analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "03ca9ded",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import json\n",
    "import pandas as pd\n",
    "from scipy.stats import ttest_1samp, ttest_rel\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "import datetime\n",
    "from IPython import display\n",
    "import base64\n",
    "from base64 import b64decode\n",
    "from statsmodels.stats.multitest import multipletests"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2184a69b",
   "metadata": {},
   "source": [
    "### Intro\n",
    "We're going to test the efficiency optimizing trading strategies with different window sizes using walk forward. method"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb24cc21",
   "metadata": {},
   "source": [
    "### Basic objective\n",
    "\n",
    "Similar to SignalToNoise ratio or SharpeRatio. For given set of trades $ T $ and profits $P = \\{p_1, p_2, ... p_i\\}$\n",
    "\n",
    "$$ R(P) = \\frac{\\text{AVG}(P)}{\\text{STD}(P)} $$\n",
    "\n",
    "### Overfitting and robustness modifications\n",
    "\n",
    "The ratio becomes unstable and the result becomes statistically insignificant when $|T|$ is low.\n",
    "Let's measure the amount of trades with the following ratio:\n",
    "$$\\text{TradeNumCoeff(T)} = \\frac{|T|}{|T| + 300}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "971e1d75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'SampleSizeCoeff')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def tnc(t):\n",
    "    return t/(t + 300)\n",
    "\n",
    "x = np.linspace(0, 10000)\n",
    "y = tnc(x)\n",
    "plt.figure(figsize=(15,7))\n",
    "plt.title('SampleSizeCoeff dependency on |T|')\n",
    "plt.plot(x, y)\n",
    "plt.xlabel('num trades')\n",
    "plt.ylabel('SampleSizeCoeff')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb14f8d1",
   "metadata": {},
   "source": [
    "The other type of overfitting of trading system is when it learns to do few trades that give large profits. In real price historical data there is always a few unpredictable large price flunctuations. We cannot predict such price movements, they create noise in the performance metrics and strategies tend to overfit to them.\n",
    "\n",
    "Fortunately, there is a way to measure such effect.\n",
    "Let's take the absolute values of profits $P_{\\text{abs}} = \\{|p_1|, |p_2|, ... |p_i|\\}$ and take 1% of most valuable trades. Let's call it $P_\\text{abs 1%}$\n",
    "\n",
    "Then let's compute the following ratio:\n",
    "\n",
    "$$\\text{OverfittingScore}(P_\\text{abs}) = \\frac{\\sum_{p_i \\in P_\\text{abs 1%}}{p_i}}{\\sum_{p_i \\in P_\\text{abs}}{p_i}}$$\n",
    "\n",
    "This is in some sense a measure of profit distribution skewness(?)\n",
    "This value is large for the list of trades where few trades contribute to the overall metric more than the tail of distribution.\n",
    "\n",
    "Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ceb5f586",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 2, 3, 2, 1, 2, 3, 2, -100] 0.8620689655172413\n",
      "[1, 2, 3, 2, 1, 2, 3, 2, 1] 0.17647058823529413\n",
      "[1, 1, 1, 1, 1, -2, 1, -1, 1, 1, 1] 0.16666666666666666\n"
     ]
    }
   ],
   "source": [
    "import math\n",
    "\n",
    "def os(x):\n",
    "    Pabs = sorted(list(map(abs, x)), reverse=True)\n",
    "    idx = math.ceil(len(Pabs) * 0.01)\n",
    "    percent = Pabs[:idx]\n",
    "    return sum(percent)/sum(Pabs)\n",
    "\n",
    "demo_lists = [\n",
    "    [1,2,3,2,1,2,3,2, -100],\n",
    "    [1,2,3,2,1,2,3,2,1],\n",
    "    [1,1,1,1,1,-2,1,-1,1,1,1]\n",
    "]\n",
    "\n",
    "for l in demo_lists:\n",
    "    print(l, os(l))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16861d1c",
