ADF_Cointegration.ipynb

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        "#importing packages\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import yfinance as yf\n",
        "import statsmodels.api as sm\n",
        "import scipy.optimize as spop\n",
        "import matplotlib.pyplot as plt\n",
        "#from statsmodels.tsa.stattools import adfuller\n",
        "#from statsmodels.tsa.stattools import grangercausalitytests\n",
        "#import statsmodels.tsa.stattools as ts"
      ]
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            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n"
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      "source": [
        "#specifying parameters\n",
        "stocks = ['JPM','C'] #['XOM', 'CVX'] #['TSM','NVDA'] #['TSLA','NVDA'] #['INTC','NVDA'] #['AMD','NVDA'] #['TSM','NVDA'] #['QCOM','NVDA'] #['QQQ','VOO']\n",
        "start = '2019-12-31' #'2019-09-28'\n",
        "end = '2021-03-08'  #'2021-09-28'\n",
        "fee = 0.001\n",
        "window = 252 # trading days in year\n",
        "DF_threshold = -2.5 # DF-critical: 10% = -1.161, 5% = -1.941, 1% = -2.567\n",
        "# trade when < test statistics: [good.. -3 -4 -5 ..wonderful]; out of confidence bandwidth?; t-dist for 2 data point to compare at a timestamp moment?\n",
        "#retrieving data\n",
        "data = pd.DataFrame()\n",
        "returns = pd.DataFrame()\n",
        "for stock in stocks:\n",
        "    prices = yf.download(stock, start, end)\n",
        "    data[stock] = prices['Close']\n",
        "    returns[stock] = np.append(data[stock][1:].reset_index(drop=True)/data[stock][:-1].reset_index(drop=True) - 1 , 0)  #change%, 0 at last∵don't know $ of next day yet"
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              "                   JPM          C\n",
              "Date                             \n",
              "2019-12-31  139.399994  79.889999\n",
              "2020-01-02  141.089996  81.230003\n",
              "2020-01-03  138.339996  79.699997\n",
              "2020-01-06  138.229996  79.449997\n",
              "2020-01-07  135.880005  78.760002\n",
              "...                ...        ...\n",
              "2021-03-01  150.500000  69.540001\n",
              "2021-03-02  150.009995  68.910004\n",
              "2021-03-03  152.910004  70.379997\n",
              "2021-03-04  150.559998  69.809998\n",
              "2021-03-05  150.910004  70.230003\n",
              "\n",
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        "#initialising arrays\n",
        "#def __init__(self):\n",
        "gross_returns = np.array([])\n",
        "net_returns = np.array([])\n",
        "t_s = np.array([])\n",
        "stock1 = stocks[0]\n",
        "stock2 = stocks[1]"
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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Augmented Dickey-Fuller Table (DF critical values)\n",
        "![image info](https://real-statistics.com/wp-content/uploads/2019/01/adf-table-critical-values.png)"
      ],
      "metadata": {
        "id": "q_9_H1gQsX_p"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Simple $AR(1)$ model:\n",
        "\n",
        "$y_t = μ+ 𝜙y_{t-1} + 𝜀_t$\n",
        "\n",
        "where $𝜀_t$ ~ $N(0,𝜎^2)$\n",
        "\n",
        "> $H_0$ : 𝜙 = 1 ( has unit root -> non-stationary, a random walk ($y_t = ∑𝜀_t$ if $y_0=0$ and without dirfting $μ$), 𝜎 influenced by former moment ( i.e. 𝜎 depends on time t))\n",
        "\n",
        "> $H_1$ : 𝜙 < 1 ( no unit root -> stationary, influence from former 𝜎 will decrease gradully, Cov and 𝜎 can be a constant (i.e. independent on time t))\n",
        "\n",
        "Transform dynamic to station by unit difference (self against lag_1) as delta:\n",
        "\n",
        "$y_t - y_{t-1} = μ+ (𝜙-1)y_{t-1} + 𝜀_t$\n",
        "\n",
        "$𝛥y_t = μ+  𝛿y_{t-1} + 𝜀_t$\n",
        "\n",
        "$𝛥y_t = 𝛿y_{t-1} + 𝜀_t$ (ignore static mean (no constant drift, no trend, stable over time),  we want the gap (stock price - fair value) fluctuate around zero)\n",
        "\n",
        "Let 𝜙 - 1 = 𝛿\n",
        "\n",
        "> $H_0$ : 𝛿 = 0 (where $y_t$ is non-statioinary)\n",
        "\n",
        "> $H_1$ : 𝛿 < 0 (where $y_t$ is statioinary)\n",
        "\n",
        "test-statistics:\n",
        "\n",
        "$t_\\hat{𝛅} = \\frac{\\hat{𝛅}}{se(\\hat{𝛅})}$\n",
        "\n",
        "$t_\\hat{𝛅}$  < DF critical value , reject $H_0$ , 𝛿 significantly different from 0 ($y_t$ is stationary, profitable when two prices converge, the gap of conintegration (stock price - fair value) at lagged unit gen signal to long/short stocks pair base on undervalued/overvalued stocks by fair value)\n",
        "\n",
        "$t_\\hat{𝛅}$  > DF critical value , no evidence to reject $H_0$ ($y_t$ can be non-stationry)\n",
        "\n",
        "For"
      ],
      "metadata": {
        "id": "VjZz4vpN3vSF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## For Cointegration test"
      ],
      "metadata": {
