ColombVisualizing Returns.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2092.32280055]\n",
      "[-1809.80728623]\n",
      "[17.53738159]\n"
     ]
    }
   ],
   "source": [
    "# GENERATING THE DATA FOR CSV FILES\n",
    "import numpy as np\n",
    "from random import random\n",
    "from random import shuffle\n",
    "import csv\n",
    "import math\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "# Generates a list containing n-number of factors\n",
    "\n",
    "#seed for consistent results\n",
    "np.random.seed(0)\n",
    "\n",
    "#creates the column headers for the factors\n",
    "def populate_factors(n):\n",
    "    s = 'Factor '\n",
    "    f = [s+str(i) for i in range(1,n+1)]\n",
    "    return f\n",
    "\n",
    "# Randomly generates a list of sigma values (std deviations) corresponding to the number of factors between [0.1,0.3] \n",
    "def get_std_devs(factors):\n",
    "    std_devs = []\n",
    "    for i in factors:\n",
    "        \n",
    "        # Sampling from adding a normal and a uniform distribution to get the standard deviations for each factor\n",
    "        # the sum of the normal and uniform was done to sample from a distribution that is uniform-like but has\n",
    "        # potential for extreme values\n",
    "        v = np.random.normal(0,.05,1) + np.random.uniform(0.1,0.25,1)\n",
    "        std_devs.append(v)\n",
    "    return std_devs\n",
    "\n",
    "# This iterates over the factors to build covariance between factors as is seen in real-market factors\n",
    "# Factors are are covariant with varrying numbers of other factors\n",
    "def addCov(facts):\n",
    "    df = pd.DataFrame(pct_changes).transpose()\n",
    "    num_facts = len(facts)\n",
    "    count = 0\n",
    "    \n",
    "    indices = [i for i in range(0, num_facts)]\n",
    "    shuffle(indices)\n",
    "    \n",
    "    for j in indices:\n",
    "        num_cov = (int)(np.random.uniform(0,num_facts/2,1))\n",
    "        if num_cov > 0:\n",
    "            covs = (np.random.uniform(1,num_facts,num_cov))\n",
    "            weight = 1 / num_cov\n",
    "\n",
    "\n",
    "            temp = df.iloc[:, j].copy()# / 4.0\n",
    "            df.iloc[:, j] = df.iloc[:,j] * 0\n",
    "            for i in covs:\n",
    "\n",
    "                df.iloc[:, j] = df.iloc[:,j] + df.iloc[:,(int)(i)] * weight\n",
    "\n",
    "            \n",
    "            df.iloc[:, j] = df.iloc[:,j] * 3 + temp\n",
    "        count += 1\n",
    "\n",
    "\n",
    "    return list(df.transpose().values)\n",
    "    \n",
    "    \n",
    "        \n",
    "    \n",
    "# Samples from a normal distribution n-times to get the pct change for n-number of data points using the sigma values generated\n",
    "def get_pct_changes(n,std_devs):\n",
    "    p = []\n",
    "    for dev in std_devs:\n",
    "        # s is a list, so pct changes is a list of lists\n",
    "        s = list(np.random.normal(0,dev,n))\n",
    "        p.append(s)\n",
    "        \n",
    "    \n",
    "    return p\n",
    "\n",
    "\n",
    "# Calculates the returns on index based on time-units\n",
    "def get_returns(pct_changes,numDataPoints):\n",
    "    rets = []\n",
    "\n",
    "    num_returns = numDataPoints\n",
    "    i = 0\n",
    "    tmp = 0\n",
    "    factor_number = 0;\n",
    "    while(i!=num_returns):\n",
    "        summing = 0\n",
    "        factor_number = 0\n",
    "        for factor_change in pct_changes:\n",
    "            factor_number+=1\n",
    "            \n",
    "            #each factor has slightly more influence on the returns\n",
    "            tmp = max( 1*factor_number - 30,0 )\n",
    "            \n",
    "            #the weight of each factor is sampled from a uniform distribution\n",
    "            w = np.random.uniform(0.1*tmp,1.4*tmp)\n",
    "            \n",
    "            #adds the weighted factor component plus some normally distributed noise\n",
    "            summing+=w*factor_change[i] + np.random.normal(0,.5,1)\n",
    "\n",
    "        rets.append(summing)\n",
    "        i+=1\n",
    "    return rets\n",
    "\n",
    "\n",
    "\n",
    "def add_jumps(pcts):\n",
    "    \n",
    "    for i in range(1,numFactors):\n",
    "        pcts[i] += np.random.poisson(.1, numDataPoints) * np.random.normal(0, .1, numDataPoints)\n",
    "        \n",
    "    return pcts\n",
    "        \n",
    "\n",
    "numFactors=100\n",
    "numDataPoints = 1000\n",
    "\n",
    "\n",
    "factors = populate_factors(numFactors)\n",
    "std_devs = get_std_devs(factors)\n",
    "pct_changes = get_pct_changes(numDataPoints,std_devs)\n",
    "pct_changes2 = addCov(pct_changes)\n",
    "pct_changes2 = add_jumps(pct_changes2)\n",
    "returns = get_returns(pct_changes2,numDataPoints)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "print(max(returns))\n",
    "print(min(returns))\n",
    "print(sum(returns)/len(returns))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(pct_changes2).transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"./percent_changes.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.DataFrame(returns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "df2.to_csv(\"./returns.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1193ae940>"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.matshow(df.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>90</th>\n",
       "      <th>91</th>\n",
       "      <th>92</th>\n",
       "      <th>93</th>\n",
       "      <th>94</th>\n",
       "      <th>95</th>\n",
       "      <th>96</th>\n",
       "      <th>97</th>\n",
       "      <th>98</th>\n",
       "      <th>99</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.040625</td>\n",
       "      <td>-0.034035</td>\n",
       "      <td>-0.003401</td>\n",
       "      <td>0.020638</td>\n",
       "      <td>0.076682</td>\n",
       "      <td>0.001278</td>\n",
       "      <td>0.030930</td>\n",
       "      <td>0.031193</td>\n",
       "      <td>-0.040298</td>\n",
       "      <td>...</td>\n",
       "      <td>0.091470</td>\n",
       "      <td>0.023083</td>\n",
       "      <td>0.048277</td>\n",
       "      <td>0.027070</td>\n",
       "      <td>-0.007745</td>\n",
       "      <td>-0.009952</td>\n",
       "      <td>-0.009282</td>\n",
       "      <td>-0.014987</td>\n",
       "      <td>0.055730</td>\n",
       "      <td>-0.006680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.040625</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.018363</td>\n",
       "      <td>0.045693</td>\n",
       "      <td>-0.030201</td>\n",
       "      <td>0.067948</td>\n",
       "      <td>-0.002561</td>\n",
       "      <td>-0.005327</td>\n",
       "      <td>-0.015446</td>\n",
       "      <td>0.010363</td>\n",
       "      <td>...</td>\n",
       "      <td>0.037836</td>\n",
       "      <td>-0.027068</td>\n",
       "      <td>0.055436</td>\n",
       "      <td>0.066178</td>\n",
       "      <td>0.018924</td>\n",
       "      <td>0.025899</td>\n",
       "      <td>0.037641</td>\n",
       "      <td>-0.020140</td>\n",
       "      <td>0.040974</td>\n",
       "      <td>0.020756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.034035</td>\n",
       "      <td>0.018363</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.002508</td>\n",
       "      <td>0.098021</td>\n",
       "      <td>-0.048020</td>\n",
       "      <td>0.033992</td>\n",
       "      <td>0.005491</td>\n",
       "      <td>-0.008408</td>\n",
       "      <td>0.018892</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.003922</td>\n",
       "      <td>0.002999</td>\n",
       "      <td>-0.052535</td>\n",
       "      <td>-0.079551</td>\n",
       "      <td>-0.023952</td>\n",
       "      <td>0.010196</td>\n",
       "      <td>-0.025946</td>\n",
       "      <td>0.004793</td>\n",
       "      <td>0.044477</td>\n",
       "      <td>0.024217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.003401</td>\n",
       "      <td>0.045693</td>\n",
       "      <td>0.002508</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.024012</td>\n",
       "      <td>-0.022231</td>\n",
       "      <td>0.000622</td>\n",
       "      <td>0.038581</td>\n",
       "      <td>-0.051841</td>\n",
       "      <td>-0.002850</td>\n",
       "      <td>...</td>\n",
       "      <td>0.125779</td>\n",
       "      <td>0.016456</td>\n",
       "      <td>-0.005715</td>\n",
       "      <td>-0.001466</td>\n",
       "      <td>0.011101</td>\n",