   "metadata": {},
   "source": [
    "I assume large values of this ratio is a sign of overfitting.\n",
    "Moreover, to increase robustness of the main performance metric we can compute it only on the distribution tail, which is the list of trades without $P_\\text{abs 1%}$. Let's denote it as $P_\\text{abs 99%}$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "094e2f45",
   "metadata": {},
   "source": [
    "### The final stabilized and overfitting-resistant objective function and optimization task"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74f7e7c3",
   "metadata": {},
   "source": [
    "Our strategy parameters is\n",
    "$$ \\theta = \\begin{bmatrix} w_1, w_2, w_3, w_4, thr_{atr}, sl, b, t, n_1, n_2, n_3 \\end{bmatrix} $$\n",
    "The optimization task is\n",
    "\n",
    "$$ \\underset{\\theta}{\\arg\\min} -R(P_\\text{abs 99%}) \\cdot \\text{OverfittingScore(P)} \\cdot \\text{TradeNumCoeff(T)} $$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e5ff4b1",
   "metadata": {},
   "source": [
    "**The perfect strategy from the point of view of this objective is the one that**\n",
    "1. Makes at least a few hundred of trades\n",
    "2. The distribution of profits over trades is more or less uniform, no ultra large spikes\n",
    "3. It has the largest Sharpe Ratio (avg over variance)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5afa2a7b",
   "metadata": {},
   "source": [
    "### Strategy\n",
    "\n",
    "For two timeseries\n",
    "\n",
    "$$ x = \\{x_1, x_2, ..., x_{n-1}, x_n\\} $$\n",
    "$$ y = \\{y_1, y_2, ..., y_{m-1}, y_m\\} $$\n",
    "\n",
    "$$\\text{crossedAbove}(x, y) = (x_n \\gt y_m) \\land (x_{n-1} \\leq y_{m-1})$$\n",
    "$$\\text{crossedBelow}(x, y) = (x_n \\lt y_m) \\land (x_{n-1} \\geq y_{m-1})$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a03dd37f",
   "metadata": {},
   "source": [
    "### Factors\n",
    "\n",
    "\n",
    "\n",
    "$$sma_1 = \\text{Simple Moving Average, timeframe}=n_1$$\n",
    "$$sma_2 = \\text{Simple Moving Average, timeframe}=n_2$$\n",
    "$$sma_3 = \\text{Simple Moving Average, timeframe}=n_3$$\\\n",
    "$$\\text{smaDiff} = \\frac{sma_2 - sma_3}{sma_2}$$\\\n",
    "$$ \\text{atr_relative} = \\frac{\\text{ATR}_{20}}{\\text{close}} $$\\\n",
    "$$ \\text{up} = [sma_2 \\gt sma_3] $$\n",
    "$$ \\text{down} = [sma_2 \\leq sma_3] $$\n",
    "$$ ca = [\\text{crossedAbove}(sma_1, sma_2)] $$\n",
    "$$ cb =  -1 \\cdot [\\text{crossedBelow}(sma_2, sma_2)] $$\n",
    "\n",
    "$$ f = \\begin{bmatrix}\n",
    "[\\text{crossedAbove}(sma_1, sma_2)]\\\\\n",
    "[sma_2 \\gt sma_3] \\cdot \\text{smaDiff}\\\\\n",
    "-1 \\cdot [\\text{crossedBelow}(sma_2, sma_2)]\\\\\n",
    "[sma_2 \\leq sma_3] \\cdot \\text{smaDiff}\n",
    "\\end{bmatrix} $$\n",
    "\n",
    "$$ w = \\begin{bmatrix}\n",
    "w_1\\\\\n",
    "w_2\\\\\n",
    "w_3\\\\\n",
    "w_4\n",
    "\\end{bmatrix} $$\n",
    "\n",
    "$$\\sigma(x) = \\frac{1}{1 + \\exp(-x)}$$\n",
    "\n",
    "$$ \\text{score} = \\sigma(w^Tf)$$\n",
    "\n",
    "### Params\n",
    "\n",
    "$$w_1, w_2, w_3, w_4 \\in [1, 50] \\cap \\mathbb{R},\\\\\n",
    "thr_{atr} \\in [0.01, 0.15] \\cap \\mathbb{R},\\\\\n",
    "sl \\in [-15, 0] \\cap \\mathbb{R}, \\\\\n",
    "b \\in [0.85, 1] \\cap \\mathbb{R}, \\\\\n",
    "t \\in [2, 10] \\cap \\mathbb{R}, \\\\\n",
    "n_1 \\in [8, 21] \\cap \\mathbb{N}\\\\ \n",
    "n_2 \\in [n_1 + 8, n_1 + 21] \\cap \\mathbb{N}\\\\\n",
    "n_3 \\in [n_2 + 8, n_2 + 21] \\cap \\mathbb{N}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e27d4f37",
   "metadata": {},
   "source": [
    "### Rules\n",
    "\n",
    "\n",
    "\n",
    "**buy** when _score_ > 0.75 and _atr_relative_ < _atr_thr_\n",
    "\n",
