       "      <th>Total Value</th>\n",
       "      <th>Total Return (%)</th>\n",
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       "      <th>Backtest</th>\n",
       "      <th>Date</th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">JNUG 20-Day Crossover</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">2019-01-02</th>\n",
       "      <th>open</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>close</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>9696.819855</td>\n",
       "      <td>10146.130762</td>\n",
       "      <td>1.461308</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2019-01-03</th>\n",
       "      <th>open</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>10114.337548</td>\n",
       "      <td>10563.648456</td>\n",
       "      <td>5.636485</td>\n",
       "      <td>563.648456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>close</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>10751.050232</td>\n",
       "      <td>11200.361139</td>\n",
       "      <td>12.003611</td>\n",
       "      <td>1054.230377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-01-04</th>\n",
       "      <th>open</th>\n",
       "      <td>-71.121124</td>\n",
       "      <td>0.525525</td>\n",
       "      <td>10197.839717</td>\n",
       "      <td>10647.150624</td>\n",
       "      <td>6.471506</td>\n",
       "      <td>83.502169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">JNUG (Buy &amp; Hold)</th>\n",
       "      <th>2019-12-27</th>\n",
       "      <th>close</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>16358.200195</td>\n",
       "      <td>16807.511103</td>\n",
       "      <td>68.075111</td>\n",
       "      <td>-718.145142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2019-12-30</th>\n",
       "      <th>open</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>16615.727700</td>\n",
       "      <td>17065.038607</td>\n",
       "      <td>70.650386</td>\n",
       "      <td>-343.369146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>close</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>17553.713379</td>\n",
       "      <td>18003.024286</td>\n",
       "      <td>80.030243</td>\n",
       "      <td>1195.513184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2019-12-31</th>\n",
       "      <th>open</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>18221.607392</td>\n",
       "      <td>18670.918299</td>\n",
       "      <td>86.709183</td>\n",
       "      <td>1605.879692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>close</th>\n",
       "      <td>-49.921226</td>\n",
       "      <td>1.799052</td>\n",
       "      <td>17476.245117</td>\n",
       "      <td>17925.556025</td>\n",
       "      <td>79.255560</td>\n",
       "      <td>-77.468262</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1008 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Max Drawdown (%)  Annual Return  \\\n",
       "Backtest              Date       Event                                    \n",
       "JNUG 20-Day Crossover 2019-01-02 open         -71.121124       0.525525   \n",
       "                                 close        -71.121124       0.525525   \n",
       "                      2019-01-03 open         -71.121124       0.525525   \n",
       "                                 close        -71.121124       0.525525   \n",
       "                      2019-01-04 open         -71.121124       0.525525   \n",
       "...                                                  ...            ...   \n",
       "JNUG (Buy & Hold)     2019-12-27 close        -49.921226       1.799052   \n",
       "                      2019-12-30 open         -49.921226       1.799052   \n",
       "                                 close        -49.921226       1.799052   \n",
       "                      2019-12-31 open         -49.921226       1.799052   \n",
       "                                 close        -49.921226       1.799052   \n",
       "\n",
       "                                        Portfolio Value   Total Value  \\\n",
       "Backtest              Date       Event                                  \n",
       "JNUG 20-Day Crossover 2019-01-02 open          0.000000  10000.000000   \n",
       "                                 close      9696.819855  10146.130762   \n",
       "                      2019-01-03 open      10114.337548  10563.648456   \n",
       "                                 close     10751.050232  11200.361139   \n",
       "                      2019-01-04 open      10197.839717  10647.150624   \n",
       "...                                                 ...           ...   \n",
       "JNUG (Buy & Hold)     2019-12-27 close     16358.200195  16807.511103   \n",
       "                      2019-12-30 open      16615.727700  17065.038607   \n",
       "                                 close     17553.713379  18003.024286   \n",
       "                      2019-12-31 open      18221.607392  18670.918299   \n",
       "                                 close     17476.245117  17925.556025   \n",
       "\n",
       "                                        Total Return (%)  Daily Profit/Loss  \n",
       "Backtest              Date       Event                                       \n",
       "JNUG 20-Day Crossover 2019-01-02 open           0.000000           0.000000  \n",
       "                                 close          1.461308           0.000000  \n",
       "                      2019-01-03 open           5.636485         563.648456  \n",
       "                                 close         12.003611        1054.230377  \n",
       "                      2019-01-04 open           6.471506          83.502169  \n",
       "...                                                  ...                ...  \n",
       "JNUG (Buy & Hold)     2019-12-27 close         68.075111        -718.145142  \n",
       "                      2019-12-30 open          70.650386        -343.369146  \n",
       "                                 close         80.030243        1195.513184  \n",
       "                      2019-12-31 open          86.709183        1605.879692  \n",
       "                                 close         79.255560         -77.468262  \n",
       "\n",
       "[1008 rows x 6 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bt.strategies['JNUG 20-Day Crossover'].metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The advantage of using using `.StrategySequence`{.interpreted-text role=\"class\"} is that we can also use it for plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x468 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bt.strategies[0].show()"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Edit 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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}