       "      <td>-0.030027</td>\n",
       "      <td>0.013393</td>\n",
       "      <td>0.069197</td>\n",
       "      <td>0.081524</td>\n",
       "      <td>0.057853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.020638</td>\n",
       "      <td>-0.030201</td>\n",
       "      <td>0.098021</td>\n",
       "      <td>0.024012</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.027025</td>\n",
       "      <td>0.057044</td>\n",
       "      <td>-0.027803</td>\n",
       "      <td>-0.003343</td>\n",
       "      <td>-0.044048</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002422</td>\n",
       "      <td>0.066848</td>\n",
       "      <td>0.040355</td>\n",
       "      <td>0.031166</td>\n",
       "      <td>0.058426</td>\n",
       "      <td>0.055276</td>\n",
       "      <td>0.066826</td>\n",
       "      <td>0.052998</td>\n",
       "      <td>0.007685</td>\n",
       "      <td>0.051635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.076682</td>\n",
       "      <td>0.067948</td>\n",
       "      <td>-0.048020</td>\n",
       "      <td>-0.022231</td>\n",
       "      <td>-0.027025</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.026569</td>\n",
       "      <td>0.032793</td>\n",
       "      <td>0.052486</td>\n",
       "      <td>-0.030444</td>\n",
       "      <td>...</td>\n",
       "      <td>0.039874</td>\n",
       "      <td>-0.026565</td>\n",
       "      <td>0.017271</td>\n",
       "      <td>0.036233</td>\n",
       "      <td>0.070785</td>\n",
       "      <td>0.070865</td>\n",
       "      <td>0.045817</td>\n",
       "      <td>0.008035</td>\n",
       "      <td>-0.007945</td>\n",
       "      <td>0.004580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.001278</td>\n",
       "      <td>-0.002561</td>\n",
       "      <td>0.033992</td>\n",
       "      <td>0.000622</td>\n",
       "      <td>0.057044</td>\n",
       "      <td>0.026569</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.064097</td>\n",
       "      <td>-0.009909</td>\n",
       "      <td>-0.001376</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.006734</td>\n",
       "      <td>0.022208</td>\n",
       "      <td>0.013627</td>\n",
       "      <td>0.058123</td>\n",
       "      <td>-0.027958</td>\n",
       "      <td>-0.032273</td>\n",
       "      <td>0.038689</td>\n",
       "      <td>0.046053</td>\n",
       "      <td>0.053563</td>\n",
       "      <td>0.042963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.030930</td>\n",
       "      <td>-0.005327</td>\n",
       "      <td>0.005491</td>\n",
       "      <td>0.038581</td>\n",
       "      <td>-0.027803</td>\n",
       "      <td>0.032793</td>\n",
       "      <td>0.064097</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.029349</td>\n",
       "      <td>0.007791</td>\n",
       "      <td>...</td>\n",
       "      <td>0.068838</td>\n",
       "      <td>-0.012201</td>\n",
       "      <td>0.002827</td>\n",
       "      <td>-0.010555</td>\n",
       "      <td>0.022950</td>\n",
       "      <td>-0.047796</td>\n",
       "      <td>0.009769</td>\n",
       "      <td>-0.065833</td>\n",
       "      <td>0.077844</td>\n",
       "      <td>0.011262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.031193</td>\n",
       "      <td>-0.015446</td>\n",
       "      <td>-0.008408</td>\n",
       "      <td>-0.051841</td>\n",
       "      <td>-0.003343</td>\n",
       "      <td>0.052486</td>\n",
       "      <td>-0.009909</td>\n",
       "      <td>0.029349</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.052125</td>\n",
       "      <td>...</td>\n",
       "      <td>0.025895</td>\n",
       "      <td>0.036114</td>\n",
       "      <td>0.028876</td>\n",
       "      <td>0.054551</td>\n",
       "      <td>-0.028261</td>\n",
       "      <td>0.081890</td>\n",
       "      <td>-0.002965</td>\n",
       "      <td>0.016246</td>\n",
       "      <td>0.105356</td>\n",
       "      <td>0.049721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-0.040298</td>\n",
       "      <td>0.010363</td>\n",
       "      <td>0.018892</td>\n",
       "      <td>-0.002850</td>\n",
       "      <td>-0.044048</td>\n",
       "      <td>-0.030444</td>\n",
       "      <td>-0.001376</td>\n",
       "      <td>0.007791</td>\n",
       "      <td>0.052125</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001174</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>-0.042993</td>\n",
       "      <td>0.034516</td>\n",
       "      <td>-0.043823</td>\n",
       "      <td>-0.026833</td>\n",
       "      <td>-0.033195</td>\n",
       "      <td>0.011506</td>\n",
       "      <td>-0.042693</td>\n",
       "      <td>0.055973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.043366</td>\n",
       "      <td>0.024993</td>\n",
       "      <td>-0.052580</td>\n",
       "      <td>0.028679</td>\n",
       "      <td>-0.040996</td>\n",
       "      <td>0.042306</td>\n",
       "      <td>0.023984</td>\n",
       "      <td>0.065347</td>\n",
       "      <td>0.006786</td>\n",
       "      <td>0.024218</td>\n",
       "      <td>...</td>\n",
       "      <td>0.083319</td>\n",
       "      <td>0.021917</td>\n",
       "      <td>-0.035911</td>\n",
       "      <td>0.043063</td>\n",
       "      <td>0.047250</td>\n",
       "      <td>0.022004</td>\n",
       "      <td>0.003133</td>\n",
       "      <td>0.037551</td>\n",
       "      <td>0.046114</td>\n",
       "      <td>-0.021326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>-0.047907</td>\n",
       "      <td>0.046651</td>\n",
       "      <td>-0.019469</td>\n",
       "      <td>-0.007726</td>\n",
       "      <td>0.011982</td>\n",
       "      <td>0.019785</td>\n",
       "      <td>0.019297</td>\n",
       "      <td>-0.036789</td>\n",
       "      <td>0.032989</td>\n",
       "      <td>0.052661</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.017073</td>\n",
       "      <td>0.026273</td>\n",
       "      <td>-0.015699</td>\n",
       "      <td>0.071642</td>\n",
       "      <td>0.006377</td>\n",
       "      <td>0.059779</td>\n",
       "      <td>-0.006340</td>\n",
       "      <td>-0.023942</td>\n",
       "      <td>-0.042343</td>\n",
       "      <td>0.027932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.023184</td>\n",
       "      <td>0.006879</td>\n",
       "      <td>0.039939</td>\n",
       "      <td>-0.036440</td>\n",
       "      <td>0.056647</td>\n",
       "      <td>-0.008438</td>\n",
       "      <td>0.143432</td>\n",
       "      <td>0.032924</td>\n",
       "      <td>-0.015306</td>\n",
       "      <td>0.035492</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015973</td>\n",
       "      <td>0.032668</td>\n",
       "      <td>0.015336</td>\n",
       "      <td>0.002441</td>\n",
       "      <td>0.020588</td>\n",
       "      <td>0.035300</td>\n",
       "      <td>0.007747</td>\n",
       "      <td>-0.007222</td>\n",
       "      <td>0.033133</td>\n",
       "      <td>0.068053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.033281</td>\n",
       "      <td>0.020417</td>\n",
       "      <td>0.031558</td>\n",
       "      <td>0.005733</td>\n",
       "      <td>-0.037976</td>\n",
       "      <td>0.070079</td>\n",
       "      <td>0.030054</td>\n",
       "      <td>0.031214</td>\n",
       "      <td>-0.017253</td>\n",
       "      <td>0.017308</td>\n",
       "      <td>...</td>\n",
       "      <td>0.111694</td>\n",
       "      <td>-0.042564</td>\n",
       "      <td>-0.001767</td>\n",
       "      <td>0.045810</td>\n",
       "      <td>-0.035851</td>\n",
       "      <td>-0.018146</td>\n",
       "      <td>-0.010807</td>\n",
       "      <td>-0.004176</td>\n",
       "      <td>0.008402</td>\n",
       "      <td>-0.006595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.029044</td>\n",
       "      <td>-0.005170</td>\n",
       "      <td>0.041642</td>\n",
       "      <td>0.016495</td>\n",
       "      <td>-0.027343</td>\n",
       "      <td>0.038502</td>\n",
       "      <td>-0.070474</td>\n",
       "      <td>0.005512</td>\n",
       "      <td>0.083170</td>\n",
       "      <td>0.013259</td>\n",
       "      <td>...</td>\n",
       "      <td>0.011214</td>\n",
       "      <td>-0.028677</td>\n",
       "      <td>0.120458</td>\n",
       "      <td>0.020636</td>\n",
       "      <td>0.003547</td>\n",
       "      <td>0.049664</td>\n",
       "      <td>-0.002028</td>\n",
       "      <td>-0.008991</td>\n",