    "set stoploss at $\\text{sl} \\cdot \\text{atr_relative} \\cdot 100$%\\\n",
    "set take_profit at $t(b^{\\text{tradeLengthMinutes}})$%\n",
    "\n",
    "\n",
    "\n",
    "**sell** when score < 0.25 (or when stoploss/take profit is triggered)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b27a9628",
   "metadata": {},
   "source": [
    "### Trade optimizer\n",
    "\n",
    "There was a few requirements to the optimization software:\n",
    "\n",
    "\n",
    "\n",
    "1. Non-bruteforce optimisation(e.g. Baysesian)\n",
    "2. The optimisation is done by iteratively sampling new parameters, running the strategy on the dataset and evaluating the objective, so performance and memory consumption of single backtesting iteration matters\n",
    "3. As much parallelisation as we can do in order to use multiple cores/processors and even cluster of multiple machines\n",
    "\n",
    "\n",
    "A distributed bayesian optimizer of strategies from scratch was implemented in Go language to satisfy this list of requirements\n",
    "\n",
    "\n",
    "In order to satisfy this requirements optimisation and backtesting was implemented in Go language which offers massive parallelisation. The system uses mysql database as storage of common data between the machines.\n",
    "This solution allows to optimize strategies using the cluster of multicore machines. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "87d77e33",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "pic = \"\"\"\n",
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    "\"\"\"\n",
    "display.Image(b64decode(pic))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a747c56",
   "metadata": {},
   "source": [
    "#### Walk forward\n",
    "\n",
    "Walk forward optimisation is a process for testing a trading strategy by finding its optimal trading parameters in a certain time period (called the in-sample or training data) and checking the performance of those parameters in the following time period\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b34499f",
   "metadata": {},
   "source": [
    "#### The experiment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "85d638fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_pic = \"\"\"\n",
    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    "\"\"\"\n",
    "display.Image(b64decode(exp_pic))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ed8aa29",
   "metadata": {},
   "source": [
    "### Analysing results, Testing hypotheses\n",
    "\n",
    "Optimizer dumps the result into json file onto disk. Let's analyze it.\n",
    "\n",
    "For each experiment we tested the following\n",
    "\n",
    "daily strategy returns against 0\n",
    "daily strategy returns against daily Buy&Hold results\n",
    "\n",
    "we used step-down Bonferroni adjustments to adjust for multiple hypothesis tesing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1c407e8f",
   "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>hypo</th>\n",
       "      <th>num_folds</th>\n",
       "      <th>t-stat</th>\n",
       "      <th>p_val</th>\n",
       "      <th>p_val_corrected</th>\n",
       "      <th>h0_rejected</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1_vs_bh_strategy</td>\n",
       "      <td>1</td>\n",
       "      <td>1.163816</td>\n",
       "      <td>2.461486e-01</td>\n",
       "      <td>7.384459e-01</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1_vs_0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.996021</td>\n",
       "      <td>3.206726e-01</td>\n",
       "      <td>7.384459e-01</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3_vs_bh_strategy</td>\n",
       "      <td>3</td>\n",
       "      <td>0.422271</td>\n",
       "      <td>6.730947e-01</td>\n",
