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Dynamic Time-Series Modeling
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Dynamic Time-Series Modeling\n",
"\n",
"Original: http://kldavenport.com/dynamic-time-series-modeling/\n",
"\n",
"Today’s article will showcase a subset of Pandas’ time-series modeling capabilities. I’ll be using financial data to demonstrate the capabilities, however, the functions can be applied to any time-series data (application logs, netflow, bio-metrics, etc). The focus will be on moving or sliding window methods. These dynamic models account for time-dependent changes for any given state in a system whereas steady-state or static models are time-invariant as they naively calculate the system in equilibrium.\n",
"\n",
"In correlation modeling (Pearson, Spearman, or Kendall) we look at the co-movement between the changes in two arrays of data, in this case time-series arrays. A dynamic implementation would include a rolling-correlation that would return a series or array of new data whereas a static implementation would return a single value that represents the correlation “all at once”. This distinction will become clearer with the visualizations below.\n",
"\n",
"Let’s suppose we want to take a look at how SAP and Oracle vary together. One approach is to simply overlay the time-series plots of both the equities. A better method is to utilize a rolling or moving correlation as it can help reveal trends that would otherwise be hard to detect. Let’s take a look below:"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"import pandas as pd\n",
"import pandas_datareader as pdr\n",
"import pandas_datareader.data as web\n",
"import statsmodels.formula.api as smf\n",
"\n",
"import datetime\n",
"import seaborn as sns\n",
"%pylab inline"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\User\\Anaconda3\\lib\\site-packages\\pandas_datareader\\google\\daily.py:40: UnstableAPIWarning: \n",
"The Google Finance API has not been stable since late 2017. Requests seem\n",
"to fail at random. Failure is especially common when bulk downloading.\n",
"\n",
" warnings.warn(UNSTABLE_WARNING, UnstableAPIWarning)\n"
]
}
],
"source": [
"start = datetime.datetime(2017, 2, 5)\n",
"end = datetime.datetime(2019, 2, 5)\n",
"\n",
"oracle_data = pdr.DataReader('ORC', 'google', start, end)\n",
"sap_data = pdr.DataReader('SAP', 'google', start, end)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"slideshow": {
"slide_type": "-"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Open High Low Close Volume\n",
"Date \n",
"2017-02-06 90.89 91.33 90.81 91.25 1222105\n",
"2018-02-05 107.78 108.95 105.40 105.87 1350594\n",
" Open High Low Close Volume\n",
"Date \n",
"2017-02-06 11.94 12.08 11.88 12.08 570711\n",
"2018-02-05 7.40 7.43 7.07 7.17 3087030\n"
]
}
],
"source": [
"print(pd.concat((sap_data.head(1), sap_data.tail(1))))\n",
"print(pd.concat((oracle_data.head(1), oracle_data.tail(1))))\n",
"\n",
"# only need time-index and daily-close.\n",
"oracle = oracle_data['Close']\n",
"sap = sap_data['Close']"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5,1,'One Year Daily Close Price for Oracle and SAP')"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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6FgfXn5SA7TC3wsP8PPCyWQ+pJykiIiKu062ONf3VrOQwXlmTT2OLAy93a18PZ9Apq23m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sxRL6SIiIhUrCYXkWY2HPgBsB0wEtjHzIYld/+Pu49Kfu4vQTsrT9Vq+HA2LF8UzuaSzz30RPau\n0DPViIiISItXzOjsLYBn3P1zADN7AjigJK2KwfTfwyO/DL9bK+jUGzr3hf4jYZfT4KsV6okUERGR\nilVMETkTuNDM1ge+AMYDzwMfASeZ2VHJ9dPdfVnRLa0k7jDjllAwfmMirFgEyz+ATxbCv2+Ez5eG\n5VREioiISIVqchHp7rPN7NfAw8AKYAawGrgSOB/w5PK3wLG1H29mk4HJAAMHDmxqM7Jp0axwNpq9\nL4FvHldzuzv8+bsw575wXbuzRUREpEIVNbDG3a9199HuviuwFJjn7ovcvcrdq4FrCMdM1vXYq919\nW3fftnfv3sU0I3tm3hFOB7jlfmvebgbjzgy/d+gednGLiIiIVKBiR2f3SS4HAgcCN5tZ/7xFDiDs\n9q58r/8Drt0T5j/V8HLuoYgcOg469Vr7/iFjYciusME2oagUERERqUDFnvbwjuSYyFXAf7j7MjO7\n0cxGEXZnzwd+WOTfSM87z8Hse8Cr4Zkrw203HgD7XQEjDqn7Ma8/Ah+/XdPjWJsZTLitedorIiIi\nUiZFFZHuPqaO2yYW85yZ8uR/w7yHwu+b7gXjfwN3/hCmHg+fvBNGWef3JlZXwz/Ogx6DYfjB9T9v\n2w7N2WoRERGRZldsT2TcFs+BrQ6E711ac2aZiXfCXSfAI78IPY7jfwutk5dx5u2w6BU46Fpo0y69\ndouIiIg0s5ZXRH76HjxyfhgZvcup9S/31efw8QIYdeSapyZs0x4O/F/oPhCe+h/45F34zoVh2ft/\nAv22DoWniIiISMRaVhH5zrPhmMavVkDHnrDTydCqnrFFH80DHHrXMZdjq1aw+3mhkLz/J3B5MgC9\n79Zw6I31P6eIiIhIJFpWEfnvv4Spd751Fjx2AXwwAwZ8o+5lF88Nl70amMtx22Nhs/Hw6j3w1XLY\n4URo27H07RYRERHJmJbVZfb2dBi0I2wzKVx/49H6l138Wjhd4fobN/ycXfrB9pNhzOkqIEVERKTF\naDlF5PJFYRf1oJ2hc5+w6/mNx+pffskc6Dk0HAMpIiIiImtoOUXkgunhctDO4XLjb8GCZ+Crz+pe\nfvHchndli4iIiLRgLaeInP80tO0E/UeE6xt/G6pXwcPnwptPwJcrapatWgVL36h7UI2IiIiItKCB\nNW9Ph4HbQ+u24frAHcMpCJ+7JvxYK+g7HAbuEEZdV6+G3pun22YRERGRjGoZReQ7z8GHs2D4ATW3\nte0Ak+6BL5bBwhfgnX+Fn5duClMAAfTZIp32ioiIiGRc/EXkjFvgnpPDqQhHTlj7/o49YNju4Qeg\najV8+CqsWAT9RpS1qSIiIiKVIt4isroqnMd6+h9g8Bg49AZYr+e6H9e6Tc1xkyIiIiJSpzgG1rw9\nHaZdAu7h+spP4ObDQwH5zePD+a4bU0CKiIiISKNUfk/k8g/gliPhi6XQvksYdX3zEWF09d6XwDeP\nS7uFIiIiItGpvCLy8Ythzv0wdFyYMPylv8CqL2Cj7eHB/wpnjbFWMPEuGDIm7daKiIiIRKmyisiZ\nU+HxX0HPjeGfV4R5HgHG/wa23A+uGhMGyhxxM/Qckm5bRURERCJWOUXkh7Ph7pNCj+Oke0MB+cm7\n4NXQJ5nP8aTnQk9kbi5IEREREWkWlVFErvwkHPfYvjMccj20aQe0W/uMMh26ptI8ERERkZYmO0Xk\n8kXgVdB1wJq3V1fDnSfAx2/DpL9B1/7ptE9EREREvpadKX7+//fh0m1g1l1r3v7Ub2HOfbDnhTBo\np3TaJiIiIiJryEZPZPUqWPgstOsCt02CGd+FLfaFFR/AoxfC1ofA9j9Mu5UiIiIikshGEbny03B5\n1N0w9+/w4g3hEmDAaNj392CWXvtEREREZA3ZKCK//BS6bgAbjIYNt4GxZ8JH86BjT+jUG1plZ6+7\niIiIiGSliFy5HIZNrOltbN0G+myRbptEREREpF7Z6OLzKth0r7RbISIiIiKNlI0islUbGLJr2q0Q\nERERkUbKRhHZbzi0Wy/tVoiIiIhII2WjiEQjr0VEREQqSUaKSBERERGpJCoiRURERKRgKiJFRERE\npGBFFZFmdoqZzTSzWWZ2anJbTzN72MzmJZc9StNUEREREcmKJheRZjYc+AGwHTAS2MfMhgFnAo+4\n+zDgkeS6iIiIiESkmJ7ILYBn3P1zd18NPAEcAOwHXJ8scz2wf3FNFBEREZGsKaaInAnsambrm9l6\nwHhgI6Cvu78PkFz2Kb6ZIiIiIpIlTT53trvPNrNfAw8DK4AZwOrGPt7MJgOTk6srzGxOU9vSzHoB\nS0r0XN2AT0r0XE1VyjxpGwgsSLsRJZT2uinl+zPtLKXW1DxZ2ObrUqnrp67Xs1Kz1KeceZr7/dkS\n101Wt/m6NJRnUGOewNy9JC0xs4uAhcApwDh3f9/M+gOPu/tmJfkjKTCz59192xI919XuPnndSzaf\nUuZJm5ktdvfeabejVNJeN6V8f6adpdSamicL23xdKnX91PV6VmqW+pQzT3O/P1viusnqNl+XUqyf\nYkdn90kuBwIHAjcD9wCTkkUmAXcX8zci87e0GxCZj9NuQGT0/iw9vaalpdeztPR6ll6Lek2bvDs7\ncYeZrQ+sAv7D3ZeZ2cXArWZ2HGFX4yHFNjIW7t6i3lxlUCm7DCqC3p+lp9e0tPR6lpZez9Jraa9p\nUUWku4+p47aPgN2Ked6MuTrtBpRYTHliygJx5YkpCyhPlsWUBeLKE1MWUJ61lOyYSBERERFpOXTa\nQxEREREpmIpIwMws7TaUUmx5RKRwMX0OxJQlJlov2dfc60hFZPD1saGRbBTdAcys2IFTqTOzzcws\nmvepmX3bzPql3Y5SMLMJZjYy+b3itxsz6573e8XnIa7P9w65XyJZN7Fol3YDmkNM/3O8mY9ZjOaF\nagoz28vMHgR+Y2YHQPO/4M3JzLqZ2UPAAwDJ6SgrkpntYWb/Ao4ngvepme1kZrOAo4HOKTenKGa2\nu5lNA34HfAMqfrv5rpk9AVxuZj+Dis+zt5ndC5xvZjun3Z5imNmeZjYduMzMjoSKXzf7m9mlZtYz\n7bYUw8zGm9kDwO/NbGLa7SkFM/uemf047XaUSvI5cJOZnWtmmzTX36n4nqpCJd9i2wIXATsCvwY2\nBA4xs5nuPi/N9hVpJbAM2NnMDnH328ystbtXpd2wxkjWTRvgbOAI4D/dfWr+/ZX4D8TMWgM/AC50\n95vSbk9TJOumA3A94VSmFwD7Aesl91fM+yyfmW0HnAdcSJgy6iQzG+7uM1NtWBOZ2TbAuYRMXYFJ\nZjbM3a8zs1buXp1qAwtgZr2BXwIXA8uBU8xsoLv/qgKzGHAA4X3WBXjczO6spAzw9d6tnxKynA2s\nD+xjZh9X6tQ2SabTgROAgWb2qLu/VMGfaR2o+YJ/AXAw8CMzu9zd3yr136v4Hp5CefAVobdurLvf\nA0wnzHVZ8he4XJJCpTvwDHAYcCmAu1dVyu6fZN2sAqqB23MFpJmNMbO26bauKF0BA+43s3ZmNtHM\nNjGzdlAZu+eSdfMF8Fd3H+fuDxK2m4nJ/RX3YZvYGXgy+Rx4B6gC3sjtzqqEdVPL7sA0d7+fcKKH\nD4ApZtbN3asrJU/Szr7ADHe/y90fAc4EzjCzXpWUBb7uPX0T2IVwVrfvEzovKkqyd+tN4HB3f4Bw\ncpH3qODd2kmmOcDmwI+BPya3V+RnmruvBGYDByeF/a+A0YROppJrMUWkmZ1sZteY2fEA7v4Pd19t\nZuOBqcCmwEVmdliyfKY/oPLyHJv00FUBnwJ7u/u9wMtmdk7Sq+JZzpOXJXeqqKuA/mb2ZzN7hfDN\n91rg2GT5zGaBNfIcl9zUChgKjABuA/Yl9IT/MfeQ8reycfKy/ADA3e9Obm9N+NI1y8w2SrONhaid\nB/gHMMHMLgWeBAYAVwK/SKuNhagjz2OEnqEeSdG/ivC58FPI9q5gM5tkZnvA1+1cAeyU2/Xr7q8S\ntp9L02tl4+XnScx094/c/Q7Cejkw90Uyy+rIMRV4y8zauvtyQjG8Xjqta5pku7nYzA5NbrrP3Ve6\n+++APmY2IVmuIjov8vLkTu5yNbDQzNq7+2uEL8f9m+WPu3v0P4Tj0J4B9gKeAH4ObJLctx2wafL7\neOBBYHDabW5Cno1JdjMmyxwLrAaeT663TbvdjcxyFtAD2B/4K+HboRF2nd4HDEy7zU3I05GwS+4N\n4LBkuc7AYmDbtNtc4PtsaN79WwPPAV3SbmsT85xN6L3vAVwC7JsstwUwE9gq7TYXmOe/ks+AS4F7\ngWnAn4HvEArjTmm3uZ4cPYDbgfeBl4HWeffdANxYa9l/AUPSbneheQhfJnNzM+8MPAKMrvVYS7v9\njcmRt0wH4C5gs7Tb28hMBpwGPE3YzTs72Y765C1zAPBu2m0tMk/vvGU2Su7v2hxtaCk9kbsBv/bQ\n/X46oes9d5D2s+4+N1nuVcI/9qwPSKmdpwPh9JJfAN+1MLjmZOBR4O3kMVnNVDtLe+CH7n4XMNnd\nX/OwJbxMOFf2qvSa2ih1rZsTgXOATskP7r4CuIXwQZ1VdW0338/d6e6vEN5zh6fTvILVztMWOMnd\nlxH2ROS2ldeAfxLei1lW13vtKHefQnjP/dLdjyHsxurg7p+l19T6Ja//Q4Ti/QXCtpJzErCXmX0z\nuf4ZMAP4qqyNLEBDeZLPMtz9aeAlwuf15rm9MLn7s2Ad6yWnO+G9NcfMNjKzg8rZxkIlr++3gLPc\n/XZCATaS8EUrt8ydwFwzOwPCQMI02toYDeTZK2+xEcAcd//UzAaY2ahStiHqItJqhun/G9gHwN2f\nJ3x7729rj1w8mtAt/1G52liIBvJMB4YQjrd5GHjW3Ue5+57AODMbkqUPJ2gwy9PAEDPbudY/vUmE\nHr1lZW1oIzWQ5ylgS8KuhJ8S/iHua2ZnEXojZqfQ3AatY7sZkNtuksMKHgI6ZPkQg3VsN4PNbEvC\nF67/NbP1CL3Hw4GFKTR3ndax7Qwzs13cfYG7P5wstzehFzxz8t43N7j7x8AVhN28gwDc/VPCoQVn\nm9kkatbNijTauy4N5fFwHGfrvPX3O+BnhF7kPrUen6pG5MgNyh0KdDGzUwnHR/ZOobl1qv1a5r3u\nzwNjAJIvYHOBrcxss7zFTwD+28w+ADYoQ3PXqQl5tkru7wWsNLMphD2tJT38KKoi0sx2NrONc9e9\nZuTb00ArM9s1uT6T0EU/IHncUWY2k1CIneDhWKLUFZBnFvAuYdTfOe5+Vt7TDPRmGJFVqALXzXvU\nrJuDzGwG4cPqBA8HDaeuwDwLgW3c/QbC8Z67AAOBfdw99UKlqdtN8sWkD/BZlr6kNGHdbO7ulxAO\nrr+dUPQf6O4flrHZ9WrCttM/edyuFqYuGkZ436Wujiy5nrmVyeVzwN8Jo5hzy1xGKLi2AQYRBgx8\nUs5216fQPO5elRRhfYHLCF9eRrn7BfmPL7cm5Mjt2dqGMMvJJoTj8TPxPkt0zL+St928Tih8t06u\nPwF0I/z/JOmpuwa4g3C4wfXlae46FZont/z+wI8I62gvL/Eo+iiKSDMbnezCfZTw4uVuz+WbRyi0\nDrMwbH8h0I9QNELYVTrZ3Se5+6IyNr1OTcjzDuEf+yB3/yr/227au7BKsG7mAj9y96MqdN0sJBRa\nwwDc/VHgZ+4+2d3fK2/r11TEuhmc9zRnuPufytTkBjUxT18g1wNxHDDB3Y9w9/fL2PQ6lWDbmQ+c\n6O4HuPuS8rV8bQ1kMVt7YufLgE3MbCsz62tmmyTbzWnJZ3Sq2w0Ulae3mQ0BlgBT3P17ab7Xilwv\n6xMGco1195OysF4AzGwHM7uDMO/rnhYGAeaffONZwkCTPcysjYcBWxsA2yb3f0TYbg7JQqYi8myX\n3H8jsJu7n+Lu75a6fRVdRJpZWzP7I2Ek0h8IXbXjkvta51XqywkHmbcjTCzelnAs2hIAd3/J3aeX\nuflrKTJPd5Ld8Llvu2Vu/hpKuG5ecfd/lrn5aylBnsW554pg3Xx9uIeH6bJSVYI8iyBkSXbdpaqE\n284Cd59V5uavoRFZPOmZ62hmnSG0G7gTeIXQq9I1uT31KVdKkGca0CP5jF6QSghKkuNJQqfFTHef\nloPQFVYAAAb/SURBVEqIOpjZOMKu96mEPQvfB3pYmFd0NYC7v04YELgJYdoogC9Jjol293c8HO+d\nuiLzvJncP9XdH2uuNlZ0EUk48P1JYIyHaW2mAlsk1XgVgJn9AriJMJHwOYQP2WnJ9ax0U+fElCem\nLBBXnpiygPJkOU9jspxLmIlhaHL9CMLAoN8AW7v7i6m0vG6x5Ck2x/CM5KhtBPCcu/8V+Ath8NyK\n3BcvM7vAzK4lDBT6A7Cdmb0ALCUU0llTTJ6HytHAijtjjZntACz1MKL6s+TFzWkNVHmY/9EIU5AM\nA8509zeSxx9LmOpiebnbXpeY8sSUBeLKE1MWUB4ynKcJWTYDfpLLQph/dJxn4FhuiCdPLDny1coE\noTA+z8zeIxS8s4ErLJze+B1CQXyOu89PHj8BaJOFPRBQoXk8A3MdNeaHsLv2PsIunLNI5jwjzJPU\nKvl9E8KuqR65+/Ie36qc7W1JeWLKEluemLIoT7bzlCBL63K2t6XkiSXHOjJ1zrtvO+BPwEHJ9eMI\nA2VG5i2Tme2m0vNU0u7sToTu5inJ77vC16djq7ZwEPD8ZJmxufsgHIju2TtHaUx5YsoCceWJKQso\nT5bzFJsl9WMea4klTyw58tXONCZ3h7s/S5hqKDfv66OEIm0ZZHK7gQrOk+ki0sLUO2PNrKuHUUVX\nA7cSJs/d3sxy08BY8iJ2SB66Mnc7pD+QISemPDFlgbjyxJQFlIcM54kpC8STJ5Yc+QrI1J4wB+yJ\nyUN3A3omy2UmUyx5MldEWtDfzB4jTDB9JHClmfXycG7Lzwnnu+0BfBvCtyYLI8pWELrod8jdnk6K\nGjHliSkLxJUnpiygPJDdPDFlgXjyxJIjX4GZdgNw9y8JE593NrMngSMIZ6ZKfd7X2PIA2Tomkppz\nc24K/CX5vQ3hXLBTay17GnABYW6r9fJuz8w5omPKE1OW2PLElEV5sp0npiwx5YklRwkydQc6Jrd1\nBIamnSPWPLmfTPREmlkbM7sIuMjMxhJGhVXB1zPjnwzsmNyXcw3QmXCav7dyXb/unvq5lWPKE1MW\niCtPTFlAeRKZzBNTFognTyw58pUg03wz28Ddv3D3N8vc/LXElqe21IvI5IV7gdB9+zpwPrAK+JaZ\nbQdfd63/Ejgv76F7E44RmEGYeyv1meUhrjwxZYG48sSUBZQn76GZyxNTFognTyw58pUg00uETCU/\nM0tTxJanTml3hRJGIU3Mu34F4eTnRwMvJLe1IpzO61ZgcHLbfsCuabc/5jwxZYktT0xZlCfbeWLK\nElOeWHLEnCm2PHX9pN4TSajSb7XkfJDA08BAd78OaG1mUzyMPtqQMBnqfAB3v9vdn0yjwesQU56Y\nskBceWLKAsozHzKbJ6YsEE+eWHLkiy1TbHnWknoR6e6fu/uXXjMX1R7UnGf4GMKpmO4FbgZehJrp\nB7IopjwxZYG48sSUBZQHspsnpiwQT55YcuSLLVNseeqSmdMeJpW6A30Jw9khzN7+c2A48JYnxwW4\nh/7eLIspT0xZIK48MWUB5UmlkY0UUxaIJ08sOfLFlim2PPlS74nMU004ufgSYERSnZ8NVLv7U57l\nA0vrFlOemLJAXHliygLKk2UxZYF48sSSI19smWLLU8MzcGBm7ocw0Wk18BRwXNrtUZ44s8SWJ6Ys\nypPtn5iyxJQnlhwxZ4otT+7HknCZYGYbAhOBSzzM0l7RYsoTUxaIK09MWUB5siymLBBPnlhy5Ist\nU2x5cjJVRIqIiIhIZcjSMZEiIiIiUiFURIqIiIhIwVREioiIiEjBVESKiIiISMFURIqIiIhIwVRE\niog0wMyqzOwlM5tlZjPM7Mdm1uBnp5kNNrMJ5WqjiEgaVESKiDTsC3cf5e5bEc59Ox44dx2PGQyo\niBSRqGmeSBGRBpjZCnfvnHd9KPAc0AsYBNwIdEruPsndp5vZM8AWwFvA9cAfgIuBcUB74HJ3/2PZ\nQoiINAMVkSIiDahdRCa3LQM2B5YTzn+70syGATe7+7ZmNg44w933SZafDPRx9wvMrD3wNHCIu79V\n1jAiIiXUJu0GiIhUIEsu2wKXmdkooArYtJ7l9wRGmNnByfVuwDBCT6WISEVSESkiUoBkd3YV8CHh\n2MhFwEjCMeYr63sYMMXdHyxLI0VEykADa0REGsnMegNXAZd5OBaoG/C+u1cDE4HWyaLLgS55D30Q\nOMHM2ibPs6mZdUJEpIKpJ1JEpGEdzewlwq7r1YSBNJck910B3GFmhwCPAZ8lt78MrDazGcB1wO8J\nI7ZfNDMDFgP7lyuAiEhz0MAaERERESmYdmeLiIiISMFURIqIiIhIwVREioiIiEjBVESKiIiISMFU\nRIqIiIhIwVREioiIiEjBVESKiIiISMFURIqIiIhIwf4PmokWGAodxAYAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x92119409e8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Create dataframe from the two series for plotting\n",
"df = pd.concat([oracle, sap], axis=1)\n",
"df.columns = ['Oracle', 'SAP']\n",
"\n",
"plt.rcParams['figure.figsize'] = 11,10\n",
"df.plot(subplots = True); plt.legend(loc='upper right')\n",
"plt.title(\"One Year Daily Close Price for Oracle and SAP\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It's intuitive to see the divergence in directionality between Oracle and SAP in the subplots above, but a (arbitrarily chosen) 50-day rolling correlation plot highlights the differences a little better."
]
},
{
"cell_type": "code",
"execution_count": 109,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x9214ee66a0>"
]
},
"execution_count": 109,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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4rJYBg0alFGlJdlq7ZLbjZBVsshqrYcez52RhtxrHHk2bCZDgS4wD0udLiKE5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\nSUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x9214fcff98>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Compute a day-to-day percentage change array (pd.Series) w/default settings\n",
"oracle_pc = oracle.pct_change(periods=1, fill_method='pad', limit=None, freq=None)\n",
"sap_pc = sap.pct_change(periods=1, fill_method='pad', limit=None, freq=None)\n",
"\n",
"plt.rcParams['figure.figsize'] = 10, 5\n",
"# pd.rolling_corr(oracle_pc, sap_pc, window = 50).plot(title = \"One Year 50-day Window Correlation of Oracle with SAP\")\n",
"oracle_pc.rolling(window=50).corr(other=sap_pc, pairwise=None).plot(title = \"One Year 50-day Window Correlation of Oracle with SAP\")"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.17722661632581346"
]
},
"execution_count": 77,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"oracle_pc.corr(sap_pc)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "-"
}
},
"source": [
"An even better approach would be to use a function that would convey the differences of volatility, which can be measured in many ways. The most basic parametric method is standard deviation for a given time range. Another method is the relative volatility to stock to a general index or market. This is commonly referred to as the beta. If Oracle has a beta value of 1.3 this would mean that it historically moved 130% for every 100% move in a given benchmark such as the S&P 500.\n",
"\n",
"A very basic dynamic volatility model could utilitize ordinary least squares:"
]
},
{
"cell_type": "code",
"execution_count": 108,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" OLS Regression Results \n",
"==============================================================================\n",
"Dep. Variable: oracle_pc R-squared: 0.031\n",
"Model: OLS Adj. R-squared: 0.028\n",
"Method: Least Squares F-statistic: 8.075\n",
