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notebook.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/yeohaikal/37e0e8689ee781c724c8c4f1391b367c/notebook.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"metadata": {
"dc": {
"key": "3"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "Vt-uk563oEOO"
},
"cell_type": "markdown",
"source": [
"## 1. Meet Professor William Sharpe\n",
"<p>An investment may make sense if we expect it to return more money than it costs. But returns are only part of the story because they are risky - there may be a range of possible outcomes. How does one compare different investments that may deliver similar results on average, but exhibit different levels of risks?</p>\n",
"<p><img style=\"float: left ; margin: 5px 20px 5px 1px;\" width=\"200\" src=\"https://assets.datacamp.com/production/project_66/img/sharpe.jpeg\"></p>\n",
"<p>Enter William Sharpe. He introduced the <a href=\"https://web.stanford.edu/~wfsharpe/art/sr/sr.htm\"><em>reward-to-variability ratio</em></a> in 1966 that soon came to be called the Sharpe Ratio. It compares the expected returns for two investment opportunities and calculates the additional return per unit of risk an investor could obtain by choosing one over the other. In particular, it looks at the difference in returns for two investments and compares the average difference to the standard deviation (as a measure of risk) of this difference. A higher Sharpe ratio means that the reward will be higher for a given amount of risk. It is common to compare a specific opportunity against a benchmark that represents an entire category of investments.</p>\n",
"<p>The Sharpe ratio has been one of the most popular risk/return measures in finance, not least because it's so simple to use. It also helped that Professor Sharpe won a Nobel Memorial Prize in Economics in 1990 for his work on the capital asset pricing model (CAPM).</p>\n",
"<p>The Sharpe ratio is usually calculated for a portfolio and uses the risk-free interest rate as benchmark. We will simplify our example and use stocks instead of a portfolio. We will also use a stock index as benchmark rather than the risk-free interest rate because both are readily available at daily frequencies and we do not have to get into converting interest rates from annual to daily frequency. Just keep in mind that you would run the same calculation with portfolio returns and your risk-free rate of choice, e.g, the <a href=\"https://fred.stlouisfed.org/series/TB3MS\">3-month Treasury Bill Rate</a>. </p>\n",
"<p>So let's learn about the Sharpe ratio by calculating it for the stocks of the two tech giants Facebook and Amazon. As benchmark we'll use the S&amp;P 500 that measures the performance of the 500 largest stocks in the US. When we use a stock index instead of the risk-free rate, the result is called the Information Ratio and is used to benchmark the return on active portfolio management because it tells you how much more return for a given unit of risk your portfolio manager earned relative to just putting your money into a low-cost index fund.</p>"
]
},
{
"metadata": {
"dc": {
"key": "3"
},
"tags": [