       "      <td>7.384459e-01</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3_vs_0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.986526</td>\n",
       "      <td>4.777977e-02</td>\n",
       "      <td>1.911191e-01</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10_vs_bh_strategy</td>\n",
       "      <td>10</td>\n",
       "      <td>3.069253</td>\n",
       "      <td>2.258186e-03</td>\n",
       "      <td>1.129093e-02</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10_vs_0</td>\n",
       "      <td>10</td>\n",
       "      <td>5.730575</td>\n",
       "      <td>1.698509e-08</td>\n",
       "      <td>1.019105e-07</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                hypo  num_folds    t-stat         p_val  p_val_corrected  \\\n",
       "0   1_vs_bh_strategy          1  1.163816  2.461486e-01     7.384459e-01   \n",
       "1             1_vs_0          1  0.996021  3.206726e-01     7.384459e-01   \n",
       "2   3_vs_bh_strategy          3  0.422271  6.730947e-01     7.384459e-01   \n",
       "3             3_vs_0          3  1.986526  4.777977e-02     1.911191e-01   \n",
       "4  10_vs_bh_strategy         10  3.069253  2.258186e-03     1.129093e-02   \n",
       "5            10_vs_0         10  5.730575  1.698509e-08     1.019105e-07   \n",
       "\n",
       "   h0_rejected  \n",
       "0        False  \n",
       "1        False  \n",
       "2        False  \n",
       "3        False  \n",
       "4         True  \n",
       "5         True  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FILE = 'opt_results/opt_XMR_USD'\n",
    "\n",
    "with open(f'{FILE}.json', 'r') as f:\n",
    "    data = json.load(f)\n",
    "\n",
    "df = []\n",
    "params = []\n",
    "for window_size, folds in data['Windows'].items():\n",
    "    for i, f in enumerate(folds):\n",
    "        params.append(f['Params'])\n",
    "        ismpl = {k:v for k, v in f['InSample'].items() if k not in ['Trades', 'BuyAndHoldDaily']}\n",
    "        ismpl['Type'] = 'InSample'\n",
    "        ismpl['Fold'] = i\n",
    "        ismpl['Window'] = window_size\n",
    "        oos = {k:v for k, v in f['OutOfSample'].items() if k not in ['Trades', 'BuyAndHoldDaily']}\n",
    "        oos['Type'] = 'OutOfSample'\n",
    "        oos['Fold'] = i\n",
    "        oos['Window'] = window_size\n",
    "        df.append(ismpl)\n",
    "        df.append(oos)\n",
    "\n",
    "df = pd.DataFrame(df)\n",
    "params_df = pd.DataFrame(params)\n",
    "\n",
    "df['TimeStart'] = pd.to_datetime(df.TsStart, unit='s') + datetime.timedelta(hours=3)\n",
    "df['TimeEnd'] = pd.to_datetime(df.TsEnd, unit='s') + datetime.timedelta(hours=3)\n",
    "df['Length'] = df.TimeEnd - df.TimeStart\n",
    "\n",
    "oos_trades = []\n",
    "for window_size, folds in data['Windows'].items():\n",
    "    for i, fold in enumerate(folds):\n",
    "        if fold['OutOfSample']['Trades'] is not None:\n",
    "            for trade in fold['OutOfSample']['Trades']:\n",
    "                trade['fold'] = i\n",
    "                trade['window'] = window_size\n",
    "                oos_trades.append(trade)\n",
    "        \n",
    "is_trades = []\n",
    "for window_size, folds in data['Windows'].items():\n",
    "    for i, fold in enumerate(folds):\n",
    "        if fold['InSample']['Trades'] is not None:\n",
    "            for trade in fold['InSample']['Trades']:\n",
    "                trade['fold'] = i\n",
    "                trade['window'] = window_size\n",
    "                is_trades.append(trade)\n",
    "                \n",
    "            \n",
    "bh_days = []\n",
    "for window_size, folds in data['Windows'].items():\n",
    "    for i, fold in enumerate(folds):\n",