"Date: Mon, 05 Feb 2018 Prob (F-statistic): 0.00486\n",
"Time: 22:58:48 Log-Likelihood: 699.00\n",
"No. Observations: 251 AIC: -1394.\n",
"Df Residuals: 249 BIC: -1387.\n",
"Df Model: 1 \n",
"Covariance Type: nonrobust \n",
"==============================================================================\n",
" coef std err t P>|t| [0.025 0.975]\n",
"------------------------------------------------------------------------------\n",
"Intercept -0.0021 0.001 -2.256 0.025 -0.004 -0.000\n",
"sap_pc 0.2893 0.102 2.842 0.005 0.089 0.490\n",
"==============================================================================\n",
"Omnibus: 193.283 Durbin-Watson: 1.723\n",
"Prob(Omnibus): 0.000 Jarque-Bera (JB): 3987.436\n",
"Skew: -2.795 Prob(JB): 0.00\n",
"Kurtosis: 21.709 Cond. No. 108.\n",
"==============================================================================\n",
"\n",
"Warnings:\n",
"[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
]
}
],
"source": [
"#ols_model = pd.ols(y = oracle_pc, x = {'sap_pc' : sap_pc}, window = 50) # Window attribute makes it dynamic\n",
"ols_model = smf.ols('oracle_pc ~ sap_pc', oracle_pc).fit()\n",
"print(ols_model.summary())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"OLS is not sophisticated enough for more advanced use cases due to the assumption that the response variables are Gaussian (Normal). A Generalized Linear Model, however, incorporates other types of distributions and includes a link function g(.) relating the mean μ or the estimated fitted values E(y) to the linear predictor Xβ (η). There is plenty to learn about with GLM but for now let's continue with practical statistical methods.\n",
"\n",
"Here we utilize the rolling_mean function to create new data that will allow us to create a great plot showing a 20 and 50 day Simple Moving Average for the adjusted close time-series data:"
]
},
{
"cell_type": "code",
"execution_count": 117,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"<style>\n",
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" text-align: right;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Open</th>\n",
" <th>High</th>\n",
" <th>Low</th>\n",
" <th>Close</th>\n",
" <th>Volume</th>\n",
" <th>SMA20</th>\n",
" <th>SMA50</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2017-02-06</th>\n",
" <td>90.89</td>\n",
" <td>91.33</td>\n",
" <td>90.81</td>\n",
" <td>91.25</td>\n",
" <td>1222105</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-02-07</th>\n",
" <td>91.36</td>\n",
" <td>91.99</td>\n",
" <td>91.31</td>\n",
" <td>91.96</td>\n",
" <td>1532969</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-02-08</th>\n",
" <td>91.72</td>\n",
" <td>92.22</td>\n",
" <td>91.62</td>\n",
" <td>91.79</td>\n",
" <td>653804</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-02-09</th>\n",
" <td>91.90</td>\n",
" <td>92.17</td>\n",
" <td>91.71</td>\n",
" <td>91.71</td>\n",
" <td>548787</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-02-10</th>\n",
" <td>91.70</td>\n",
" <td>91.94</td>\n",
" <td>91.64</td>\n",
" <td>91.73</td>\n",
" <td>417028</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Open High Low Close Volume SMA20 SMA50\n",
"Date \n",
"2017-02-06 90.89 91.33 90.81 91.25 1222105 NaN NaN\n",
"2017-02-07 91.36 91.99 91.31 91.96 1532969 NaN NaN\n",
"2017-02-08 91.72 92.22 91.62 91.79 653804 NaN NaN\n",
"2017-02-09 91.90 92.17 91.71 91.71 548787 NaN NaN\n",
"2017-02-10 91.70 91.94 91.64 91.73 417028 NaN NaN"
]
},
"execution_count": 117,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"SAPdf = pd.DataFrame(sap_data)\n",
"\n",
"#SAPdf['SMA20'] = pd.stats.moments.rolling_mean(SAPdf['Close'], 20)\n",
"#SAPdf['SMA50'] = pd.stats.moments.rolling_mean(SAPdf['Close'], 50)\n",
"\n",
"SAPdf['SMA20'] = SAPdf.rolling(window=20, center=False).mean()\n",
"SAPdf['SMA50'] = SAPdf.rolling(window=50, center=False).mean()\n",
"\n",
"SAPdf.head(5)"
]
},
{
"cell_type": "code",
"execution_count": 120,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0.5,1,'SAP Daily Volume')"
]
},
"execution_count": 120,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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i52IUknU+N0PKVvjsZqhp+aBxs75s6tjeZ4+w1zKqrdP0n6dnVDt5OH4tRoT7\nEZtRTIWtZfvo/vPH4/zfysMk5pazJ7Wgvh61Ej7aenYi61KmAlVFURRF6YBiEnJ55YdjZwU5aQUV\nuIhzZ1SFEIzrHcCk/sEEeJpbpPk7o6iCIC/zGRm7Lj4mOP4D/PAkLLke/tEDXusP6/4f9J7CUwFv\n8LHHvTDzfTi5HWL+ddH1aGzd0VMM6uLjcJqs1syo5pfZ8HV3bXLWgxHhftTUyhafz3ZHUj5RXX0R\nAnJKquq7IIzrE8iXe9JaratDe1CBqqIoiqJ0QB/EJPPe5kRmvL2tftlSe63kfwczGdcnELPRcM5r\n/GfOED6YNww/dxMFF9n0L6UkJa+CUF83grzN+FHCQ4bV9IkeA8vmwL6lUF0J/W+Eaf+Eu36AOV9g\ncveitKoaBt8CV8yFLf+Cg9FgbZmps3JKrOw/WcSUAcEO93dyN1FYUd0qS4bnl1fh30Q2FaB/iDaw\nK7mFBznllFTRM9ADfw8TOaVV5JbZEAKeuLYvFTY7n/9yskXLa0+qj6qiKIqidDBSSmIzionq6svJ\nggpu/O9W/vm7K/CyGMkqtvLUdc7PzVk/8r3c+ebv6F0niQz1YVCY1s81MbeMp1bFsiulgIdHd8a8\n4Rm2WRbhhg38x8PUl6HvNIeDpbwsRhJz9azw1Fcg7RdYdT8IA3S9EiImQt/pEBzpdP0aWnc0G4Br\nBzoesOTrbsJWU0tltR13U8uGPXlltmanngr0MmN0EfUreLWE2lpJTqmVYG8LgV4WckqsCKEF5AO7\n+DC2dwBLtqfw+7E9nPox09GpjKqiKIqidDAZRZUUlNv47bAw1jwyht7BXjz0+T