"sample_code"
],
"trusted": true,
"id": "RIGU1TrdoEOX"
},
"cell_type": "code",
"source": [
"# Importing required modules\n",
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"# Settings to produce nice plots in a Jupyter notebook\n",
"# plt.style.use('fivethirtyeight')\n",
"#%matplotlib inline\n",
"\n",
"# Reading in the data\n",
"stock_data = pd.read_csv('datasets/stock_data.csv', parse_dates=['Date'], index_col='Date').dropna()\n",
"benchmark_data = pd.read_csv('datasets/benchmark_data.csv', parse_dates=['Date'], index_col='Date').dropna() "
],
"execution_count": null,
"outputs": []
},
{
"metadata": {
"dc": {
"key": "11"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "5HBGHY2moEOZ"
},
"cell_type": "markdown",
"source": [
"## 2. A first glance at the data\n",
"<p>Let's take a look the data to find out how many observations and variables we have at our disposal.</p>"
]
},
{
"metadata": {
"dc": {
"key": "11"
},
"tags": [
"sample_code"
],
"trusted": true,
"id": "ns5vAgI7oEOZ",
"outputId": "477a3d2c-3dbd-4b30-a577-e99c80bbb172"
},
"cell_type": "code",
"source": [
"# Display summary for stock_data\n",
"print('Stocks\\n')\n",
"print(stock_data.info())\n",
"print(stock_data.head())\n",
"\n",
"# Display summary for benchmark_data\n",
"print('\\nBenchmarks\\n')\n",
"print(benchmark_data.info())\n",
"print(benchmark_data.head())\n"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": "Stocks\n\n<class 'pandas.core.frame.DataFrame'>\nDatetimeIndex: 252 entries, 2016-01-04 to 2016-12-30\nData columns (total 2 columns):\nAmazon 252 non-null float64\nFacebook 252 non-null float64\ndtypes: float64(2)\nmemory usage: 5.9 KB\nNone\n Amazon Facebook\nDate \n2016-01-04 636.989990 102.220001\n2016-01-05 633.789978 102.730003\n2016-01-06 632.650024 102.970001\n2016-01-07 607.940002 97.919998\n2016-01-08 607.049988 97.330002\n\nBenchmarks\n\n<class 'pandas.core.frame.DataFrame'>\nDatetimeIndex: 252 entries, 2016-01-04 to 2016-12-30\nData columns (total 1 columns):\nS&P 500 252 non-null float64\ndtypes: float64(1)\nmemory usage: 3.9 KB\nNone\n S&P 500\nDate \n2016-01-04 2012.66\n2016-01-05 2016.71\n2016-01-06 1990.26\n2016-01-07 1943.09\n2016-01-08 1922.03\n",
"name": "stdout"
}
]
},
{
"metadata": {
"dc": {
"key": "18"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "e9c6YeoFoEOd"
},
"cell_type": "markdown",
"source": [
"## 3. Plot & summarize daily prices for Amazon and Facebook\n",
"<p>Before we compare an investment in either Facebook or Amazon with the index of the 500 largest companies in the US, let's visualize the data, so we better understand what we're dealing with.</p>"
]
},
{
"metadata": {
"dc": {
"key": "18"
},
"tags": [
"sample_code"
],
"trusted": true,
"id": "UMFl5ULwoEOd",
"outputId": "fe5605d4-11f6-4a27-9bef-a3a32000e55b"
},
"cell_type": "code",
"source": [
"# visualize the stock_data\n",
"stock_data.plot(subplots=True)\n",
"plt.title('Stock Data')\n",
"\n",
"# summarize the stock_data\n",
"stock_data.describe()\n"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 60,
"data": {
"text/plain": " Amazon Facebook\ncount 252.000000 252.000000\nmean 699.523135 117.035873\nstd 92.362312 8.899858\nmin 482.070007 94.160004\n25% 606.929993 112.202499\n50% 727.875000 117.765000\n75% 767.882492 123.902503\nmax 844.359985 133.279999",