       "      <td>0.004571</td>\n",
       "      <td>0.061222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>-0.037203</td>\n",
       "      <td>0.055244</td>\n",
       "      <td>-0.008861</td>\n",
       "      <td>0.056205</td>\n",
       "      <td>-0.032658</td>\n",
       "      <td>0.053808</td>\n",
       "      <td>0.005671</td>\n",
       "      <td>-0.045688</td>\n",
       "      <td>0.018706</td>\n",
       "      <td>0.047562</td>\n",
       "      <td>...</td>\n",
       "      <td>0.066308</td>\n",
       "      <td>-0.045094</td>\n",
       "      <td>0.022523</td>\n",
       "      <td>-0.023964</td>\n",
       "      <td>0.022567</td>\n",
       "      <td>-0.053990</td>\n",
       "      <td>-0.016509</td>\n",
       "      <td>0.036098</td>\n",
       "      <td>0.027670</td>\n",
       "      <td>-0.004943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>-0.019283</td>\n",
       "      <td>0.177382</td>\n",
       "      <td>0.002553</td>\n",
       "      <td>0.039915</td>\n",
       "      <td>0.102789</td>\n",
       "      <td>0.009665</td>\n",
       "      <td>-0.002001</td>\n",
       "      <td>-0.025970</td>\n",
       "      <td>0.020572</td>\n",
       "      <td>0.050462</td>\n",
       "      <td>...</td>\n",
       "      <td>0.032633</td>\n",
       "      <td>0.048366</td>\n",
       "      <td>-0.053634</td>\n",
       "      <td>0.106019</td>\n",
       "      <td>-0.009461</td>\n",
       "      <td>-0.003806</td>\n",
       "      <td>0.062932</td>\n",
       "      <td>0.079343</td>\n",
       "      <td>0.137155</td>\n",
       "      <td>0.109241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.035214</td>\n",
       "      <td>0.009823</td>\n",
       "      <td>-0.004273</td>\n",
       "      <td>0.023265</td>\n",
       "      <td>-0.031319</td>\n",
       "      <td>0.041612</td>\n",
       "      <td>0.058265</td>\n",
       "      <td>-0.010898</td>\n",
       "      <td>0.045835</td>\n",
       "      <td>0.056381</td>\n",
       "      <td>...</td>\n",
       "      <td>0.023001</td>\n",
       "      <td>0.068251</td>\n",
       "      <td>0.058896</td>\n",
       "      <td>0.056651</td>\n",
       "      <td>0.018764</td>\n",
       "      <td>0.051028</td>\n",
       "      <td>0.042209</td>\n",
       "      <td>0.031008</td>\n",
       "      <td>0.054646</td>\n",
       "      <td>0.006278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.005547</td>\n",
       "      <td>0.043952</td>\n",
       "      <td>0.022089</td>\n",
       "      <td>0.019305</td>\n",
       "      <td>0.067709</td>\n",
       "      <td>-0.008630</td>\n",
       "      <td>0.017954</td>\n",
       "      <td>-0.005192</td>\n",
       "      <td>0.058103</td>\n",
       "      <td>-0.028687</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015262</td>\n",
       "      <td>0.016250</td>\n",
       "      <td>-0.012756</td>\n",
       "      <td>0.001525</td>\n",
       "      <td>0.067671</td>\n",
       "      <td>0.068577</td>\n",
       "      <td>0.049779</td>\n",
       "      <td>0.016939</td>\n",
       "      <td>0.029236</td>\n",
       "      <td>0.074081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>-0.019459</td>\n",
       "      <td>0.049361</td>\n",
       "      <td>0.014257</td>\n",
       "      <td>-0.012803</td>\n",
       "      <td>0.026035</td>\n",
       "      <td>-0.004554</td>\n",
       "      <td>0.011263</td>\n",
       "      <td>-0.030794</td>\n",
       "      <td>-0.011106</td>\n",
       "      <td>-0.030536</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.009333</td>\n",
       "      <td>0.380157</td>\n",
       "      <td>0.039395</td>\n",
       "      <td>0.032093</td>\n",
       "      <td>0.144085</td>\n",
       "      <td>0.022734</td>\n",
       "      <td>0.025620</td>\n",
       "      <td>0.037008</td>\n",
       "      <td>0.070098</td>\n",
       "      <td>0.080403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>-0.023253</td>\n",
       "      <td>-0.002097</td>\n",
       "      <td>0.029254</td>\n",
       "      <td>0.107422</td>\n",
       "      <td>0.017677</td>\n",
       "      <td>0.131089</td>\n",
       "      <td>0.062515</td>\n",
       "      <td>-0.025080</td>\n",
       "      <td>-0.004549</td>\n",
       "      <td>-0.017257</td>\n",
       "      <td>...</td>\n",
       "      <td>0.023274</td>\n",
       "      <td>0.032204</td>\n",
       "      <td>-0.007321</td>\n",
       "      <td>0.056546</td>\n",
       "      <td>-0.010143</td>\n",
       "      <td>0.026973</td>\n",
       "      <td>0.026784</td>\n",
       "      <td>0.046330</td>\n",
       "      <td>0.051733</td>\n",
       "      <td>-0.007363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>-0.006752</td>\n",
       "      <td>0.021925</td>\n",
       "      <td>0.063633</td>\n",
       "      <td>-0.009669</td>\n",
       "      <td>0.020644</td>\n",
       "      <td>0.026000</td>\n",
       "      <td>-0.014804</td>\n",
       "      <td>0.036766</td>\n",
       "      <td>0.050698</td>\n",
       "      <td>0.080494</td>\n",
       "      <td>...</td>\n",
       "      <td>0.019004</td>\n",
       "      <td>0.024434</td>\n",
       "      <td>-0.003034</td>\n",
       "      <td>0.008371</td>\n",
       "      <td>0.009270</td>\n",
       "      <td>0.000314</td>\n",
       "      <td>0.033496</td>\n",
       "      <td>0.016149</td>\n",
       "      <td>0.051962</td>\n",
       "      <td>0.041463</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.026289</td>\n",
       "      <td>0.019868</td>\n",
       "      <td>0.025487</td>\n",
       "      <td>0.020735</td>\n",
       "      <td>0.047882</td>\n",
       "      <td>0.053906</td>\n",
       "      <td>-0.011244</td>\n",
       "      <td>-0.082269</td>\n",
       "      <td>0.012861</td>\n",
       "      <td>-0.047820</td>\n",
       "      <td>...</td>\n",
       "      <td>0.016009</td>\n",
       "      <td>0.073124</td>\n",
       "      <td>0.011917</td>\n",
       "      <td>0.008397</td>\n",
       "      <td>0.051871</td>\n",
       "      <td>0.047583</td>\n",
       "      <td>-0.000327</td>\n",
       "      <td>0.035797</td>\n",
       "      <td>0.013310</td>\n",
       "      <td>0.017549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.012457</td>\n",
       "      <td>0.028007</td>\n",
       "      <td>-0.002755</td>\n",
       "      <td>0.018455</td>\n",
       "      <td>0.074549</td>\n",
       "      <td>0.066016</td>\n",
       "      <td>0.080015</td>\n",
       "      <td>-0.023582</td>\n",
       "      <td>0.036918</td>\n",
       "      <td>0.024254</td>\n",
       "      <td>...</td>\n",
       "      <td>0.033013</td>\n",
       "      <td>0.056159</td>\n",
       "      <td>0.020439</td>\n",
       "      <td>0.059683</td>\n",
       "      <td>0.032810</td>\n",
       "      <td>0.076297</td>\n",
       "      <td>-0.063109</td>\n",
       "      <td>0.026982</td>\n",
       "      <td>0.005348</td>\n",
       "      <td>0.046878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>-0.010130</td>\n",
       "      <td>0.034193</td>\n",
       "      <td>-0.037087</td>\n",
       "      <td>0.111596</td>\n",
       "      <td>-0.011617</td>\n",
       "      <td>-0.017986</td>\n",
       "      <td>0.025388</td>\n",
       "      <td>0.017491</td>\n",
       "      <td>0.044892</td>\n",
       "      <td>0.003231</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.016674</td>\n",
       "      <td>-0.031004</td>\n",
       "      <td>0.101107</td>\n",
       "      <td>-0.015000</td>\n",
       "      <td>0.040393</td>\n",
       "      <td>-0.038858</td>\n",
       "      <td>0.004261</td>\n",
       "      <td>0.011824</td>\n",
       "      <td>0.031112</td>\n",
       "      <td>0.017326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.006467</td>\n",
       "      <td>0.061356</td>\n",
       "      <td>-0.027678</td>\n",
       "      <td>0.031733</td>\n",
       "      <td>-0.002227</td>\n",
       "      <td>0.060731</td>\n",
       "      <td>0.012587</td>\n",
       "      <td>0.043141</td>\n",
       "      <td>0.030601</td>\n",
       "      <td>0.019261</td>\n",
       "      <td>...</td>\n",
       "      <td>0.065347</td>\n",
       "      <td>0.013226</td>\n",
       "      <td>0.007499</td>\n",
       "      <td>-0.015324</td>\n",
       "      <td>0.130405</td>\n",
       "      <td>0.034373</td>\n",
       "      <td>0.027895</td>\n",
       "      <td>0.027287</td>\n",