        "id": "atE8GOMg6smC"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "To test if there is stationary in price spread of the pair stocks that their tendency are similar\n",
        "\n",
        "> $y_t$ is price of stock2 at time t\n",
        "\n",
        "> $x_t$ is price of stock1 at time t\n",
        "\n",
        "\n",
        "\n",
        "> Fair value:\n",
        "\n",
        "$\\hat{y_t} = a + b*x_t$\n",
        "\n",
        "> $z_t$  is the difference between dyanmic equlibrium(fair value) and price of stock2 (the response variable), (i.e. the value of undervalued/overvalued at time t)\n",
        "\n",
        "$z_t = \\hat{y_t} - y_t$"
      ],
      "metadata": {
        "id": "fmYqW1elOhZK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        ">\n",
        "\n",
        "> To apply Dickey-Fuller test in this example,\n",
        "\n",
        "> $H_0$ : 𝛿 = 0 (where $z_t = (a+b∗x_t) - y_t$ is non-statioinary)\n",
        "\n",
        "> $H_1$ : 𝛿 < 0 (where $z_t = (a+b∗x_t) - y_t$ is statioinary)\n",
        "\n",
        "$𝛥z_t = 𝛿z_{t-1} + 𝜀_t$\n",
        "\n",
        "> $z_{t-1}$ is lagged a trading day unit\n",
        "\n",
        "> $𝛥z_t$ is the change of $(z_t-z_{t-1})$\n",
        "\n",
        "> we then find the optimal coefficient 𝛿 and $t_\\hat{𝛅}$ given $𝛥z_t$ and $z_{t-1}$, to determine whether the signal is confident to trigger\n",
        "\n",
        "Looking for the mean reversion of the price spread from divergen to convergen\n",
        "\n"
      ],
      "metadata": {
        "id": "4Ja7GuGAwXUp"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "2BA4SPvvcDUg",
        "outputId": "8a59006e-5fef-4d72-f507-e86b43234a85",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "day 2020-12-30 00:00:00\n",
            "\n",
            "no trading\n",
            "gross daily return: 0%\n",
            "net daily return: 0.0%\n",
            "cumulative net return so far: 0.0%\n",
            "\n",
            "day 2020-12-31 00:00:00\n",
            "\n",
            "no trading\n",
            "gross daily return: 0%\n",
            "net daily return: 0.0%\n",
            "cumulative net return so far: 0.0%\n",
            "\n",
            "day 2021-01-04 00:00:00\n",
            "\n",
            "no trading\n",
            "gross daily return: 0%\n",
            "net daily return: 0.0%\n",
            "cumulative net return so far: 0.0%\n",
            "\n",
            "day 2021-01-05 00:00:00\n",
            "\n",
            "no trading\n",
            "gross daily return: 0%\n",
            "net daily return: 0.0%\n",
            "cumulative net return so far: 0.0%\n",
            "\n",
            "day 2021-01-06 00:00:00\n",
            "\n",
            "no trading\n",
            "gross daily return: 0%\n",
            "net daily return: 0.0%\n",
            "cumulative net return so far: 0.0%\n",
            "\n",
            "day 2021-01-07 00:00:00\n",
            "\n",
            "no trading\n",
            "gross daily return: 0%\n",
            "net daily return: 0.0%\n",
            "cumulative net return so far: 0.0%\n",
            "\n",
            "day 2021-01-08 00:00:00\n",
            "\n",
            "no trading\n",
            "gross daily return: 0%\n",
            "net daily return: 0.0%\n",
            "cumulative net return so far: 0.0%\n",
            "\n",
            "day 2021-01-11 00:00:00\n",
            "\n",
            "no trading\n",
            "gross daily return: 0%\n",
            "net daily return: 0.0%\n",
            "cumulative net return so far: 0.0%\n",
            "\n",
            "day 2021-01-12 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.19%\n",
            "net daily return: -0.29%\n",
            "cumulative net return so far: -0.29%\n",
            "\n",
            "day 2021-01-13 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -2.63%\n",
            "net daily return: -2.63%\n",
            "cumulative net return so far: -2.92%\n",
            "\n",
            "day 2021-01-14 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 5.13%\n",
            "net daily return: 5.13%\n",
            "cumulative net return so far: 2.07%\n",
            "\n",
            "day 2021-01-15 00:00:00\n",
            "\n",
            "long position on C and short position on JPM\n",
            "gross daily return: -0.41%\n",
            "net daily return: -0.61%\n",
            "cumulative net return so far: 1.45%\n",
            "\n",
            "day 2021-01-19 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.81%\n",
            "net daily return: -1.01%\n",
            "cumulative net return so far: 0.42%\n",
            "\n",
            "day 2021-01-20 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 1.34%\n",
            "net daily return: 1.34%\n",
            "cumulative net return so far: 1.77%\n",
            "\n",
            "day 2021-01-21 00:00:00\n",
            "\n",
            "long position on C and short position on JPM\n",
            "gross daily return: -0.1%\n",
            "net daily return: -0.3%\n",