"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>Amazon</th>\n <th>Facebook</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>count</th>\n <td>252.000000</td>\n <td>252.000000</td>\n </tr>\n <tr>\n <th>mean</th>\n <td>699.523135</td>\n <td>117.035873</td>\n </tr>\n <tr>\n <th>std</th>\n <td>92.362312</td>\n <td>8.899858</td>\n </tr>\n <tr>\n <th>min</th>\n <td>482.070007</td>\n <td>94.160004</td>\n </tr>\n <tr>\n <th>25%</th>\n <td>606.929993</td>\n <td>112.202499</td>\n </tr>\n <tr>\n <th>50%</th>\n <td>727.875000</td>\n <td>117.765000</td>\n </tr>\n <tr>\n <th>75%</th>\n <td>767.882492</td>\n <td>123.902503</td>\n </tr>\n <tr>\n <th>max</th>\n <td>844.359985</td>\n <td>133.279999</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x288 with 2 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"dc": {
"key": "25"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "WOHI_oujoEOf"
},
"cell_type": "markdown",
"source": [
"## 4. Visualize & summarize daily values for the S&P 500\n",
"<p>Let's also take a closer look at the value of the S&amp;P 500, our benchmark.</p>"
]
},
{
"metadata": {
"dc": {
"key": "25"
},
"tags": [
"sample_code"
],
"trusted": true,
"id": "yW7WPylBoEOg",
"outputId": "0a8040cc-571f-48f0-99ae-f736e0ed1f43"
},
"cell_type": "code",
"source": [
"# plot the benchmark_data\n",
"benchmark_data.plot()\n",
"plt.title('Stock Data')\n",
"\n",
"# summarize the benchmark_data\n",
"benchmark_data.describe()"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 62,
"data": {
"text/plain": " S&P 500\ncount 252.000000\nmean 2094.651310\nstd 101.427615\nmin 1829.080000\n25% 2047.060000\n50% 2104.105000\n75% 2169.075000\nmax 2271.720000",
"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>S&amp;P 500</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>count</th>\n <td>252.000000</td>\n </tr>\n <tr>\n <th>mean</th>\n <td>2094.651310</td>\n </tr>\n <tr>\n <th>std</th>\n <td>101.427615</td>\n </tr>\n <tr>\n <th>min</th>\n <td>1829.080000</td>\n </tr>\n <tr>\n <th>25%</th>\n <td>2047.060000</td>\n </tr>\n <tr>\n <th>50%</th>\n <td>2104.105000</td>\n </tr>\n <tr>\n <th>75%</th>\n <td>2169.075000</td>\n </tr>\n <tr>\n <th>max</th>\n <td>2271.720000</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"dc": {
"key": "32"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "q6acuK5_oEOg"
},
"cell_type": "markdown",
"source": [
"## 5. The inputs for the Sharpe Ratio: Starting with Daily Stock Returns\n",
"<p>The Sharpe Ratio uses the difference in returns between the two investment opportunities under consideration.</p>\n",
"<p>However, our data show the historical value of each investment, not the return. To calculate the return, we need to calculate the percentage change in value from one day to the next. We'll also take a look at the summary statistics because these will become our inputs as we calculate the Sharpe Ratio. Can you already guess the result?</p>"
]
},
{
"metadata": {
"dc": {
"key": "32"
},
"tags": [
"sample_code"
],
"trusted": true,
"id": "19Fl-RG8oEOh",