       "      <td>-0.003708</td>\n",
       "      <td>-0.002203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.015294</td>\n",
       "      <td>-0.008577</td>\n",
       "      <td>-0.025896</td>\n",
       "      <td>-0.023266</td>\n",
       "      <td>0.024837</td>\n",
       "      <td>0.067920</td>\n",
       "      <td>0.053225</td>\n",
       "      <td>0.056428</td>\n",
       "      <td>-0.001301</td>\n",
       "      <td>0.013318</td>\n",
       "      <td>...</td>\n",
       "      <td>0.017222</td>\n",
       "      <td>0.048625</td>\n",
       "      <td>-0.003916</td>\n",
       "      <td>0.025962</td>\n",
       "      <td>0.055138</td>\n",
       "      <td>-0.028406</td>\n",
       "      <td>0.012296</td>\n",
       "      <td>-0.026018</td>\n",
       "      <td>0.005183</td>\n",
       "      <td>0.056403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.025678</td>\n",
       "      <td>0.033285</td>\n",
       "      <td>0.019985</td>\n",
       "      <td>0.007290</td>\n",
       "      <td>0.001222</td>\n",
       "      <td>0.024654</td>\n",
       "      <td>0.025152</td>\n",
       "      <td>0.182104</td>\n",
       "      <td>0.046087</td>\n",
       "      <td>0.036538</td>\n",
       "      <td>...</td>\n",
       "      <td>0.037046</td>\n",
       "      <td>0.270824</td>\n",
       "      <td>0.121511</td>\n",
       "      <td>-0.001532</td>\n",
       "      <td>0.047971</td>\n",
       "      <td>0.103280</td>\n",
       "      <td>-0.006360</td>\n",
       "      <td>-0.018283</td>\n",
       "      <td>0.064031</td>\n",
       "      <td>0.041432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>-0.032005</td>\n",
       "      <td>0.028905</td>\n",
       "      <td>0.000968</td>\n",
       "      <td>-0.003122</td>\n",
       "      <td>-0.046442</td>\n",
       "      <td>-0.052860</td>\n",
       "      <td>-0.017451</td>\n",
       "      <td>0.023688</td>\n",
       "      <td>0.002742</td>\n",
       "      <td>0.026057</td>\n",
       "      <td>...</td>\n",
       "      <td>0.080899</td>\n",
       "      <td>0.005540</td>\n",
       "      <td>0.057462</td>\n",
       "      <td>-0.026711</td>\n",
       "      <td>0.045183</td>\n",
       "      <td>-0.015509</td>\n",
       "      <td>-0.067490</td>\n",
       "      <td>0.000194</td>\n",
       "      <td>0.023764</td>\n",
       "      <td>0.049320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.003651</td>\n",
       "      <td>0.078622</td>\n",
       "      <td>0.029876</td>\n",
       "      <td>0.022549</td>\n",
       "      <td>-0.060683</td>\n",
       "      <td>-0.008446</td>\n",
       "      <td>0.041146</td>\n",
       "      <td>0.010348</td>\n",
       "      <td>0.048287</td>\n",
       "      <td>0.013864</td>\n",
       "      <td>...</td>\n",
       "      <td>0.054123</td>\n",
       "      <td>-0.008292</td>\n",
       "      <td>0.056299</td>\n",
       "      <td>0.025906</td>\n",
       "      <td>0.039961</td>\n",
       "      <td>-0.010619</td>\n",
       "      <td>0.003036</td>\n",
       "      <td>-0.009943</td>\n",
       "      <td>0.038557</td>\n",
       "      <td>0.038876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>0.030044</td>\n",
       "      <td>-0.011478</td>\n",
       "      <td>0.031832</td>\n",
       "      <td>0.029338</td>\n",
       "      <td>0.016496</td>\n",
       "      <td>0.056535</td>\n",
       "      <td>0.038741</td>\n",
       "      <td>-0.013950</td>\n",
       "      <td>0.044313</td>\n",
       "      <td>-0.011266</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.010679</td>\n",
       "      <td>0.033702</td>\n",
       "      <td>0.043218</td>\n",
       "      <td>0.079540</td>\n",
       "      <td>0.060663</td>\n",
       "      <td>0.025775</td>\n",
       "      <td>0.037291</td>\n",
       "      <td>0.092307</td>\n",
       "      <td>0.033993</td>\n",
       "      <td>0.064758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>0.068850</td>\n",
       "      <td>0.017476</td>\n",
       "      <td>0.011185</td>\n",
       "      <td>0.034737</td>\n",
       "      <td>0.047819</td>\n",
       "      <td>0.061698</td>\n",
       "      <td>0.066802</td>\n",
       "      <td>0.038352</td>\n",
       "      <td>0.024717</td>\n",
       "      <td>0.017099</td>\n",
       "      <td>...</td>\n",
       "      <td>0.087878</td>\n",
       "      <td>0.078644</td>\n",
       "      <td>0.001169</td>\n",
       "      <td>0.056417</td>\n",
       "      <td>0.058878</td>\n",
       "      <td>0.045797</td>\n",
       "      <td>0.046718</td>\n",
       "      <td>0.031760</td>\n",
       "      <td>0.099875</td>\n",
       "      <td>0.058896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>0.061213</td>\n",
       "      <td>0.018752</td>\n",
       "      <td>0.082204</td>\n",
       "      <td>0.004026</td>\n",
       "      <td>-0.018760</td>\n",
       "      <td>0.021060</td>\n",
       "      <td>0.048474</td>\n",
       "      <td>0.059219</td>\n",
       "      <td>0.066398</td>\n",
       "      <td>0.013326</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012766</td>\n",
       "      <td>0.014964</td>\n",
       "      <td>-0.010635</td>\n",
       "      <td>0.076898</td>\n",
       "      <td>0.004181</td>\n",
       "      <td>0.047923</td>\n",
       "      <td>0.064638</td>\n",
       "      <td>0.006270</td>\n",
       "      <td>0.039787</td>\n",
       "      <td>0.068219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>0.005782</td>\n",
       "      <td>0.005685</td>\n",
       "      <td>0.000893</td>\n",
       "      <td>-0.001711</td>\n",
       "      <td>0.021520</td>\n",
       "      <td>0.023153</td>\n",
       "      <td>0.054316</td>\n",
       "      <td>-0.007624</td>\n",
       "      <td>0.006441</td>\n",
       "      <td>0.139919</td>\n",
       "      <td>...</td>\n",
       "      <td>0.010727</td>\n",
       "      <td>0.001390</td>\n",
       "      <td>0.031513</td>\n",
       "      <td>-0.051967</td>\n",
       "      <td>-0.035380</td>\n",
       "      <td>-0.020994</td>\n",
       "      <td>-0.006525</td>\n",
       "      <td>0.014680</td>\n",
       "      <td>-0.062977</td>\n",
       "      <td>0.013133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>0.013390</td>\n",
       "      <td>0.036976</td>\n",
       "      <td>0.013263</td>\n",
       "      <td>0.014132</td>\n",
       "      <td>0.044478</td>\n",
       "      <td>0.047040</td>\n",
       "      <td>-0.015521</td>\n",
       "      <td>0.019689</td>\n",
       "      <td>-0.019101</td>\n",
       "      <td>0.036707</td>\n",
       "      <td>...</td>\n",
       "      <td>0.016998</td>\n",
       "      <td>0.052091</td>\n",
       "      <td>0.009716</td>\n",
       "      <td>0.019614</td>\n",
       "      <td>0.057383</td>\n",
       "      <td>0.036852</td>\n",
       "      <td>0.005912</td>\n",
       "      <td>0.069153</td>\n",
       "      <td>0.060787</td>\n",
       "      <td>0.056461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>0.025786</td>\n",
       "      <td>0.038387</td>\n",
       "      <td>0.028823</td>\n",
       "      <td>0.009131</td>\n",
       "      <td>0.151366</td>\n",
       "      <td>0.000547</td>\n",
       "      <td>0.030138</td>\n",
       "      <td>-0.004998</td>\n",
       "      <td>-0.005520</td>\n",
       "      <td>0.047455</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.008406</td>\n",
       "      <td>-0.003356</td>\n",
       "      <td>-0.016417</td>\n",
       "      <td>0.067905</td>\n",
       "      <td>0.035068</td>\n",
       "      <td>0.012411</td>\n",
       "      <td>-0.006795</td>\n",
       "      <td>0.036763</td>\n",
       "      <td>0.043492</td>\n",
       "      <td>-0.023244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>0.025160</td>\n",
       "      <td>-0.010964</td>\n",
       "      <td>0.018578</td>\n",
       "      <td>-0.017474</td>\n",
       "      <td>0.044319</td>\n",
       "      <td>0.021458</td>\n",
       "      <td>0.001151</td>\n",
       "      <td>-0.066650</td>\n",
       "      <td>0.036483</td>\n",
       "      <td>0.000147</td>\n",
       "      <td>...</td>\n",
       "      <td>0.034347</td>\n",
       "      <td>0.261926</td>\n",
       "      <td>0.034523</td>\n",
       "      <td>0.007357</td>\n",
       "      <td>0.010644</td>\n",
       "      <td>0.022261</td>\n",
       "      <td>0.010252</td>\n",
       "      <td>0.004005</td>\n",
       "      <td>0.050057</td>\n",