6eWHEIHzdXJvYP\nOvdFGvDzMDndR7XaXsv/Wx3L/I93kZxXzmvrjjPtPzEcySzm39NDeTzrcdj5Dltdx/B7z3fgzv/B\ngBubHNHvZTFSog/2wc0XHt6lZVvH/FHLwG58Ad4dDUk/n9c91Vl3NJseAR70DvJ0uN+3FZdRzSur\ncjiQqo7BRdDZx1I/CK0lFFbYqLZLgr3MBHubySnVmv7rFh24b1xPckur+N+BzBYrsz2pjKqiKIqi\ndDB1K0oN6uJDqK8bX95/FS99H8eS7SnMvzoci+v5Zco6eTg/RVN6YSX2WklIxTHW/mcpvUUO67xL\n6OqSj2FjDhjNMPtzUnP7McqJ63lZXCm11iCl1BYcMLhC96u1x8RnoCwHFk+Fbx+DB3eAyfkR69Zq\nOzsS87hrdI8mFzPo5KaFOoXlNro0M+frhcgvszmcmqqhUF+3+tW8WkJ2idYfNdjbQpCXmbisEkxG\nl/plXMdEBNCvsxcfxCRx87A0Kef9AAAgAElEQVSwS34FShWodgAvvvgiX3zxBQaDARcXF95//32e\nfPJJkpKSSE1NrX+TzZgxg/Xr19dPUQXw+uuvs2DBArKzs/Hx0ZpoUlJS6N+/P337asvIjRo1ivfe\new+AvXv31s+jOn36dN54441L/k2sKIrya3MovRiji6BfZy8ATEYXFt4YyW+HhhHRROawOZ30Se9r\na6XDVawAqKmCwhSsu9fzhetnXG04Sg1Gqj1DcQsMB5+h4NtVa6YPGczv+zlXtrfFlZpaibW6FjeT\ngwDbMwhufBOWXAcbnoVprzp9X4m5ZVTbJVeE+Z69s6IAfvx/TI5dySLXSGqTBXSZ7vS1z8VWU0tx\nZTX+Hmaqa6vZn72f7Ipscitzya3IJb8yn9zKXE66ZWGtMvHcjuHc0OsGogKjLup7N7tUy84GeVsI\n8rKQW1qFyejCkK7aAgNCCO4b15M/f3mQzfG5TOh7ftn3jkYFqu1sx44drFmzhn379mE2m8nLy8Nm\n0371+vr6sm3bNsaMGUNRURFZWVlnnb9s2TJGjBjBqlWrmD9/fv32Xr16ceDAgbOOf/DBB1m0aBGj\nRo1i+vTprF27Vk36ryiK0sEcziimT7DXWZnTuj6j56XGxpDSzcwgiaqtibhVngK3TuDTVQs8fcIg\nOQZ+XADWYvoDKSKY8rFP4TH6PoyWCyizgbplVEut1Y4DVYDwMTDyAfjlPQgbAYNuduraCdla4qZP\nsCfYyiFtF6Rug5RtkLEHZC3lPaYz5MRmAtfPpTZ7Ni43/KfZrG1FdQVH8o+QXpqOROLq4orJYMJs\nMGMymLAYLJgNZkqtEhe3VI5Y9zN1xSZyKnPqr+FmdCPQLZAAtwACjYEYK2JZczyZr+K/4srOV/KH\nIX+gb6e+uLue/3ynOSVaoBrsbSbI20yt1LLgk/qfHkx2/eBQ/rH2OB/EJKlAVbk4WVlZBAQEYDZr\nKfuAgNNzwM2ZM4fo6GjGjBnDypUrmTVrFkeOHKnfn5iYSFlZGf/85z956aWXzghUmyqrpKSEq666\nCoB58+axevVqFagqiqK0gbpR5+fKpkkpOZxRzNSWWM0obRf871Em5cYxyQRsBIwWqHHQZ7L7aBg2\nn/eOuvJWnBuHr7lWm4D1ItUFqiXWGoK8mzlw8vOQdRC++QO4GCByphZ8NrNAQPXxdfzP9CYRS0uh\nshBqa7RBWiFXwJX3sb/bUJZm/cJPFX3wsORTUbYD47KRGA0WXITLWQ+b3UZZdVmT5TXmEQ478124\nKnQUfxv1N3r59CLQPRAPVw8oSIIDy6hM+QhRVYLNpzPfUsi7LgeZ98M8AALdAunm3Y1w73C6eXcj\n0j+SkSEjmy2zruk/0MtMkJc2HZeU1Df9g5aBnzm0C+/+nEiNvRZjE9NnXQpUoKp7dderHCs41qLX\n7OfXjyevfLLZY6ZMmcJzzz1Hnz59mDRpErNnz2b8+PEATJw4kXvvvRe73U50dDSLFi2qXxIVtGzq\n3LlzGTt2LMePHycnJ4egIO2XU3JyMkOGDMHb25sXXniBsWPHkpGRQVhYWP35YWFhZGRktOg9K4qi\nKI7d8v4OhnX34/+mNd9mnl5YSVFFNQO7XEQmsywHNv8Ddn8I3l04POYdHtxg4+27xnFF757aIKbi\ndChO0x4mT4icBS4u7Nizi/CAqhbrFuZt0QYzxWYUsyMxjzuuCnd8oNEEtyzVprr6aj6s+ZMWfHoE\nQedBpx+FKdp9VeTzO7uNdGMoov8N4O4PXUeR7teVrbn72ZS2ie27FuJj9sVeE0y4x1DGWXKpSdxA\njZ8/tQF9qfXuQq3BFbu0I6XE1eCKv8Wfvn596eHTA6MwUlNbQ5W96oyHzW5jX3oOb29M4sNbbmFC\n7x7aPVhL4PDXcGCZNmcsgsrOo7k19XpeumkGt+35K9cf/46dV9/LyU5dSK3M5WTpSTalbaLAWgDA\nrN6z+NvIv2E2OB6klV1ixc/DhNloIMj79DGNB3XVBa7lNjs+bipQVS6Qp6cne/fuJSYmhk2bNjF7\n9mxeeeUVAAwGA2PGjGH58uVUVlYSHh5+xrnR0dGsWrUKFxcXZs2axVdffcXDDz9MSEgIJ0+exN/f\nn7179zJjxgyOHDnicA451T9VURSlbRzNLHFquqDdKVrAMqx7p/MvJCcOdrwNh74Euw1G3g/XPIU9\nx076+m3k2T21LKnJHQL7aI9GUvPLibyYILmRuozqc2uOUlBuY+bQMDzNTYQfnkFw94+w4y3IPwG+\n4VCYDKcOafdVq4/cj5gEwQP5924rqd1m8cBVXnyX9B0xR94kuVhbmSnMM4w/RP2BOwbcwYjntzCg\nW1cevm6AFsDvfAcS94OLURvU1fta6DMVAiKcvq+c7DRqSt3p3ilI7w/7NziyGmoqwb83TPw7DJ5N\nntWbY69vIaNMMnTWh/h8fjPXbn1fu4hvNy37G3I9pQF9+Lj0GB8c+4ytGVuZ228uU7pPpatXlzO+\nq7NLqgjy0lthPV0RxiKMnvGsyPialdkV9cF0UWUFnr0rmfj1QnzNnfAQoVzfZzTju46nT6ezX/eO\nSgWqunNlPluTwWBgwoQJTJgwgUGDBvHJJ5/U75szZw4zZ85k4cKFZ5xz6NAhEhISmDx5MgA2m42e\nPXvy8MMPYzab67sSDBs2jF69ehEfH09YWBjp6en110hPTyc0NLT1b1BRFOUyV15VQ7nNTlbxuUd/\n704pxMtipE+wl/MFpO2Gza/AifVgdIMht8GohyCgNwB+7hUA55z0v9peS1phJdcNDnG+7HPw0jOq\ndWXnlFjxDGxmQJjBFcb86eztNTbIPabNOhDYl0qbnXe2L6Kn4TVmrzmKycXE8M7DuaXPLYzpMobu\n3t3rAzxfdxOF5TYtSJ/wJIz9C6Tvhvi1EP+jtorWuv+ndX+4dTmYz/3cJ+aW42oQhHVyg9WPaUHq\n0Dsg6jboMqy+20SIWQuuM4sqwdUCt6/U+tFmHTz9iPsWL+BRV3dGXv8yH2Rv5Y19b/DGvjcwSh96\n+YUS4hFMkHsQx6vKcfNx5c8/r2ZrxlY8e2vvqcLqrvT2DMditGAymMgptrMtp5gbhnQnPi+TuPzj\nvLn/Td7c/yb9/PoxqdskJnabSC/fXh06aaUC1XZ2/PhxXFxc6N1b+5/JgQMH6N69O7GxsQCMHTuW\nBQsWMHfu3DPOW7ZsGQsXLmTBggX123r06EFqairu7u74+flhMBhISkoiISGBnj174ufnh5eXFzt3\n7mTkyJEsXbqURx55pO1uVlEU5TJVtxZ7VrH19DRNTdiTUsCw7p0wNDU6v7HSbFh6k9aX85qnYNjd\n4OF/xiG+Hlqw2NSa97W1kvs/20tUV1/stZJw/6b7hZ6vuoxqndzSKno2F6g2xWiCkMHkV+az4fiX\nfH38O9zD91Fe68dfh/+Vmb1n4mVyHGBGhnqz6XguJdZqrSuCwQjdr9Iek5+FwlQ4uhq5/ll+eeU6\nymd9zsRBXZutzomcUnoEeOCatAEOfwXj/w9+s+Cs47wsrnhZjKcn/TeaoNdvtEcdazFkHYJvH2Xk\nj88x8p6fSDOZuP7D96hwySS1ppLqgAwO5h6kyFxIEVCdE8D1Pa9nxQ5JWUlnPn7sDsI6nR6ctSU+\nl41bf+E2H3/K4r+gJr2CkH5D2dmzP98XHOatA2/x1oG36O7dnWu6XcPkbpMZFDjovF+W1qYC1XZW\nVlbGI488QlFREUajkYiICBYtWsTNN2sjHoUQPP7442edFx0dzQ8//HDGtpkzZxIdHU1ERATPPPMM\nRqMRg8HAe++9h5+fHwDvvvtu/fRU06ZNUwOpFEVR2kBuqRaoVtjslFbV1PfbbKyw3EZCThkzhnRx\n/uKbXwF7FdwdA/69HB7iZTZidBFNTvqflFfOT0ez+Ulf5Sk8oOUD1c7eFk6VWMnRn4tzsdlt/JT6\nEydLT3Kq/BSnyk+RVZ5FakkqtbKWAHMYVTlT+OK2JxgU6nj51DqPTuzN9f/dyocxyfx5soNm707d\nYfRjxJeYGPXL/3Hixzsh4mttdoQmnMgp48pgtPlfA/rC2D83eWwXXzcympv03+IDPcbCbSvgw4mw\n4m6C5v9IcfbVjO0dwO6UAkqK3PjsriuZ8K8NPDihF49P6Y8Qgm07t5BqzSMocxMcS4XSLCjNYkhu\nGrvNcQR+U4wdA0dFV7qlbKRX+hZueyCGHFcTm05uYsPJDXx65FPi8uP4YMoHzT6P7UEFqu1s2LBh\nbN++/aztP//8s8Pj6+ZQTU5OPmvfa6+9Vv/v3/72tw7PHz58eH22VlEURWkbdRlVgFPF1iYD1T2p\nhQCMCPdz7sK58bD3ExhxT5NBKmhJj04eevO3AwfSigDwMBkot9lbNKPqaTZy68hu/KZvEPcu3VMf\ntDdne8Z2Xtr1EqklqQAEuAXQ2b0zEb4RTA2fyqTuk1i8sZKvizLoFxx4zusN7OLDtIGd+SgmiflX\nh+Pn4XiS/vWWybxvS+HVsg+11bJG3ANBA7TuCAaT/nClShoxFcbzoGk1lOfCnM+1LglNcHrSf/9e\ncMMb8OU8rD+/BlzBdYNCeGxib+5espsZ72yjVrrQ2cdDy8pXFvJH+8eMNf+A6Sv9+gYzeIdgNAex\npXYwEcMn81VJJJ8dqeLda7yZtn0ufHknQfO+YXa/2czuN5sSWwmF1sJz168dqEBVURRFUS5STomV\nQC9zk036DYOzrGJrk/1P96QUYDK4MNjZ+VI3PAuu7jDuiXMe2sndtck+qgfTivA0G/nk7hGsj8up\nX46zJQgheGnmIH1UvWgyoyql5GDuQT49+inrUtfRzasb70x8h5EhIzEZzqzPvpOFLN+zndtGdsPV\nyamX/jy5D2uPnOK9zYn8bXp/h8ccTCtiXe04Um2d+dJ3PYYNzzk8zgysMwGFwHX/htAhzZYd4Gni\naGaJU/VkwE0QOROvX17jBpf7CfIezvBwP5bffxV3fLQLgGAvM6Ruh+V3MLUinxj33zDud49B58Fa\nFlgIiout/OXlDbwcMoj0glNALsmEwIx34Ks74eOpMHc5+HTB2+SNt6m5ucPajwpUFUVRFOUCncgp\n47k1R9kSn8vjU/rwh2t6OzzujEC1mczaz8dzGdLN17klUlN3wLE1Wr9Uz3NnFTu5m8gusVJtrz0r\nuDuYXsTgMB+GdfdjWHcns7nnSQhBgKfgWNF+ViYcJbs8m+yKbE5VnNL+XZ5NaXUpFoOFh6Me5q6B\ndzmcoqnGXssTKw4R4m3hyalOLo8F9A72YmZUFz7ZnsI9Y3oQ7G0565jDGcX4e5jYW96HPRPmMdKv\nAirywF6tzaJgt4G9ml0nTvHJ1hP836yr6Tps6jnLdjcZKbfVOF1Xrn+douw0/pv3FiXb4yBzGP2D\nB/DN7B58sLeMMfkrYOVz2qwBd6xkbOfBZ81566l3uSiz1lBSqfVNzi2tggk3agHqiru1bgZzl50z\n0G5Pl32geq5O7ZcbR1NYKYqiKI49seIgJ3LK6NfZi/c3J3H7qO74up+djcwtq8LX3ZXiymqyih33\nVTyRU8bx7FIW3jDg3AVLCT89A14hMOphp+oa7u/B8j1pjHhxPbeP7M7dY3rg52HCWm0nLquE34/t\n6dR1LsTB3IN8dvQzykPWs9dWw97tIBD4u/kT7B5MN69ujOg8gkj/SK7pdg1eJi+s1XZWHUrn2sjO\nuJtOhyuxmSWcyCnjtVuuqJ9RwFl/nNSH/x3M5I/RB3j4NxFc1cu/ftBaTqmVrGIrD03oxTs/J3Ig\nrYiRPXtpq3c1EpNynLUE8lrUFKcWRfAwG6iw2Z2POdw68f2Q96j44e/cXXocYjaBrKULsBDgGBA+\nFm5ZinB3/MPC3dWAENqKYKXWGv0e9R9MfabAPT/CF7Ph4+kwaxH0v+Hc9WoHl3WgarFYyM/Px9/f\nXwWraEFqfn4+FsvZvzIVRVGUM+07Wci+k0UsvGEAo3r5M+2NGBZtSeIJB1m+3FIbIT5uuBpcONVE\noLo2Vlsme+pAJ6aGStoE6bvg+tebXQ60oedmRDKxfxAr92Xw9s8nWLwtmdtHdWdY905U2yVRXX2d\nus75KLQW8s/d/+TbpG/xMnkRJCZQU9qbL+bPINAtEFeD40Azt7SKe5fu4UBaEZP6Z/H+HcPrA8o9\n+jyzYyICHJ7bnG7+7iyY3p///BTP7R/9QmdvCzcNCWXWkDAyirQpvCb0DWLNoaz6fruOJGSX0d3f\n3al5cUHLqNprJVU1tc5ly4FTZbW8Y7+Nex6ZDnYr5B7X5sktToeIayB0aLNBsouLwNNkpLSqhhJr\ng4xqneBI+P0GiL4Vlt8BkxbC6MdaZDWylnRZB6p184rm5ua2d1U6DIvFcsbqVYqiKMpppdZqfkkq\nwFpjZ/X+TLwsRn43vCseZiPXDw5lyfYU7h7T44zlLEHLqAZ4mnA1CLJKzgxUq+21VNjsfH/4FMO6\nd6KzjxPJgi3/Bq9Qbc5OJ5mNBqZEdmZKZGcSskt55+dEPoxJYtEWbX9LB6px+XE8tukxcitzuW/w\nfdwz8B5eWJPI2pOnCPVseg7vqho78xbvIjmvjNnDu7J8TxrPfnuEZ2+MRAjBruQCuvu7E+Sg6d4Z\n94zpwW0ju7E+LptV+zL4KCaZ9zcn4W0xIoQ2lVVUV19+OprN418dxNNspKyqhgpbDWVVdsqrajia\nWcK4Ps4Hyh4mLTitsNmdDlRzSq0EeJq1AN3FDUKjtMd58LQY9aZ/LaOa17h/sFcwzF8Dqx/Ulnzt\ngC7rQNXV1ZUePXq0dzUURVGUS0BKXjk3/HcrpVWn+xreP64nHvoqS3+c1JvvDmXy3s+JPHX9mc33\neaVV9Ar0wM3VQEp+ef32DXHZPLU6tr47wFPXOR7kc2ZFtkHqVrj25WZHmjend7AXr8+O4rGJvXlv\ncyIVNrvDPpvno6a2hti8WLZnbmd75nYO5x0m0C2Qz6Z/RqR/JKAt81lQbnPYT7bOG+sTiMsq4cN5\nw5k0IBhvNyMfxCTTzc+de8b0YE9qIb/pG3RRdbW4Grh+cCjXDw4lv6yKbw9msmp/BsHeFjzMRh4Y\n34tqey0bj+VQY6/Fw2w8/TAZGNM7gDubWgrWAXf9PVJhq2lyxoHGckqrzlgi9UJ4mo0UVtiorLYD\nOJ5xwdUNfrsYZG2Hy6bCZR6oKoqiKIqzVu7PoNxWwyd3X4mPmyuH04u4qcF8p70CPZk1NIxPd6Zy\n77ie9YGflJLc0ioCvcx4W1zZkZRPbmkVz357hDWHsugb7MWdV4dTXFnN74Y3P8k8padg5b3g3QWG\n3XnR9xQe4MErvx18UddILErkkyOfsP7kekptpQgEgwIGce+ge5nbby7+bqcXH6gLvPLKqgjxcTvr\nWvHZpby3OZHZw7syaYA2N+qCaf3JKKrkxe/jsFbbKSi3cWWPC1hetgn+nmbmj+7B/NGnE1cDQr15\n9/ZhLVaGh6kuULU7fU52SRWhzmTXm+FpMZKpz98a7G0mu6SKSpsdN1OjrK6LC+Dc7AltTQWqiqIo\ninIOUkq+O5TJyB7+jO+jjbB31FT+2MTerN6fwdubTvDcTQMBKLHWYLPXEuhppqZWUmqtYdJrm6m0\n2fnL5D7cP74XJuM5goRqqzbCP+bfUFkEd6/VVqJqR4dyD/H+offZkr4Fi8HCteHXMiZsDFeFXIWP\n2fH0WkFeWuCVU+I4UP0luYBaCY9MjKjf5uIieO2WKE4V7+Rf6+IBGO7sPLMdhLtZCwzLq5wf+Z9b\naiWqq5PTlDXB02wkOa8Y0H5IZZdUkVdWRVc/5/o1dwQqUFUURVGUczh2qpTE3HLuGt18d7Gufu7c\nMqIry3ad5L5xPQnr5F7f3BroZa4ffNMn2JOXZw0mIqiZpUSlhMx9sP9ziF2hLbPp0xVu+QRCLi4L\nejEqqiv47/7/8nnc5/iafXko6iHm9J1DJ8u5s5yBXlpGtalJ/xOyS/E0G+nie2YQa3E18OGdI5j1\nzjbKbXZ6tuDKWW3hfDOq1fZa8sttBHpdXEbV2+Jav2xur0BPtifmk1OqAlVFURRF+VX57lAWLgKm\nDux8zmMfuSaCFXvTeWvjCV757eDTgaqnmVE9/Vn10NVcEeaLi8s5+gP+9AxsfxOMFuh/Iwy5DcLH\n6c20bUtKSUZZBrF5sby5/03SStOY3Xc2fxr2JzxcnQ8ag/RAtalJ/+OzS4kI8nQ4E4+fh4kVD15N\nUYXtkpupx910fhnVvLIqpDz9fF0oT/PpMK9XoPY6ObMyWEeiAlVFURRFaYaUkjWHMrm6V8BZo/kd\nCfFx49Yru/HpzlSemNqvfvnUQC8zLi6CId2c6F+Znwg734FBv9NWPrJcXBPwhUgqTuKLuC+IL4wn\nvjCe8mptEFiYZxiLr13MiM4jzvuadc9fcl6Zw/0J2WVM7N/0QKkAT7NTr0FH42E+v4xqTon2nrnY\nAW51k/4D9AzUsve5ZSpQVRRFUZRfjSOZJaTkV3D/+F5OnzNraBeWbE9h07Ec4rJKcDUIQnzP7pPZ\npI3Pa2u2T3mxzYNUKSVfxX/FP3f/EyEE/f36c0PPG+jj14e+nfrSz6/fWUuaOstkdGF0hD8fxCQD\n8MTUfvWj//PLqsgvtzW5vOylrG56KmdXp6rLOLdkRrVHgAdCqIyqoiiKovyqfHc4C4OLYGrkuZv9\n6wwM9SHIy8xPR7M5kFbE+D5BZwQNzUrbBUdWwbgntHku21CRtYintz/Nz2k/c3Xo1bww+gUC3c+9\nPOv5+OjOEbz4XRwfxCSzJ7WQt24dShdfNxJytCxr719hoFo/PVWVcxnVuKwShOCi+5J6NciodvIw\n4eduqs/wXyo65lwEiqIoitIB1DX7j44IoJOT81+CNlJ9Yv8gfjx6ilMlVm6KanqC+zPYa2DNn7Xp\np0Y/doG1vjCpJanc9v1tbMvYxl+H/5V3J73b4kEqaAOjnp8xkLduHUJCdhnXvRnDhrhsErJLAW2g\n2a+Nm+v5ZVTXx2UT1dXX6TlXm1L348hFaFldHzdXSiqrL+qabU0FqoqiKIrShMMZxaQVVHL9YCeW\nNW1kYr9gpNQG0kzq72RmdPeHkH0Ypr4M5rYL2BKLErnj+zsotZWy+NrFzIuch4to3RDh+sGhrHlk\nDKE+btzzyR4+2pqMl9lI54vsl9kRGVwEbq4Gp/qoniq2cii92Pn3TDPq+qh6WVwRQuBlMVJidX6K\nrI5ABaqKoiiK0oQ1h7JwNQiuHeB8s3+d0REBeJgMTI3sfPYE645YS2DzK9BzgjbKvw1UVFewPXM7\n9627D4OLgaXTlhIVdH7LdF6M8AAPVj50NVMjO5OSX0HvYMcj/n8NPMwGp0b9bziWDcDkARcfqHpZ\nXAHwdjPq/3Wl1HppZVRVH1VFURRFcUCb5D+Lsb0D8XF3Pe/z3UwGVj08mmBn58Lc+Q5UFsLEv7fa\nUpZSSrZmbGVn1k725+wnLj+OGlmDr9mXxdcuJtwnvFXKbY7F1cBbtw7hrU0n6Psr7J9ax83kXEZ1\nQ1wO3fzc6d3cHLtOqmv699YDVi+LsX653kuFClQVRVEUxYEDaUVkFFXy58l9LvgaTo9gL8uB7W9B\n/xugy9ALLu9cPjz8IW/ufxOTi4mBAQOZP3A+Q4KGMDRoKJ6m9usbajS48MdJF/48Xwo8TMZzZlQr\nbDVsPZHH7SO7t0hmuW4wVV2g6m259PqoqkBVURRFUdBWA6qbKqmqxk70rjRMBhcmR7byyPvaWlj1\nANhtcM3TrVbM1/Ff8+b+N5neYzrPj37+gqeYUi6MuxMZ1ZiEPGw1tUwa0PRcsuejPqPqVtdX1Uip\n6qOqKIqiKJeWbw5kEPXsOooqbJzIKWPkSxtYvieN6waH1GejWlxtLWTsg+/+BIkbYOpLENi3VYra\ncHIDz+18jtFdRvPC6BdUkNoOPMzGc476X380G2+LkRHhfi1SZsPBVKBlVCur7VTba1vk+m1BZVQV\nRVGUy95HW5Mpt9k5nFHM4Yxiiiqq+WDecCb0beHpmWrtkLAOjn8P8eug7BQIFxg2H4bf07Jl6WLz\nYnli8xMM9B/Ia+Nfw9XQSoG30ix3k6F+xSlH7LWSjcdy+E2/oPrM/sXyMJ3dRxWg1Fpz0VNftRUV\nqCqKoiiXtdiMYg6lFwPaROtHM0sI6+TWIqOuz1BRAF//XsuemrwgYiL0nQYRk8HDv2XL0hVXFfOX\nn/+Cv5s/b018C3fXi5tAXrlwHqbmM6r7ThaSX25r0fedwUXwx0m9Gd9H+8FVl1ktqaxWgaqiKIqi\nXAqid5/EbHTBw2wkLquUo1klDAjxbtlCCpLg01lQkgHX/RuGzANj6wYK9lo7C2IWkFOZw9KpS+lk\n6dSq5SnNczc33Uc1MbeMP0YfwMtiZFyfls3iNxyk5u2mBaqXUj9VFagqiqIol62iChur92dy3aAQ\niiqr2ZtaSFphBTde4eRKUs5I2QZfzYfaapj/HXS9suWu3Yx/7fkXMRkxPD3qaQYFDmqTMpWmeZiM\nVDjIqB5MK+KuJbtxEbDs3lGt1yeahk3/l87IfxWoKoqiKJetxVuTKauq4b7xPfn2YCYbj+UAEBnq\nc+EXtVVAxl7I3Kf99+g30Ckcbv2y1QZL1ZFSEpMRw0eHP2Jfzj5u7387t/S9pVXLVJzjbjJira7F\nXisxuGhTT8Uk5HL/p3vx9zTx6d0jCQ/waNU61AXBJSpQVRRFUZSWJ6XkkWX7ierqy+/H9qzfduxU\nKf3Ps7m+uKKaj7elMG1gZ/p19uZETln9vgGh59n0n7gRTmyAkzsg6yDU6pkzjyC4+hGYsABMrReE\nVNdWszZ5LYtjF3Oi6ASdPTrz5IgnmdtvbquVqZwfD7O2OlmFrQYviyv/O5jJX748QESQF5/cNYKg\nNlg6ti6jeikto9ohAlUhxGLgeiBHSjlQ3/Y7YCHQH7hSSrmnwfELgHsAO/ColPLHNq+0oiiKctGk\nlKw+kME1/YLxcTt3kwymUfIAACAASURBVOf3h0+x5lAWO5MKuGt0Dwwugq0n8rjjo10suWsEE/o6\nP//kR9uSKa2q4dGJvQHqA10fN1dCfc4jaNjyT9j4AhjM0GUYXP0odLsKwoaDe8tMM9SciuoK5q+d\nT1xBHBG+Ebw45kWm9ZiGq4sa3d+RuOsj8Ctsdr7em86za44yItyPD+YNd+q93xLq+qheSpP+d4hA\nFVgCvAUsbbAtFpgFvN/wQCHEAGAOEAmEAuuFEH2klOdel0xRFEXpUGIzSvjT8oPMiArlP3OGNHts\nVY2dV9bG4W4ykFdWxY7EfMb0DmB7Yj4A3xzIdDpQLa6s5uNtyUyN7FwfoIb7e2BxdWFAiLfzqwJt\nfV0LUgfPgRveANfWz4o1JKXkxV9e5FjBMV4e+zLTe0zHRagp0juiuozq4m3JvL85iSkDgnlz7hAs\nroY2q0PdAgCX0mCqDvFullJuAQoabYuTUh53cPhNQLSUskpKmQycANqmZ7qiKIrSon5J1oLM1Qcy\n2aEHnI7klFq5b+le0gr+P3v3HR5llfZx/PvMJJM+6b0TWuhdiiCIIoooomJdu6yrrq9tXXvBgl3X\n7lpYsLC6KiqCDaV3pJdQU0id9EmbzGTmef94kgCmMEkmDe7PdXEJk2fOOUEgv5xynypev2IIvh5u\nfLc9C4AtadqXj1/25GKxOTdn8fGaVMosx2ZTQSvlc++5vbnpzETnBr/3e1j2JAy4DGa80+EhFeD7\nw9/z/eHvuW3wbVzY40IJqV1Y3Yzqp+vTGRBt5J1rhnVoSAXtz7ifh1u32qPaHf9ERwNHj/t1Zu1r\nDSiKMltRlC2KomzJz8/vkMEJIYRw3ua0IqL8PYkJ9OKhb3aSZ7Y0eObXvXlMfX01G44U8syMAUzp\nH8F5/SP4aXcuZouNHUdLGRBtpMJqZ3ntYajmlFbZ+HhtKlP6hTfYizp7QpJzdSz3/wSL/grRI+Di\nt0HXsYEDIKs8i7mb5jI8fDh/HfTXDu9ftIyPQfszUmG1c8HASNxcVNS/pbrbNardMag2th6jNvag\nqqr/VlV1hKqqI0JDXXy7iBBCiDZRVZXNacWMTgrmtSuGkF9WzWXvrSO7pArQDp089M0ubl2whUh/\nT5bcdSbXjo4H4LLhMZRV1/Dg1zux2h3cOaknIb4eLN6ZfdJ+/7M2rcFsagsGrS33L7wSQnrDVQs7\nZSbV7rDz8OqHAXj2zGfRd0JQFi3j7XFst+W5yS6+TKIFjF7u3WqPancMqplA7HG/jgFO/i+TEEKI\nLuVwfjlFFVZGJQQxMiGIz28dTW6phfnr03A4VC57dz3/3ZzBbWclsej2cfQM86t/75ikYMb3CmHp\nrlwARiUGc8HACH5PMVFe3fRskdli46M1Rzi3XzgDoltQgspihtRV8PXN2nJ//0vgxh/B1/nDW660\nYO8Ctpq28tCoh4j2bXRRUXQxdTOqCcHe9Azz7bRxyIxq+/seuFJRFA9FURKBXsCmTh6TEEKIFtqU\nWgzAqETtZPzg2ACGxAaw4UgRu7NL2ZtjZs7FA3jw/L4Y3Bp+uXpkWjI6BXqG+RLkY2D64CgsNge/\n7ctrss8vNh3FbKnh/042m1pRAFsXwKLb4K2R8HwczJ8OexbBpEfhso/B0DnXke4v2s+b297knLhz\nuCjpok4Zg2i5uhnVc/uFO39Yrx34ebpTVt19ZlS7xKl/RVEWAhOBEEVRMoEn0A5XvQmEAksURdmu\nqup5qqruURTlS2AvUAPcISf+hRCi+9mcVkSIr4HE44qcj+4RzDsrDrNkVw6KAhcMiGjy/X0jjDx+\nYT8Ca+8sHx4XSKS/J4t3ZHPxkMZnGf9ILyYxxKfp2VSHA9a8AsvngmrX6qBGD4eBl0P0MIga1iEl\np5pSWl3KPSvuIcAjgMfHPN6pgUe0TJS/J/84rw+XDovp1HEYPd04ZOo+M6pdIqiqqtpUReJFTTz/\nLPBs+41ICCFEe9uUWsTIhKATwtboHsG8+fshFqxLZ0CUP8G+Hs22ccO4Yyf0dTqFCwdF8p91aZRW\n2vD3blibMiXX3HQxf1WFb26F3V9pS/tn3gsRA6ELhEFVVdldsJtX/3iVnIoc5p03j0DPwM4elmgB\nRVG4Y1LPzh6GNqMqp/6FEEKIpmWVVJFVUlW/7F9nWFwgBr2OKpuds3q3/BDs9MFR2OwqP+/JbfCx\niuoa0osq6RvRRFBd/7YWUic9ApfNg8hBnR5SC6sKmb9nPjO/n8nVS69mV8EunhjzBEPChnTquET3\nZfRyw2ypQVUbPYfe5XSJGVUhhBCnl82pWu3TkQknBlUvg54hsQFsSitiQiuC6sBof+KCvFm8M5tZ\nI2NP+Nj+vDJUFfpG+DV8Y/Z2WPYE9L0QJvyj0wMqwPs73ue9He9Ro9YwKHQQj495nKkJU/EzNDJ+\nIZzk5+mO3aFSZbPX13btyrr+CIUQQpxyNqUV4efhVn8r1PGm9A8ns7iSoXEBLW5XURSmD47kvZVH\nKCivJuS4rQMpOWUADftUVfjpIfAKhIvf6hIhddHBRby1/S2mxE/h9iG3kxSQ1NlDEqcIo6e2Jaa0\nytYtgqos/QshhOhwm1KLGJ4QiF7XMBTefGYiq/95Nu6tLIg+fXAUdofKj7tPXP5PyTXj6+FGTKDX\niW848BNkrIOJD2phtZMtz1jOnPVzGBM5hucnPC8hVbhUhL/2zVt2ScPLNboiCapCCCE6VFGFlUOm\n8gbL/nUURWk0wDqrT7gfvcJ8WfKn4v8pOWX0jfA7dnjLboPtC2HJfRDcE4Zd3+o+XWV5xnLuXXkv\nycHJvDLxFdx1DQ+ECdEWcUFalY2MoopOHolzJKgKIYToUJvTtP2pZyS2T5knRVEYkxTMnmxz/YER\nVVXZl2umb6QfWCth4/vwxlD49jbwDIBL3gd954bC+pAalMz7574ve1FFu4gN8kJRIL2wsrOH4pSu\nvzlBCCHEKWVTahEGNx0DY1pwM1QLJQT7UGapobDCSoivB1klVZRZapis2wavz4DKAogdDdNegV5T\nOn1f6uLDi3l83eMkByXz3rnvSUgV7cbDTU+Uv5cEVSFE95ZeWEGAtwF/L1l6FK61Oa2IIbEBeLi1\n3/30iaHa8mZaQQUhvh6k5JSRoOQwYdcTEJQIV3wC8WPbrX9nqKrKroJdfH3wa745+A2jIkbx2qTX\nMBqaKJ8lhIvEBXmTXtg9lv4lqAohGlBVlRlvr8XTXc971w5ncGzLT18L0Zjy6hr2ZJu5fWL7HhBK\nDNaC6pGCCkYkBHEwO5+33d9Ap3eHqxZCQOxJWmg/mWWZ/HDkB5YcWUKaOQ0PvQfXJF/DfSPukz2p\nokPEB3uzrJmrhrsSCapCiAbMlhqKK20oio3L31/PMzMGMGtE531hF6eOrenF2B1qkwepXCUm0As3\nnUJagTZrNGDXC/TXpcMlX3RqSP183+c8v+l5VFRGRozkpgE3cU78ObLULzpUfLAPBeVWyqtr8PXo\n2lGwa49OCNEp8sxa2ZKnLurPz3tyeeCrnezKLOWxC/thcJMzmKL1NqcVoVNgWHz7loFy0+uIC/Im\ntaACdv6P8aXf87P/LM7rM7Vd+23Ot4e+Ze6muUyMmchDZzxElG9Up41FnN7ig70BbYtX/6j22yvu\nCvIVRwjRQF1Q7RthZP6No/jrhB58siGdaz/cSHWNvZNHJ7orh0O72nRgtH+HzOIkhvjgl7Me9bvb\n2ejoS0q/e9q9z6b878D/eHzt44yOHM0rE1+RkCo6VVyQFlQzusGBKgmqQogG8szVAIQbPXDT63jo\ngmSenjGATWlFbDxS1MmjE93V4p3ZHMgr56YzEzukv7Pdd/F4+TNY/BK41XovfaI7vph/tb2alze/\nzJz1cxgfM543z34Tg97Q4eMQ4nh1M6ppElSFEN1R3YxqmJ9n/Wszh0bjplPYcKSws4YlujGb3cFr\nvx6gb4Qf0we182yitQKWP8dVB+/jqBrKZ71ex4wvfSM69jT9uux1zFo8i/l753NFnyt4feLreLp5\nnvyNQrQzP093gn0M3aLov+xRFUI0YDJbMHq64WU4Vj7Ix8ONwbEBElRFq/yRXkxaYSVvXT0UXRtu\nnWqW3QZbF8CK56HCRGHCdC5NuQTDHxX4GPT1y53tIb8yn50FO0kpSiGlMIW9RXsxVZqI8Y3hncnv\nMD5mfLv1LURrxAV7d4taqhJUhRAN5JmrCTc2nPkZ3SOI91ceoaK6Bp8uflJUdC35Zdp2kj7h7XS6\nfe93sOwpKDoMcWPgys/QBQ6GF5cTE+jF3ZN7t0tAdqgOFuxZwL+2/osatQadoiPBmMDIiJEMDR3K\njF4z8NB7uLxfIdoqIdiHTaldfyuXfKURQjSQV2ZpIqgG8/byw2xJL+as3qGdMDLRXRVXWgEI9GmH\n/Zk7voBFsyE0Ga76AnqfB4pCMLDziSm46dtnl1thVSGPrH2EtVlrmRw3mRsH3EjvwN54uXm1S39C\nuFJckDffbs+iusberpdvtJUEVSFEAyZzNaN7+DZ4fXh8IO56hbWHCiSoihYpqtCCaoCrbzqzmOHX\nxyB6ONz0C+hP/LLWXiF1Y85GHlr9EKXVpTxyxiNc0ecKlE6+hlWIlogP9kZVIbO4iqTQhv/edxUS\nVIUQgHYb1ZPf7+GiIdGYyiyEGxsuV3ob3Dirdxjz1qYyPD4QBW2fU0cfUhHdT3GFFaOnm+uD48oX\noNyk3Tal75gvae9uf5d3d7xLvDGed895lz5BfTqkXyFcKb729rb0wgoJqkKIri/XbGH++nR2ZJZi\ns6uNLv0DvDJrMFf9ewN//eQPAEYlBPHlbWNcPp45i/eSX17Ni5cOOuFQl+ieiiptBLl62T99PWx4\nB4Zfr82odhC9Ts9FSRfx8BkP4+3efge0hGhPx4r+d+0DVRJUhRAAHDKVA7D9aAlAozOqAP5e7nxy\n8ygWrE9n/eFCskurXD6WogorC9anUeNQMZktfHTDyC5/zZ+r7csxs3BTBv+c2veUOLhWXGF17f5U\ni1nblxoQB1OecV27Trh14K2yzC+6vWAfAz4GfZcPqlJHVQgBHAuqdcKamFEFCPb14J5zezMsPhCT\nuRpVVV06liU7s6lxqNx1dk/+SC/mmg83UlJ7GOd0UFhezS3zt7BgfTpvLz/U2cNxieJKK0HeLgyq\nvz8DJUfhkvfBo50qCTRBQqo4FSiKQnywD+mFXbuWqgRVIQSgBVV/L/f6WpNNLf0fL9zogdXuoLjS\n5tKxfLs9m74Rftw7pQ/vXjucfdlmrvz3hvoSR6e6f3y1k/zyasb0COaD1Uc4kl9+8jd1cS6dUc3e\nBps/gJE3Q9xo17QpxGkoPtib9CKZURVCdAMHTeX0DPPl0mEx+Hm4Eep78tqPdWG27iYrV8gorOSP\n9GJmDI0G4Nx+4Xx8w0jSCyu54v319afHTzXvrzzMrsxSLDY7K/abuHFcAm9cNRRPNz1PLt7r8lnr\njlZUaXXNHlVVhSX3g3cInP1Y29sT4jQWF+xNZlEVdkfX/fdFgqoQAoDDpnJ6hvpyx6Qklt13Fga3\nk//zULeP1ZVBdd3hAgCm9Auvf+3MXiF8dMMIjhRUsHRXjsv66iqqrHbm/pjCvHWpHMwrx6HCkJgA\nQv20LRarDuTzy968zh5mq1VZ7VhsDgJdsfS/fylkbYHJj4FXQNvbE+I0lhDsg9XuIKcdzhq4igRV\nIU4TFdU1TX6suMJKYYWVnmG+uOl1Ti37A4T5ac+ZzK5bkt+VVYqfpxuJIT4nvD6mRzC+Hm4cyCuj\ntMrGmLm/sfJAvsv67UxZJdrS246jJezLMQPQN1Ir+XXdmHj6hPsxZ/FeLDZ7p42xLYpq9xcH+bSx\nhqrDAb8/C0E9YPDVLhiZEKe3+NqtXhld+ECVBFUhTgPLU0wMeuoXNh4pbPTjh2r3QPYMa1ktvbDa\nGdVcF86o7s420z/K2ODAiqIo9A73ZX9uGduPlpBTauFgXpnL+u1MR4u12YwjBRVsSivCy11f/wXE\nTa/jqYv7k1VSxbsrDnfmMFutuHa7RptmVCsKYfFdYNoDEx/usJqpQpzK4upKVHXhfaoSVIU4xRVV\nWPnHVzuxO9Qml83rTvy3NKh6uOkJ8jG0aem/pNJaP1NoszvYl2NmYLR/o8/2iTCSnpvPntRsAMqb\nmSXuTrJqg6qqwtJdOfSJ8DvhXvrRPYK5aHAU76483KVnPppSt6+4VXtU7TZY/w68ORS2fw6jb4cB\nM108QiFOT5H+Xhj0OtK68Ml/CapCnOKe/mEvpVVW+kb48VuK6YRDOTV2Bws3ZfD6sgMYPd2IDmj5\nHeVhfh7ktXLpv8xi49zXVvHCTymAFpitNQ4GHB9UK4sgZQn8/Aj3pt3GascN3LT+XP7pthBHReMz\nxN1NZnEV+tpgWmm1kxzZ8KavR6Yl465TeOTbXTi68MGHxhTXLv23+NT/4d/hnTHw80NaQf+/rYWp\nc0EnF0AI4Qp6nUJMkFeX/gZY1k6EOIUdMpXz7fYs/johibggbx5etEs73R/qy9LdObzyywFSCyoY\nHh/Io9OST5jFc1a40bPVM6rvrzgMZXl4pe6GTetIr+zNYOUQ47O2wJEsyNkB+VqIRW/AI3gQ/y6a\nRrRSwF/1P2Dd8RsEPwDj7oZuXNsys7iS2EAvVLRbYpIjG9YFDTd68tAFyTz67W7eXXmYOyb17PiB\ntlL9jGpLlv4zNsCnl0JgIlz1BfQ+r1v/Pxaiq4oP8u7SRf8lqApxCntn+SE83fTcOj4Rq90BwFu/\nH+JIQTm7s8z0Cffjw+tGMDk5rNVFzMONHvUHgBpVchTy90PCmZC3Bw7+AoWHsOUf5LbcA9zvWQVF\nwFKYCkz1AHWzAsZoCOsLAy+H+LEQNQxbtcJLzywD4G1lBq8Gf8fAZU+Coodxd7Vq/F1BZnEVMYHe\nBPkYaoNqwxlVgGvOiGPDkUJe+WU/U/qF0yu8Ywvdt1ZxhRVFAaOXk4epqkrg61u1W6dmrwDPxn8/\nhBBtFx/sw6bUIlRV7ZKXWUhQFeIUdbSoku92ZHPj2ASCa2ui9os08v2ObGICvXjtisFcNDi6fsm5\ntSKMnhSUV1Njd+CmP243kcMOG96F5c+CrRL0BrBbAQUC4kitCWODYzx+UX1ZmOHPJ/fMYP4nH2PT\neXLHbXc1Wnoo2B1CfD0oKK8mTRfLGyFP8EHcO/DrY2ApgTP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2bFv9OahuSS/maFEVd0/u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YADnwCXZ7KBYfbiko3cNXcZO/dUs3RDOUcO6MItsxdxcK8OjDtk/+kQT763FjP4/NDYUyX6dmlH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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x9214e98198>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.rcParams['figure.figsize'] = 11, 7\n",
"\n",
"main = plt.subplot2grid((4,4), (0,0), rowspan=3, colspan=4)\n",
"main.plot(SAPdf.index, SAPdf['Close'], label='Close')\n",
"main.plot(SAPdf.index, SAPdf['SMA20'], label='SMA20')\n",
"main.plot(SAPdf.index, SAPdf['SMA50'], label='SMA50')\n",
"main.axes.xaxis.set_ticklabels([])\n",
"\n",
"plt.title('One Year SAP Daily Close w/ 20- & 50-day SMA')\n",
"plt.legend()\n",
"\n",
"vol = plt.subplot2grid((4,4), (3,0), rowspan=1, colspan=4)\n",
"vol.bar(SAPdf.index, SAPdf['Volume'])\n",
"\n",
"plt.title('SAP Daily Volume')\n",
"\n",
"#savefig('img.png', bbox_inches='tight', transparent=True)"
]
}
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