"outputId": "57e17445-841f-4ad5-951b-0c094a888702"
},
"cell_type": "code",
"source": [
"# calculate daily stock_data returns\n",
"stock_returns = stock_data.pct_change()\n",
"\n",
"# plot the daily returns\n",
"stock_returns.plot()\n",
"\n",
"# summarize the daily returns\n",
"stock_returns.describe()"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 64,
"data": {
"text/plain": " Amazon Facebook\ncount 251.000000 251.000000\nmean 0.000818 0.000626\nstd 0.018383 0.017840\nmin -0.076100 -0.058105\n25% -0.007211 -0.007220\n50% 0.000857 0.000879\n75% 0.009224 0.008108\nmax 0.095664 0.155214",
"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>Amazon</th>\n <th>Facebook</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>count</th>\n <td>251.000000</td>\n <td>251.000000</td>\n </tr>\n <tr>\n <th>mean</th>\n <td>0.000818</td>\n <td>0.000626</td>\n </tr>\n <tr>\n <th>std</th>\n <td>0.018383</td>\n <td>0.017840</td>\n </tr>\n <tr>\n <th>min</th>\n <td>-0.076100</td>\n <td>-0.058105</td>\n </tr>\n <tr>\n <th>25%</th>\n <td>-0.007211</td>\n <td>-0.007220</td>\n </tr>\n <tr>\n <th>50%</th>\n <td>0.000857</td>\n <td>0.000879</td>\n </tr>\n <tr>\n <th>75%</th>\n <td>0.009224</td>\n <td>0.008108</td>\n </tr>\n <tr>\n <th>max</th>\n <td>0.095664</td>\n <td>0.155214</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"dc": {
"key": "39"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "nzseGwADoEOh"
},
"cell_type": "markdown",
"source": [
"## 6. Daily S&P 500 returns\n",
"<p>For the S&amp;P 500, calculating daily returns works just the same way, we just need to make sure we select it as a <code>Series</code> using single brackets <code>[]</code> and not as a <code>DataFrame</code> to facilitate the calculations in the next step.</p>"
]
},
{
"metadata": {
"dc": {
"key": "39"
},
"tags": [
"sample_code"
],
"trusted": true,
"id": "Urgy5DO8oEOh",
"outputId": "6cad0024-eca2-4e27-ee78-3dbe3a8d4a70"
},
"cell_type": "code",
"source": [
"# calculate daily benchmark_data returns\n",
"sp_returns = benchmark_data['S&P 500'].pct_change()\n",
"\n",
"# plot the daily returns\n",
"sp_returns.plot()\n",
"\n",
"# summarize the daily returns\n",
"sp_returns.describe()\n"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 66,
"data": {
"text/plain": "count 251.000000\nmean 0.000458\nstd 0.008205\nmin -0.035920\n25% -0.002949\n50% 0.000205\n75% 0.004497\nmax 0.024760\nName: S&P 500, dtype: float64"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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AFzHGGOe8yDm/A26gWjagAU41ztXtmAAlMyhTS77choOIzdQv1HV/F4W6nAekxPDxNrr/6kuQgyrXbNgOj5g1KnUbr/nU3fjiXXsW5XMJYl2s0OfXrPgE8VJLfIJBSdece05OuqaNbOaGxjqKQYm6Q+/aXvuJO/EfP9sV2IaYZ1Jj0olERRGgFjuwVr10Q+0kbBnVjgC1BsB+6fcD3mvKbTjnFoBpAEOtfAhj7K2MsW2MsW3j4+MLONzm4A0YVMDFZzsiiFDgMDQNOUNPPCvinEMPXQW/UNfdh1+oy1GSWqUQfIkvGYNaLImPAlM4QHz4x9tx754JfOWX+xblcwmiaW7o89/2P9vwnu8+pnwPBYwlq4NS5qBcFp3xbgTVvUPndqg7g6mYXn2nIohN0sB6cKqMQ9PlwDZ5z5i0VCx4IaBrSzZz+bXFgiztqdj5csZJY5LgnH+Gc76Vc751ZGRksT8LgNokIQ9+VUuW+Lz6Fs2d0S1E4vMLdd3fZYmPBlIVg2pskvBvzMWS+Og4wvmCO3e6eanThrsW5XPDCJsk9h4v4XBoUCOIQt0lk/hUOSh3UpJpWKjrvjbSk8VUqXbSzYTnC1VLsbBURc/PSSHx1WxoDMh7rA/wGc5iQQ6AJ1seqh0B6iCAddLva73XlNswxgwAfQCW7