            "cumulative net return so far: 1.47%\n",
            "\n",
            "day 2021-01-22 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 0.01%\n",
            "net daily return: -0.19%\n",
            "cumulative net return so far: 1.27%\n",
            "\n",
            "day 2021-01-25 00:00:00\n",
            "\n",
            "long position on C and short position on JPM\n",
            "gross daily return: 0.99%\n",
            "net daily return: 0.79%\n",
            "cumulative net return so far: 2.07%\n",
            "\n",
            "day 2021-01-26 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.35%\n",
            "net daily return: -0.55%\n",
            "cumulative net return so far: 1.51%\n",
            "\n",
            "day 2021-01-27 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 0.18%\n",
            "net daily return: 0.18%\n",
            "cumulative net return so far: 1.69%\n",
            "\n",
            "day 2021-01-28 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 2.79%\n",
            "net daily return: 2.79%\n",
            "cumulative net return so far: 4.52%\n",
            "\n",
            "day 2021-01-29 00:00:00\n",
            "\n",
            "long position on C and short position on JPM\n",
            "gross daily return: 0.02%\n",
            "net daily return: -0.18%\n",
            "cumulative net return so far: 4.34%\n",
            "\n",
            "day 2021-02-01 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 1.11%\n",
            "net daily return: 0.91%\n",
            "cumulative net return so far: 5.29%\n",
            "\n",
            "day 2021-02-02 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -1.41%\n",
            "net daily return: -1.41%\n",
            "cumulative net return so far: 3.81%\n",
            "\n",
            "day 2021-02-03 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 0.16%\n",
            "net daily return: 0.16%\n",
            "cumulative net return so far: 3.97%\n",
            "\n",
            "day 2021-02-04 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.47%\n",
            "net daily return: -0.47%\n",
            "cumulative net return so far: 3.48%\n",
            "\n",
            "day 2021-02-05 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.14%\n",
            "net daily return: -0.14%\n",
            "cumulative net return so far: 3.33%\n",
            "\n",
            "day 2021-02-08 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 0.43%\n",
            "net daily return: 0.43%\n",
            "cumulative net return so far: 3.78%\n",
            "\n",
            "day 2021-02-09 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.73%\n",
            "net daily return: -0.73%\n",
            "cumulative net return so far: 3.02%\n",
            "\n",
            "day 2021-02-10 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 0.38%\n",
            "net daily return: 0.38%\n",
            "cumulative net return so far: 3.41%\n",
            "\n",
            "day 2021-02-11 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 0.74%\n",
            "net daily return: 0.74%\n",
            "cumulative net return so far: 4.18%\n",
            "\n",
            "day 2021-02-12 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 1.64%\n",
            "net daily return: 1.64%\n",
            "cumulative net return so far: 5.88%\n",
            "\n",
            "day 2021-02-16 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.69%\n",
            "net daily return: -0.69%\n",
            "cumulative net return so far: 5.15%\n",
            "\n",
            "day 2021-02-17 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 2.31%\n",
            "net daily return: 2.31%\n",
            "cumulative net return so far: 7.59%\n",
            "\n",
            "day 2021-02-18 00:00:00\n",
            "\n",
            "long position on C and short position on JPM\n",
            "gross daily return: 1.95%\n",
            "net daily return: 1.75%\n",
            "cumulative net return so far: 9.48%\n",
            "\n",
            "day 2021-02-19 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 1.33%\n",
            "net daily return: 1.13%\n",
            "cumulative net return so far: 10.72%\n",
            "\n",
            "day 2021-02-22 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -1.06%\n",
            "net daily return: -1.06%\n",
            "cumulative net return so far: 9.54%\n",
            "\n",
            "day 2021-02-23 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -1.03%\n",
            "net daily return: -1.03%\n",
            "cumulative net return so far: 8.42%\n",
            "\n",
            "day 2021-02-24 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 0.38%\n",
            "net daily return: 0.38%\n",
            "cumulative net return so far: 8.83%\n",
            "\n",
            "day 2021-02-25 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.38%\n",
            "net daily return: -0.38%\n",