    "        for trade in fold['OutOfSample']['BuyAndHoldDaily']:\n",
    "            trade['fold'] = i\n",
    "            trade['window'] = window_size\n",
    "            bh_days.append(trade)\n",
    "            \n",
    "bh_days = pd.DataFrame(bh_days)\n",
    "bh_days['Time'] = pd.to_datetime(bh_days.Day, unit='s') + datetime.timedelta(hours=3)\n",
    "bh_days=bh_days.groupby(['Time', 'window']).agg(\n",
    "    {\n",
    "        'Profit': 'sum',\n",
    "        'fold': lambda x: list(x)\n",
    "    }\n",
    ")\n",
    "bh_days = bh_days.reset_index().set_index('Time')\n",
    "\n",
    "oos_trades = pd.DataFrame(oos_trades)\n",
    "oos_trades['time_sell'] = pd.to_datetime(oos_trades.ts_sell, unit='s') + datetime.timedelta(hours=3)\n",
    "oos_trades = oos_trades.set_index('time_sell').sort_index()\n",
    "\n",
    "\n",
    "\n",
    "testing_df = []\n",
    "\n",
    "def fill_empty_days(df, other):\n",
    "    r = pd.date_range(start=other.index.min(), end=other.index.max())\n",
    "    return df.reindex(r).fillna(0.0) \n",
    "\n",
    "for window_size in [1, 3, 10]:\n",
    "    w_oos_trades = oos_trades[oos_trades.window.astype('int') == window_size]\n",
    "    window_bh = bh_days[bh_days.window.astype('int') == window_size]\n",
    "    w_oos_trades = fill_empty_days(w_oos_trades.profit.resample('D').sum().fillna(0), window_bh)\n",
    "    window_bh = fill_empty_days(window_bh, w_oos_trades)\n",
    "    testing_df.append({\n",
    "        'hypo': f'{window_size}_vs_bh_strategy',\n",
    "        'num_folds': window_size, \n",
    "        't-stat': ttest_rel(w_oos_trades, window_bh.Profit)[0],\n",
    "        'p_val': ttest_rel(w_oos_trades, window_bh.Profit)[1]\n",
    "    })\n",
    "    testing_df.append({\n",
    "        'hypo': f'{window_size}_vs_0',\n",
    "        'num_folds': window_size, \n",
    "        't-stat': ttest_1samp(w_oos_trades, 0.0)[0],\n",
    "        'p_val': ttest_1samp(w_oos_trades, 0.0)[1]\n",
    "    })\n",
    "\n",
    "testing_df = pd.DataFrame(testing_df)\n",
    "rejection, p_val_corrected, _, _ = multipletests(pvals=testing_df.p_val, alpha=0.05, method='holm')\n",
    "testing_df['p_val_corrected'] = p_val_corrected\n",
    "testing_df['h0_rejected'] = rejection\n",
    "testing_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38bf3db7",
   "metadata": {},
   "source": [
    "### Visualising equity curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "dea2fe55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fc6e07da750>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "oos_trades[oos_trades.window.astype('int') == 1].profit.cumsum().plot(label='Walk Forward, 1 fold')\n",
    "bh_days[bh_days.window.astype('int') == 1].Profit.cumsum().plot(label='Buy and hold')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d6334c89",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fc700e2da50>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "oos_trades[oos_trades.window.astype('int') == 3].profit.cumsum().plot(label='Walk Forward, 3 folds')\n",
    "bh_days[bh_days.window.astype('int') == 3].Profit.cumsum().plot(label='Buy and hold')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fc65895a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fc6e12b2b10>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
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     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "oos_trades[oos_trades.window.astype('int') == 10].profit.cumsum().plot(label='Walk Forward, 10 folds')\n",
    "bh_days[bh_days.window.astype('int') == 10].Profit.cumsum().plot(label='Buy and hold')\n",
    "plt.legend()"
   ]
  }
 ],
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