       "      <td>0.029424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>-0.026205</td>\n",
       "      <td>0.017333</td>\n",
       "      <td>0.036190</td>\n",
       "      <td>0.162909</td>\n",
       "      <td>0.023445</td>\n",
       "      <td>-0.004075</td>\n",
       "      <td>0.040532</td>\n",
       "      <td>0.002045</td>\n",
       "      <td>0.032324</td>\n",
       "      <td>0.067659</td>\n",
       "      <td>...</td>\n",
       "      <td>0.042294</td>\n",
       "      <td>0.142724</td>\n",
       "      <td>0.053399</td>\n",
       "      <td>0.010325</td>\n",
       "      <td>0.031849</td>\n",
       "      <td>0.026000</td>\n",
       "      <td>0.022931</td>\n",
       "      <td>0.038934</td>\n",
       "      <td>0.066006</td>\n",
       "      <td>0.064813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>0.025191</td>\n",
       "      <td>0.023285</td>\n",
       "      <td>-0.032068</td>\n",
       "      <td>-0.030159</td>\n",
       "      <td>0.028856</td>\n",
       "      <td>0.039487</td>\n",
       "      <td>0.028924</td>\n",
       "      <td>0.225500</td>\n",
       "      <td>0.068857</td>\n",
       "      <td>0.073118</td>\n",
       "      <td>...</td>\n",
       "      <td>0.043078</td>\n",
       "      <td>0.061827</td>\n",
       "      <td>-0.007934</td>\n",
       "      <td>0.032239</td>\n",
       "      <td>0.057028</td>\n",
       "      <td>-0.023626</td>\n",
       "      <td>-0.067268</td>\n",
       "      <td>0.038292</td>\n",
       "      <td>0.019182</td>\n",
       "      <td>0.042420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>-0.006546</td>\n",
       "      <td>0.013987</td>\n",
       "      <td>0.000317</td>\n",
       "      <td>0.019455</td>\n",
       "      <td>0.020370</td>\n",
       "      <td>0.065075</td>\n",
       "      <td>0.039354</td>\n",
       "      <td>0.005148</td>\n",
       "      <td>0.019809</td>\n",
       "      <td>0.029539</td>\n",
       "      <td>...</td>\n",
       "      <td>0.101157</td>\n",
       "      <td>0.024061</td>\n",
       "      <td>0.054376</td>\n",
       "      <td>-0.037809</td>\n",
       "      <td>0.031491</td>\n",
       "      <td>-0.013209</td>\n",
       "      <td>0.009175</td>\n",
       "      <td>0.060704</td>\n",
       "      <td>0.023780</td>\n",
       "      <td>0.029602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>0.028851</td>\n",
       "      <td>0.003642</td>\n",
       "      <td>0.110402</td>\n",
       "      <td>-0.002696</td>\n",
       "      <td>0.066100</td>\n",
       "      <td>-0.008727</td>\n",
       "      <td>0.065206</td>\n",
       "      <td>0.033751</td>\n",
       "      <td>0.049302</td>\n",
       "      <td>0.035020</td>\n",
       "      <td>...</td>\n",
       "      <td>0.069635</td>\n",
       "      <td>-0.003097</td>\n",
       "      <td>-0.017345</td>\n",
       "      <td>0.128250</td>\n",
       "      <td>0.012779</td>\n",
       "      <td>0.029048</td>\n",
       "      <td>0.016496</td>\n",
       "      <td>0.015618</td>\n",
       "      <td>0.053902</td>\n",
       "      <td>0.065303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>0.010184</td>\n",
       "      <td>0.033225</td>\n",
       "      <td>0.028950</td>\n",
       "      <td>-0.032448</td>\n",
       "      <td>0.070351</td>\n",
       "      <td>0.068365</td>\n",
       "      <td>0.074265</td>\n",
       "      <td>0.080354</td>\n",
       "      <td>0.009395</td>\n",
       "      <td>0.042150</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.021027</td>\n",
       "      <td>0.014481</td>\n",
       "      <td>0.083692</td>\n",
       "      <td>-0.008506</td>\n",
       "      <td>0.024721</td>\n",
       "      <td>0.043040</td>\n",
       "      <td>-0.034767</td>\n",
       "      <td>-0.023597</td>\n",
       "      <td>-0.007354</td>\n",
       "      <td>0.053350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>0.075889</td>\n",
       "      <td>-0.032429</td>\n",
       "      <td>0.007278</td>\n",
       "      <td>-0.036653</td>\n",
       "      <td>0.026468</td>\n",
       "      <td>0.044537</td>\n",
       "      <td>0.038605</td>\n",
       "      <td>0.052966</td>\n",
       "      <td>0.074846</td>\n",
       "      <td>-0.041406</td>\n",
       "      <td>...</td>\n",
       "      <td>0.040113</td>\n",
       "      <td>0.105347</td>\n",
       "      <td>0.031586</td>\n",
       "      <td>0.005376</td>\n",
       "      <td>0.052777</td>\n",
       "      <td>0.019367</td>\n",
       "      <td>-0.011342</td>\n",
       "      <td>0.057290</td>\n",
       "      <td>0.040896</td>\n",
       "      <td>0.086057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>-0.017949</td>\n",
       "      <td>0.019021</td>\n",
       "      <td>0.084080</td>\n",
       "      <td>0.013975</td>\n",
       "      <td>-0.047211</td>\n",
       "      <td>-0.031876</td>\n",
       "      <td>0.025521</td>\n",
       "      <td>-0.040643</td>\n",
       "      <td>0.016435</td>\n",
       "      <td>0.026943</td>\n",
       "      <td>...</td>\n",
       "      <td>0.012671</td>\n",
       "      <td>-0.001187</td>\n",
       "      <td>0.142022</td>\n",
       "      <td>-0.038140</td>\n",
       "      <td>-0.010744</td>\n",
       "      <td>-0.045802</td>\n",
       "      <td>-0.015397</td>\n",
       "      <td>0.071529</td>\n",
       "      <td>0.027285</td>\n",
       "      <td>0.027263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>0.018429</td>\n",
       "      <td>-0.011032</td>\n",
       "      <td>-0.003874</td>\n",
       "      <td>0.000802</td>\n",
       "      <td>0.013506</td>\n",
       "      <td>0.025389</td>\n",
       "      <td>0.011486</td>\n",
       "      <td>-0.064914</td>\n",
       "      <td>0.085977</td>\n",
       "      <td>-0.030164</td>\n",
       "      <td>...</td>\n",
       "      <td>0.052693</td>\n",
       "      <td>-0.021847</td>\n",
       "      <td>-0.057619</td>\n",
       "      <td>0.053197</td>\n",
       "      <td>-0.039772</td>\n",
       "      <td>0.079466</td>\n",
       "      <td>0.057603</td>\n",
       "      <td>0.040496</td>\n",
       "      <td>0.025826</td>\n",
       "      <td>0.039700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>-0.019405</td>\n",
       "      <td>0.101011</td>\n",
       "      <td>-0.002765</td>\n",
       "      <td>0.030976</td>\n",
       "      <td>0.081542</td>\n",
       "      <td>0.000459</td>\n",
       "      <td>0.037675</td>\n",
       "      <td>0.009042</td>\n",
       "      <td>0.032377</td>\n",
       "      <td>-0.024641</td>\n",
       "      <td>...</td>\n",
       "      <td>0.107734</td>\n",
       "      <td>-0.023065</td>\n",
       "      <td>0.049418</td>\n",
       "      <td>0.021129</td>\n",
       "      <td>0.018881</td>\n",
       "      <td>0.135343</td>\n",
       "      <td>-0.004924</td>\n",
       "      <td>-0.009714</td>\n",
       "      <td>0.000816</td>\n",
       "      <td>0.118277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>0.012776</td>\n",
       "      <td>0.000891</td>\n",
       "      <td>0.500011</td>\n",
       "      <td>-0.001144</td>\n",
       "      <td>0.282243</td>\n",
       "      <td>0.037207</td>\n",
       "      <td>-0.013135</td>\n",
       "      <td>0.019289</td>\n",
       "      <td>-0.043845</td>\n",
       "      <td>0.015206</td>\n",
       "      <td>...</td>\n",
       "      <td>0.071402</td>\n",
       "      <td>0.078109</td>\n",
       "      <td>-0.014032</td>\n",
       "      <td>-0.027641</td>\n",
       "      <td>0.032945</td>\n",
       "      <td>0.024596</td>\n",
       "      <td>-0.019934</td>\n",
       "      <td>0.047558</td>\n",
       "      <td>0.024277</td>\n",
       "      <td>0.068216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>-0.037942</td>\n",
       "      <td>-0.011525</td>\n",
       "      <td>0.173897</td>\n",
       "      <td>0.006856</td>\n",
       "      <td>0.016974</td>\n",
       "      <td>0.049265</td>\n",
       "      <td>-0.014911</td>\n",
       "      <td>-0.021345</td>\n",
       "      <td>0.012203</td>\n",
       "      <td>0.068210</td>\n",
       "      <td>...</td>\n",
       "      <td>0.011849</td>\n",
       "      <td>0.034840</td>\n",
       "      <td>0.125371</td>\n",
       "      <td>-0.019825</td>\n",
       "      <td>0.035176</td>\n",
       "      <td>0.112391</td>\n",
       "      <td>0.019199</td>\n",
       "      <td>-0.037031</td>\n",
       "      <td>0.036926</td>\n",