            "cumulative net return so far: 8.41%\n",
            "\n",
            "day 2021-02-26 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -3.29%\n",
            "net daily return: -3.29%\n",
            "cumulative net return so far: 4.84%\n",
            "\n",
            "day 2021-03-01 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 0.58%\n",
            "net daily return: 0.58%\n",
            "cumulative net return so far: 5.45%\n",
            "\n",
            "day 2021-03-02 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.2%\n",
            "net daily return: -0.2%\n",
            "cumulative net return so far: 5.24%\n",
            "\n",
            "day 2021-03-03 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.73%\n",
            "net daily return: -0.73%\n",
            "cumulative net return so far: 4.47%\n",
            "\n",
            "day 2021-03-04 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: -0.37%\n",
            "net daily return: -0.37%\n",
            "cumulative net return so far: 4.09%\n",
            "\n",
            "day 2021-03-05 00:00:00\n",
            "\n",
            "long position on JPM and short position on C\n",
            "gross daily return: 0.0%\n",
            "net daily return: 0.0%\n",
            "cumulative net return so far: 4.09%\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7ff955a258d0>]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "#moving through the sample\n",
        "for t in range(window, len(data)):\n",
        "    #defining the unit root function: stock2 = a + b*stock1\n",
        "    def unit_root(b):\n",
        "        a = np.average(data[stock2][t-window:t] - b*data[stock1][t-window:t])\n",
        "        fair_value = a + b*data[stock1][t-window:t]  # equilibrium\n",
        "        diff = np.array(fair_value - data[stock2][t-window:t])\n",
        "        diff_diff = diff[1:] - diff[:-1]\n",
        "        reg = sm.OLS(diff_diff, diff[:-1])\n",
        "        res = reg.fit()\n",
        "        return res.params[0]/res.bse[0]\n",
        "    #optimising the cointegration equation parameters\n",
        "    res1 = spop.minimize(unit_root, data[stock2][t]/data[stock1][t], method='Nelder-Mead') # b = C/JPM <1\n",
        "    t_opt = res1.fun #\n",
        "    b_opt = float(res1.x)\n",
        "    a_opt = np.average(data[stock2][t-window:t] - b_opt*data[stock1][t-window:t])\n",
        "    #simulating trading\n",
        "    fair_value = a_opt + b_opt*data[stock1][t] # Dynamic equilibrium\n",
        "    if t == window:\n",
        "        old_signal = 0\n",
        "    if t_opt > DF_threshold:\n",
        "        signal = 0\n",
        "        gross_return = 0\n",
        "    else:\n",
        "        signal = np.sign(fair_value - data[stock2][t])\n",
        "        gross_return = signal*returns[stock2][t] - signal*returns[stock1][t]\n",
        "    fees = fee*abs(signal - old_signal)\n",
        "    net_return = gross_return - fees\n",
        "    gross_returns = np.append(gross_returns, gross_return)\n",
        "    net_returns = np.append(net_returns, net_return)\n",
        "    t_s = np.append(t_s, t_opt)\n",
        "    #interface: reporting daily positions and realised returns\n",
        "    print('day '+str(data.index[t]))\n",
        "    print('')\n",
        "    if signal == 0:\n",
        "        print('no trading')\n",
        "    elif  signal == 1:\n",
        "        print('long position on '+stock2+' and short position on '+stock1)\n",
        "    else:\n",
        "        print('long position on '+stock1+' and short position on '+stock2)\n",
        "    print('gross daily return: '+str(round(gross_return*100,2))+'%')\n",
        "    print('net daily return: '+str(round(net_return*100,2))+'%')\n",
        "    print('cumulative net return so far: '+str(round(np.prod(1+net_returns)*100-100,2))+'%')\n",
        "    print('')\n",
        "    old_signal = signal\n",
        "#plotting equity curves\n",
        "plt.plot(np.append(1,np.cumprod(1+gross_returns)))\n",
        "plt.plot(np.append(1,np.cumprod(1+net_returns)))\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(data['CVX']-data['XOM'], label = 'Spread (CVX - XOM)')\n",
        "plt.legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 451
        },
        "id": "_9c8giPNo2cT",
        "outputId": "49a2a361-5757-4256-d163-47c1a46720f9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f22be96f130>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(net_returns)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
        },
        "id": "3MJEZuxypDGl",
        "outputId": "742f0847-0f49-41c9-b63d-96d859e872e8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f22bde147c0>]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "yYuAqeL7qQOY"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "collapsed_sections": [
        "vIN3SeTaNko3"
      ]
    },
    "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": "3.7.4"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}