       "      <td>-0.012113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>0.001875</td>\n",
       "      <td>0.033088</td>\n",
       "      <td>0.036427</td>\n",
       "      <td>0.106201</td>\n",
       "      <td>0.055862</td>\n",
       "      <td>0.021900</td>\n",
       "      <td>0.040772</td>\n",
       "      <td>0.049846</td>\n",
       "      <td>0.015267</td>\n",
       "      <td>-0.043784</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036268</td>\n",
       "      <td>0.001529</td>\n",
       "      <td>0.026494</td>\n",
       "      <td>0.019856</td>\n",
       "      <td>0.024830</td>\n",
       "      <td>0.007172</td>\n",
       "      <td>0.052531</td>\n",
       "      <td>0.038087</td>\n",
       "      <td>0.010057</td>\n",
       "      <td>0.084209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>0.021686</td>\n",
       "      <td>0.087454</td>\n",
       "      <td>0.023463</td>\n",
       "      <td>0.037678</td>\n",
       "      <td>0.034616</td>\n",
       "      <td>0.049044</td>\n",
       "      <td>0.056177</td>\n",
       "      <td>-0.061580</td>\n",
       "      <td>0.014701</td>\n",
       "      <td>-0.050998</td>\n",
       "      <td>...</td>\n",
       "      <td>0.013144</td>\n",
       "      <td>0.069632</td>\n",
       "      <td>-0.011388</td>\n",
       "      <td>0.063562</td>\n",
       "      <td>0.003973</td>\n",
       "      <td>-0.021729</td>\n",
       "      <td>0.029588</td>\n",
       "      <td>0.022644</td>\n",
       "      <td>0.089395</td>\n",
       "      <td>0.109009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>0.091470</td>\n",
       "      <td>0.037836</td>\n",
       "      <td>-0.003922</td>\n",
       "      <td>0.125779</td>\n",
       "      <td>-0.002422</td>\n",
       "      <td>0.039874</td>\n",
       "      <td>-0.006734</td>\n",
       "      <td>0.068838</td>\n",
       "      <td>0.025895</td>\n",
       "      <td>0.001174</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.062123</td>\n",
       "      <td>-0.020439</td>\n",
       "      <td>0.094381</td>\n",
       "      <td>0.017140</td>\n",
       "      <td>-0.007522</td>\n",
       "      <td>-0.017833</td>\n",
       "      <td>0.015158</td>\n",
       "      <td>0.080709</td>\n",
       "      <td>0.036836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>0.023083</td>\n",
       "      <td>-0.027068</td>\n",
       "      <td>0.002999</td>\n",
       "      <td>0.016456</td>\n",
       "      <td>0.066848</td>\n",
       "      <td>-0.026565</td>\n",
       "      <td>0.022208</td>\n",
       "      <td>-0.012201</td>\n",
       "      <td>0.036114</td>\n",
       "      <td>0.000069</td>\n",
       "      <td>...</td>\n",
       "      <td>0.062123</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.142452</td>\n",
       "      <td>0.025030</td>\n",
       "      <td>0.012215</td>\n",
       "      <td>0.057974</td>\n",
       "      <td>-0.017018</td>\n",
       "      <td>0.017971</td>\n",
       "      <td>0.134937</td>\n",
       "      <td>0.131733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>0.048277</td>\n",
       "      <td>0.055436</td>\n",
       "      <td>-0.052535</td>\n",
       "      <td>-0.005715</td>\n",
       "      <td>0.040355</td>\n",
       "      <td>0.017271</td>\n",
       "      <td>0.013627</td>\n",
       "      <td>0.002827</td>\n",
       "      <td>0.028876</td>\n",
       "      <td>-0.042993</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.020439</td>\n",
       "      <td>0.142452</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.034640</td>\n",
       "      <td>0.021631</td>\n",
       "      <td>0.162098</td>\n",
       "      <td>0.063559</td>\n",
       "      <td>0.008251</td>\n",
       "      <td>0.029513</td>\n",
       "      <td>0.030643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>0.027070</td>\n",
       "      <td>0.066178</td>\n",
       "      <td>-0.079551</td>\n",
       "      <td>-0.001466</td>\n",
       "      <td>0.031166</td>\n",
       "      <td>0.036233</td>\n",
       "      <td>0.058123</td>\n",
       "      <td>-0.010555</td>\n",
       "      <td>0.054551</td>\n",
       "      <td>0.034516</td>\n",
       "      <td>...</td>\n",
       "      <td>0.094381</td>\n",
       "      <td>0.025030</td>\n",
       "      <td>-0.034640</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.006888</td>\n",
       "      <td>0.133294</td>\n",
       "      <td>0.001097</td>\n",
       "      <td>0.050904</td>\n",
       "      <td>0.019473</td>\n",
       "      <td>0.041432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>-0.007745</td>\n",
       "      <td>0.018924</td>\n",
       "      <td>-0.023952</td>\n",
       "      <td>0.011101</td>\n",
       "      <td>0.058426</td>\n",
       "      <td>0.070785</td>\n",
       "      <td>-0.027958</td>\n",
       "      <td>0.022950</td>\n",
       "      <td>-0.028261</td>\n",
       "      <td>-0.043823</td>\n",
       "      <td>...</td>\n",
       "      <td>0.017140</td>\n",
       "      <td>0.012215</td>\n",
       "      <td>0.021631</td>\n",
       "      <td>-0.006888</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.021927</td>\n",
       "      <td>0.000560</td>\n",
       "      <td>-0.025452</td>\n",
       "      <td>0.010766</td>\n",
       "      <td>0.050308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>-0.009952</td>\n",
       "      <td>0.025899</td>\n",
       "      <td>0.010196</td>\n",
       "      <td>-0.030027</td>\n",
       "      <td>0.055276</td>\n",
       "      <td>0.070865</td>\n",
       "      <td>-0.032273</td>\n",
       "      <td>-0.047796</td>\n",
       "      <td>0.081890</td>\n",
       "      <td>-0.026833</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.007522</td>\n",
       "      <td>0.057974</td>\n",
       "      <td>0.162098</td>\n",
       "      <td>0.133294</td>\n",
       "      <td>0.021927</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.047543</td>\n",
       "      <td>-0.019899</td>\n",
       "      <td>0.019591</td>\n",
       "      <td>0.145466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>-0.009282</td>\n",
       "      <td>0.037641</td>\n",
       "      <td>-0.025946</td>\n",
       "      <td>0.013393</td>\n",
       "      <td>0.066826</td>\n",
       "      <td>0.045817</td>\n",
       "      <td>0.038689</td>\n",
       "      <td>0.009769</td>\n",
       "      <td>-0.002965</td>\n",
       "      <td>-0.033195</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.017833</td>\n",
       "      <td>-0.017018</td>\n",
       "      <td>0.063559</td>\n",
       "      <td>0.001097</td>\n",
       "      <td>0.000560</td>\n",
       "      <td>0.047543</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.033105</td>\n",
       "      <td>0.035789</td>\n",
       "      <td>0.047178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>-0.014987</td>\n",
       "      <td>-0.020140</td>\n",
       "      <td>0.004793</td>\n",
       "      <td>0.069197</td>\n",
       "      <td>0.052998</td>\n",
       "      <td>0.008035</td>\n",
       "      <td>0.046053</td>\n",
       "      <td>-0.065833</td>\n",
       "      <td>0.016246</td>\n",
       "      <td>0.011506</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015158</td>\n",
       "      <td>0.017971</td>\n",
       "      <td>0.008251</td>\n",
       "      <td>0.050904</td>\n",
       "      <td>-0.025452</td>\n",
       "      <td>-0.019899</td>\n",
       "      <td>0.033105</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.018918</td>\n",
       "      <td>-0.015441</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.055730</td>\n",
       "      <td>0.040974</td>\n",
       "      <td>0.044477</td>\n",
       "      <td>0.081524</td>\n",
       "      <td>0.007685</td>\n",
       "      <td>-0.007945</td>\n",
       "      <td>0.053563</td>\n",
       "      <td>0.077844</td>\n",
       "      <td>0.105356</td>\n",
       "      <td>-0.042693</td>\n",
       "      <td>...</td>\n",
       "      <td>0.080709</td>\n",
       "      <td>0.134937</td>\n",
       "      <td>0.029513</td>\n",
       "      <td>0.019473</td>\n",
       "      <td>0.010766</td>\n",
       "      <td>0.019591</td>\n",
       "      <td>0.035789</td>\n",
       "      <td>0.018918</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.045663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>-0.006680</td>\n",
       "      <td>0.020756</td>\n",
       "      <td>0.024217</td>\n",
       "      <td>0.057853</td>\n",
       "      <td>0.051635</td>\n",
       "      <td>0.004580</td>\n",
       "      <td>0.042963</td>\n",
       "      <td>0.011262</td>\n",
       "      <td>0.049721</td>\n",
       "      <td>0.055973</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036836</td>\n",
       "      <td>0.131733</td>\n",
       "      <td>0.030643</td>\n",
       "      <td>0.041432</td>\n",
       "      <td>0.050308</td>\n",
       "      <td>0.145466</td>\n",
       "      <td>0.047178</td>\n",
       "      <td>-0.015441</td>\n",
       "      <td>0.045663</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 100 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3         4         5         6   \\\n",
       "0   1.000000 -0.040625 -0.034035 -0.003401  0.020638  0.076682  0.001278   \n",
       "1  -0.040625  1.000000  0.018363  0.045693 -0.030201  0.067948 -0.002561   \n",
       "2  -0.034035  0.018363  1.000000  0.002508  0.098021 -0.048020  0.033992   \n",
       "3  -0.003401  0.045693  0.002508  1.000000  0.024012 -0.022231  0.000622   \n",
       "4   0.020638 -0.030201  0.098021  0.024012  1.000000 -0.027025  0.057044   \n",
       "5   0.076682  0.067948 -0.048020 -0.022231 -0.027025  1.000000  0.026569   \n",
       "6   0.001278 -0.002561  0.033992  0.000622  0.057044  0.026569  1.000000   \n",
       "7   0.030930 -0.005327  0.005491  0.038581 -0.027803  0.032793  0.064097   \n",
       "8   0.031193 -0.015446 -0.008408 -0.051841 -0.003343  0.052486 -0.009909   \n",
       "9  -0.040298  0.010363  0.018892 -0.002850 -0.044048 -0.030444 -0.001376   \n",
       "10  0.043366  0.024993 -0.052580  0.028679 -0.040996  0.042306  0.023984   \n",
       "11 -0.047907  0.046651 -0.019469 -0.007726  0.011982  0.019785  0.019297   \n",
       "12  0.023184  0.006879  0.039939 -0.036440  0.056647 -0.008438  0.143432   \n",
       "13  0.033281  0.020417  0.031558  0.005733 -0.037976  0.070079  0.030054   \n",
       "14  0.029044 -0.005170  0.041642  0.016495 -0.027343  0.038502 -0.070474   \n",
       "15 -0.037203  0.055244 -0.008861  0.056205 -0.032658  0.053808  0.005671   \n",
       "16 -0.019283  0.177382  0.002553  0.039915  0.102789  0.009665 -0.002001   \n",
       "17  0.035214  0.009823 -0.004273  0.023265 -0.031319  0.041612  0.058265   \n",
       "18  0.005547  0.043952  0.022089  0.019305  0.067709 -0.008630  0.017954   \n",
       "19 -0.019459  0.049361  0.014257 -0.012803  0.026035 -0.004554  0.011263   \n",
       "20 -0.023253 -0.002097  0.029254  0.107422  0.017677  0.131089  0.062515   \n",
       "21 -0.006752  0.021925  0.063633 -0.009669  0.020644  0.026000 -0.014804   \n",
       "22  0.026289  0.019868  0.025487  0.020735  0.047882  0.053906 -0.011244   \n",
       "23  0.012457  0.028007 -0.002755  0.018455  0.074549  0.066016  0.080015   \n",
       "24 -0.010130  0.034193 -0.037087  0.111596 -0.011617 -0.017986  0.025388   \n",
       "25  0.006467  0.061356 -0.027678  0.031733 -0.002227  0.060731  0.012587   \n",
       "26  0.015294 -0.008577 -0.025896 -0.023266  0.024837  0.067920  0.053225   \n",
       "27  0.025678  0.033285  0.019985  0.007290  0.001222  0.024654  0.025152   \n",
       "28 -0.032005  0.028905  0.000968 -0.003122 -0.046442 -0.052860 -0.017451   \n",
       "29  0.003651  0.078622  0.029876  0.022549 -0.060683 -0.008446  0.041146   \n",
       "..       ...       ...       ...       ...       ...       ...       ...   \n",
       "70  0.030044 -0.011478  0.031832  0.029338  0.016496  0.056535  0.038741   \n",
       "71  0.068850  0.017476  0.011185  0.034737  0.047819  0.061698  0.066802   \n",
       "72  0.061213  0.018752  0.082204  0.004026 -0.018760  0.021060  0.048474   \n",
       "73  0.005782  0.005685  0.000893 -0.001711  0.021520  0.023153  0.054316   \n",
       "74  0.013390  0.036976  0.013263  0.014132  0.044478  0.047040 -0.015521   \n",
       "75  0.025786  0.038387  0.028823  0.009131  0.151366  0.000547  0.030138   \n",
       "76  0.025160 -0.010964  0.018578 -0.017474  0.044319  0.021458  0.001151   \n",
       "77 -0.026205  0.017333  0.036190  0.162909  0.023445 -0.004075  0.040532   \n",
       "78  0.025191  0.023285 -0.032068 -0.030159  0.028856  0.039487  0.028924   \n",
       "79 -0.006546  0.013987  0.000317  0.019455  0.020370  0.065075  0.039354   \n",
       "80  0.028851  0.003642  0.110402 -0.002696  0.066100 -0.008727  0.065206   \n",
       "81  0.010184  0.033225  0.028950 -0.032448  0.070351  0.068365  0.074265   \n",
       "82  0.075889 -0.032429  0.007278 -0.036653  0.026468  0.044537  0.038605   \n",
       "83 -0.017949  0.019021  0.084080  0.013975 -0.047211 -0.031876  0.025521   \n",
       "84  0.018429 -0.011032 -0.003874  0.000802  0.013506  0.025389  0.011486   \n",
       "85 -0.019405  0.101011 -0.002765  0.030976  0.081542  0.000459  0.037675   \n",
       "86  0.012776  0.000891  0.500011 -0.001144  0.282243  0.037207 -0.013135   \n",
       "87 -0.037942 -0.011525  0.173897  0.006856  0.016974  0.049265 -0.014911   \n",
       "88  0.001875  0.033088  0.036427  0.106201  0.055862  0.021900  0.040772   \n",
       "89  0.021686  0.087454  0.023463  0.037678  0.034616  0.049044  0.056177   \n",
       "90  0.091470  0.037836 -0.003922  0.125779 -0.002422  0.039874 -0.006734   \n",
       "91  0.023083 -0.027068  0.002999  0.016456  0.066848 -0.026565  0.022208   \n",
       "92  0.048277  0.055436 -0.052535 -0.005715  0.040355  0.017271  0.013627   \n",
       "93  0.027070  0.066178 -0.079551 -0.001466  0.031166  0.036233  0.058123   \n",
       "94 -0.007745  0.018924 -0.023952  0.011101  0.058426  0.070785 -0.027958   \n",
       "95 -0.009952  0.025899  0.010196 -0.030027  0.055276  0.070865 -0.032273   \n",
       "96 -0.009282  0.037641 -0.025946  0.013393  0.066826  0.045817  0.038689   \n",
       "97 -0.014987 -0.020140  0.004793  0.069197  0.052998  0.008035  0.046053   \n",
       "98  0.055730  0.040974  0.044477  0.081524  0.007685 -0.007945  0.053563   \n",
       "99 -0.006680  0.020756  0.024217  0.057853  0.051635  0.004580  0.042963   \n",
       "\n",
       "          7         8         9     ...           90        91        92  \\\n",
       "0   0.030930  0.031193 -0.040298    ...     0.091470  0.023083  0.048277   \n",
       "1  -0.005327 -0.015446  0.010363    ...     0.037836 -0.027068  0.055436   \n",
       "2   0.005491 -0.008408  0.018892    ...    -0.003922  0.002999 -0.052535   \n",
       "3   0.038581 -0.051841 -0.002850    ...     0.125779  0.016456 -0.005715   \n",
       "4  -0.027803 -0.003343 -0.044048    ...    -0.002422  0.066848  0.040355   \n",
       "5   0.032793  0.052486 -0.030444    ...     0.039874 -0.026565  0.017271   \n",
       "6   0.064097 -0.009909 -0.001376    ...    -0.006734  0.022208  0.013627   \n",
       "7   1.000000  0.029349  0.007791    ...     0.068838 -0.012201  0.002827   \n",
       "8   0.029349  1.000000  0.052125    ...     0.025895  0.036114  0.028876   \n",
       "9   0.007791  0.052125  1.000000    ...     0.001174  0.000069 -0.042993   \n",
       "10  0.065347  0.006786  0.024218    ...     0.083319  0.021917 -0.035911   \n",
       "11 -0.036789  0.032989  0.052661    ...    -0.017073  0.026273 -0.015699   \n",
       "12  0.032924 -0.015306  0.035492    ...     0.015973  0.032668  0.015336   \n",
       "13  0.031214 -0.017253  0.017308    ...     0.111694 -0.042564 -0.001767   \n",
       "14  0.005512  0.083170  0.013259    ...     0.011214 -0.028677  0.120458   \n",
       "15 -0.045688  0.018706  0.047562    ...     0.066308 -0.045094  0.022523   \n",
       "16 -0.025970  0.020572  0.050462    ...     0.032633  0.048366 -0.053634   \n",
       "17 -0.010898  0.045835  0.056381    ...     0.023001  0.068251  0.058896   \n",
       "18 -0.005192  0.058103 -0.028687    ...     0.015262  0.016250 -0.012756   \n",
       "19 -0.030794 -0.011106 -0.030536    ...    -0.009333  0.380157  0.039395   \n",
       "20 -0.025080 -0.004549 -0.017257    ...     0.023274  0.032204 -0.007321   \n",
       "21  0.036766  0.050698  0.080494    ...     0.019004  0.024434 -0.003034   \n",
       "22 -0.082269  0.012861 -0.047820    ...     0.016009  0.073124  0.011917   \n",
       "23 -0.023582  0.036918  0.024254    ...     0.033013  0.056159  0.020439   \n",
       "24  0.017491  0.044892  0.003231    ...    -0.016674 -0.031004  0.101107   \n",
       "25  0.043141  0.030601  0.019261    ...     0.065347  0.013226  0.007499   \n",
       "26  0.056428 -0.001301  0.013318    ...     0.017222  0.048625 -0.003916   \n",
       "27  0.182104  0.046087  0.036538    ...     0.037046  0.270824  0.121511   \n",
       "28  0.023688  0.002742  0.026057    ...     0.080899  0.005540  0.057462   \n",
       "29  0.010348  0.048287  0.013864    ...     0.054123 -0.008292  0.056299   \n",
       "..       ...       ...       ...    ...          ...       ...       ...   \n",
       "70 -0.013950  0.044313 -0.011266    ...    -0.010679  0.033702  0.043218   \n",
       "71  0.038352  0.024717  0.017099    ...     0.087878  0.078644  0.001169   \n",
       "72  0.059219  0.066398  0.013326    ...     0.012766  0.014964 -0.010635   \n",
       "73 -0.007624  0.006441  0.139919    ...     0.010727  0.001390  0.031513   \n",
       "74  0.019689 -0.019101  0.036707    ...     0.016998  0.052091  0.009716   \n",
       "75 -0.004998 -0.005520  0.047455    ...    -0.008406 -0.003356 -0.016417   \n",
       "76 -0.066650  0.036483  0.000147    ...     0.034347  0.261926  0.034523   \n",
       "77  0.002045  0.032324  0.067659    ...     0.042294  0.142724  0.053399   \n",
       "78  0.225500  0.068857  0.073118    ...     0.043078  0.061827 -0.007934   \n",
       "79  0.005148  0.019809  0.029539    ...     0.101157  0.024061  0.054376   \n",
       "80  0.033751  0.049302  0.035020    ...     0.069635 -0.003097 -0.017345   \n",
       "81  0.080354  0.009395  0.042150    ...    -0.021027  0.014481  0.083692   \n",
       "82  0.052966  0.074846 -0.041406    ...     0.040113  0.105347  0.031586   \n",
       "83 -0.040643  0.016435  0.026943    ...     0.012671 -0.001187  0.142022   \n",
       "84 -0.064914  0.085977 -0.030164    ...     0.052693 -0.021847 -0.057619   \n",
       "85  0.009042  0.032377 -0.024641    ...     0.107734 -0.023065  0.049418   \n",
       "86  0.019289 -0.043845  0.015206    ...     0.071402  0.078109 -0.014032   \n",
       "87 -0.021345  0.012203  0.068210    ...     0.011849  0.034840  0.125371   \n",
       "88  0.049846  0.015267 -0.043784    ...     0.036268  0.001529  0.026494   \n",
       "89 -0.061580  0.014701 -0.050998    ...     0.013144  0.069632 -0.011388   \n",
       "90  0.068838  0.025895  0.001174    ...     1.000000  0.062123 -0.020439   \n",
       "91 -0.012201  0.036114  0.000069    ...     0.062123  1.000000  0.142452   \n",
       "92  0.002827  0.028876 -0.042993    ...    -0.020439  0.142452  1.000000   \n",
       "93 -0.010555  0.054551  0.034516    ...     0.094381  0.025030 -0.034640   \n",
       "94  0.022950 -0.028261 -0.043823    ...     0.017140  0.012215  0.021631   \n",
       "95 -0.047796  0.081890 -0.026833    ...    -0.007522  0.057974  0.162098   \n",
       "96  0.009769 -0.002965 -0.033195    ...    -0.017833 -0.017018  0.063559   \n",
       "97 -0.065833  0.016246  0.011506    ...     0.015158  0.017971  0.008251   \n",
       "98  0.077844  0.105356 -0.042693    ...     0.080709  0.134937  0.029513   \n",
       "99  0.011262  0.049721  0.055973    ...     0.036836  0.131733  0.030643   \n",
       "\n",
       "          93        94        95        96        97        98        99  \n",
       "0   0.027070 -0.007745 -0.009952 -0.009282 -0.014987  0.055730 -0.006680  \n",
       "1   0.066178  0.018924  0.025899  0.037641 -0.020140  0.040974  0.020756  \n",
       "2  -0.079551 -0.023952  0.010196 -0.025946  0.004793  0.044477  0.024217  \n",
       "3  -0.001466  0.011101 -0.030027  0.013393  0.069197  0.081524  0.057853  \n",
       "4   0.031166  0.058426  0.055276  0.066826  0.052998  0.007685  0.051635  \n",
       "5   0.036233  0.070785  0.070865  0.045817  0.008035 -0.007945  0.004580  \n",
       "6   0.058123 -0.027958 -0.032273  0.038689  0.046053  0.053563  0.042963  \n",
       "7  -0.010555  0.022950 -0.047796  0.009769 -0.065833  0.077844  0.011262  \n",
       "8   0.054551 -0.028261  0.081890 -0.002965  0.016246  0.105356  0.049721  \n",
       "9   0.034516 -0.043823 -0.026833 -0.033195  0.011506 -0.042693  0.055973  \n",
       "10  0.043063  0.047250  0.022004  0.003133  0.037551  0.046114 -0.021326  \n",
       "11  0.071642  0.006377  0.059779 -0.006340 -0.023942 -0.042343  0.027932  \n",
       "12  0.002441  0.020588  0.035300  0.007747 -0.007222  0.033133  0.068053  \n",
       "13  0.045810 -0.035851 -0.018146 -0.010807 -0.004176  0.008402 -0.006595  \n",
       "14  0.020636  0.003547  0.049664 -0.002028 -0.008991  0.004571  0.061222  \n",
       "15 -0.023964  0.022567 -0.053990 -0.016509  0.036098  0.027670 -0.004943  \n",
       "16  0.106019 -0.009461 -0.003806  0.062932  0.079343  0.137155  0.109241  \n",
       "17  0.056651  0.018764  0.051028  0.042209  0.031008  0.054646  0.006278  \n",
       "18  0.001525  0.067671  0.068577  0.049779  0.016939  0.029236  0.074081  \n",
       "19  0.032093  0.144085  0.022734  0.025620  0.037008  0.070098  0.080403  \n",
       "20  0.056546 -0.010143  0.026973  0.026784  0.046330  0.051733 -0.007363  \n",
       "21  0.008371  0.009270  0.000314  0.033496  0.016149  0.051962  0.041463  \n",
       "22  0.008397  0.051871  0.047583 -0.000327  0.035797  0.013310  0.017549  \n",
       "23  0.059683  0.032810  0.076297 -0.063109  0.026982  0.005348  0.046878  \n",
       "24 -0.015000  0.040393 -0.038858  0.004261  0.011824  0.031112  0.017326  \n",
       "25 -0.015324  0.130405  0.034373  0.027895  0.027287 -0.003708 -0.002203  \n",
       "26  0.025962  0.055138 -0.028406  0.012296 -0.026018  0.005183  0.056403  \n",
       "27 -0.001532  0.047971  0.103280 -0.006360 -0.018283  0.064031  0.041432  \n",
       "28 -0.026711  0.045183 -0.015509 -0.067490  0.000194  0.023764  0.049320  \n",
       "29  0.025906  0.039961 -0.010619  0.003036 -0.009943  0.038557  0.038876  \n",
       "..       ...       ...       ...       ...       ...       ...       ...  \n",
       "70  0.079540  0.060663  0.025775  0.037291  0.092307  0.033993  0.064758  \n",
       "71  0.056417  0.058878  0.045797  0.046718  0.031760  0.099875  0.058896  \n",
       "72  0.076898  0.004181  0.047923  0.064638  0.006270  0.039787  0.068219  \n",
       "73 -0.051967 -0.035380 -0.020994 -0.006525  0.014680 -0.062977  0.013133  \n",
       "74  0.019614  0.057383  0.036852  0.005912  0.069153  0.060787  0.056461  \n",
       "75  0.067905  0.035068  0.012411 -0.006795  0.036763  0.043492 -0.023244  \n",
       "76  0.007357  0.010644  0.022261  0.010252  0.004005  0.050057  0.029424  \n",
       "77  0.010325  0.031849  0.026000  0.022931  0.038934  0.066006  0.064813  \n",
       "78  0.032239  0.057028 -0.023626 -0.067268  0.038292  0.019182  0.042420  \n",
       "79 -0.037809  0.031491 -0.013209  0.009175  0.060704  0.023780  0.029602  \n",
       "80  0.128250  0.012779  0.029048  0.016496  0.015618  0.053902  0.065303  \n",
       "81 -0.008506  0.024721  0.043040 -0.034767 -0.023597 -0.007354  0.053350  \n",
       "82  0.005376  0.052777  0.019367 -0.011342  0.057290  0.040896  0.086057  \n",
       "83 -0.038140 -0.010744 -0.045802 -0.015397  0.071529  0.027285  0.027263  \n",
       "84  0.053197 -0.039772  0.079466  0.057603  0.040496  0.025826  0.039700  \n",
       "85  0.021129  0.018881  0.135343 -0.004924 -0.009714  0.000816  0.118277  \n",
       "86 -0.027641  0.032945  0.024596 -0.019934  0.047558  0.024277  0.068216  \n",
       "87 -0.019825  0.035176  0.112391  0.019199 -0.037031  0.036926 -0.012113  \n",
       "88  0.019856  0.024830  0.007172  0.052531  0.038087  0.010057  0.084209  \n",
       "89  0.063562  0.003973 -0.021729  0.029588  0.022644  0.089395  0.109009  \n",
       "90  0.094381  0.017140 -0.007522 -0.017833  0.015158  0.080709  0.036836  \n",
       "91  0.025030  0.012215  0.057974 -0.017018  0.017971  0.134937  0.131733  \n",
       "92 -0.034640  0.021631  0.162098  0.063559  0.008251  0.029513  0.030643  \n",
       "93  1.000000 -0.006888  0.133294  0.001097  0.050904  0.019473  0.041432  \n",
       "94 -0.006888  1.000000  0.021927  0.000560 -0.025452  0.010766  0.050308  \n",
       "95  0.133294  0.021927  1.000000  0.047543 -0.019899  0.019591  0.145466  \n",
       "96  0.001097  0.000560  0.047543  1.000000  0.033105  0.035789  0.047178  \n",
       "97  0.050904 -0.025452 -0.019899  0.033105  1.000000  0.018918 -0.015441  \n",
       "98  0.019473  0.010766  0.019591  0.035789  0.018918  1.000000  0.045663  \n",
       "99  0.041432  0.050308  0.145466  0.047178 -0.015441  0.045663  1.000000  \n",
       "\n",
       "[100 rows x 100 columns]"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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