QpkjXJQddsR+Z+6zQNLYgAegzK1FpbbUNnM1QzK5r4UZejRJHvDBQu9h7onZyyaxGeJXFjwOGhAWarZWzhQF2tWgyUsqFB3aZyNFHy0EINissTXgEENd2dRt/kpW8sWBp0Lt/0YV9bz0LO3VCx4IajUbeRMPWByWuwi2k4PUPcB2MwYO40xlgHwWgA3hra5EcAbvZ+vA3ArX8ZTQJGDUlxLy+YBt5Vw8UnSTc7UE9vMOefQQleBApTjLfshu/ioXseQ3kTkqPGKuu5G/QVz3gGKc47z3vuT2FxSXD0WPRSLPVMkhD+/VLVj2aW15BKfn0si8BCDUpokvPeNdGcBuNbqxUKpZmH/RGnR9t8KLMnFR+clfC1FgDoJGFTF8gKUdP2XUuI72YwSCw5QXk7pegA/AfAEgG9wzh9jjL2PMfYKb7PPARhijO0E8E4AworOGNsD4F8B/B5j7IDCAbjkaJyD4qIYV27BUrMkF5+hJ+8koXTxeQzK5ih5xgPalh5CU8WgGsR8ujH78ua8l9uoWg7mqhbee6M6n2PH5KBoxrtUszf58znnjRkUmSSW2sXHgi5M1yThM/O49430uAFqMZ18/3XnHvz6x25fFg1aqWjZkQxCEQa1xN1AFoJyzUHe1AMS7+JLfP7+TzYG1ZZefJzzHwL4Yei190g/VwC8Oua9G9txDO2EyKXEmCTcJTWqAVeMXN+SM7XECxbaPF7iszkPFB/aDpckvtZyUDRA9+VNHJqan2mymRTRLEAt9kwxfBwAxErEcRZ8Wj5lqeugZNYsclCNTBK2L/EBi1sLdWyuipmKhelyHQNdmUX7nCSoSy6+uABF56uRTDtdrkNjQE/OXKQjTYaKZSNrakEGtcgSX9AksfyDuIyTxiSxFHjs0DQ+edtOiUFFt7FsLhKcqk4Shk4MauHNYm3Hl/doWxpI5dltK4W6/fnMvCW+ZrJlfIAKnqOF4N9ufgoPH2i8+m2gMW7Nz98pt5VWSF6KljPqOig3B8UYg6kztUnCe99wz+IHKGL/x+aqi/YZSeFLfD5TCuc46b6aKcff19d/5QH87Q0nfsG+at1GzlhqBuUofz4ZkAYoCb/+sTvwLz95UqqDaibx+Svv+iYJrw6qBZt5LINyuGhz1OOtH0MMSs5T+IW6zRlUb37+OahmQVfYzMM5qDYxqLrt4N9u3oEfP9q4NUzAUu85FuMs+HKX8KWQiHym7T96bh7SveYZXWtokqAc1GJKfMT+x2dPfIBKJPF5r083sN8fm6th7zLIq5XrNvIZPZBDDj8Xu8fn8Omf7wq/FTc/fhT3751o+TPlANhxOahTETTAqi6lZTui7kIu1K0Kk4SGnKknl/gcRYBiUQbVVzDhcH8QlR/SRpKkOG5J4ivV7XnlF5rl1WxFWxrOedtyUNNN1sUSx8GjDKqZSQJYGiefvySI9Jo0STENraFJYrjbldwmSzVU6vai2M2JKY8vAwallvjCEyD3eGcq9dj72nacRTWWJEWl7iBnakEGFXquvverw/inH22PTAg/8IPHI0XKSVDrcBffKYdGLXPqts+gapa/0ifNenXWGoNyeHTBwgCD8nJQA4VMQOKTB1Z6JsMtYILH7f6tL2+C8/mxhWYMij5eZnK2w4VkulApg1hDs1mgau2reJu5f84qtcV/eC1pIkNwc1Duz6auKSU+ei1n6ujJGnj80AzOfveP8fX79ke2XShoIrIcGBRdH859phG+z2nQ5RyYjVEHLJsviwBVrtnIm3qgTCT8XNCzGX7exmerAck/KTrdZn7KwRIBKvo32+GeScKVroSLjwYenSFn6IG+eY3Am+SgaKmN/oLpSXxW4PPc42xeB2U7bp6jx6tgp4H7wGQJb/+f+xN1gm4eoJzIccjBRH5QLNvBx27ZgekWpCpiUM3W0AnmoOzIazICDKq++AzKl/j812SZN6NrSimUjt/QGfq7TNyz2y0j/FETuXM+oOu82E1Mk0BeeoQG8giDks7XjCTzTZfqwi5vORyzVeuED9CuSSKcgwoeE51/+fVyzUaxZs9rJQKZockmCc45Pv3zXcsi1xiHNEApQIOWSi6wHMevg5IWUgvmoJKvCaWS+AzJxUd9+PryJhwpB1VvMQdVtzlMTUOXtw4NDdzv/s6j+PFjRxJ1IZdZ4USxhl/799ux4+iseM1SME8KpBkjOPA+cnAa/3rTU7j5iaNNP5cwXa4FPicOwRyU1fA98utL0Y+Pgmu4jk0EKENTMkRyG+oaw0AhIyYuckeCdqGyjHJQ8n1erjW2mQMIMIzf+dwv8bx/vg2c++tJLWQ14h1HZ2M7kiRFte4gZwTroMLjhAhQUmChIDKvAGWrGdSvDkzjn360HX/xzV+1vM+lQhqgFKBBK65ZbEZnMDTm9eILOtTIZg4ka16pkvi0gEnCQkbXUMjosKU6KJXE15hBOTB0hq5MkEFtP+IGmOMJ5A/5QXrs0DQePzyDB/ZNSscRZXI0mPRkDdQs35ZPVveJFmQXwaCaMFOHxzMo2+F43Wfuwc+fGg8cHwBUFjFATRRrmKtaks083IvP/Tmja6KmToZNXew1Df0F3/pN+dB2Yjm5+ALXh+79GBef+7fgJAgAnjo6J16fWECA+uOvPogP/Wj7vN8PkElCa8igyoJB+feBCFAtSnzTpTr2HiuK3//77r24e5fLvildsJy7kqQBSgGR7I9ZbsPQNZi65uagQhIfFeoCyRiUymZuBGzmdfTkDOgac00SKgaVsFBX15joojxXtXBsrorD026gSNI5QP4+tHCiPMumoKkKULT+DZ2nQ1PuTPRYMfkgSDmoZgxK/ntRMCi/Vubu3cdFf0Db4WK5hsVkUG/8/L14//ceV3aScLjf0d40WEyhri/xDRT8Wp7cIjAoGhiXA4OSJ2I0cIdlOnmAl5+Li9b1AwDu3nVM7KeVCVEYsxULR2cWtvBCxbOZN3Lx0TNeCTAo97jjcmxx+IfvP4b/vONp8ftdu47jv+50fxeycXgAWkZIA5QCjZZQr9suE3HrVfyVPumh0TQm1vVJYgpQdZLwu5m7OajevAmNsYDEp8pBcR6/sJvlODB1DQUvUJRqFp464stz+443D1Cy5EAPqpynUDIoL4dAgZEeRupIPdFCnsNnUIoBXDofyjoox693AoAjXmC2bC6KNxezm8TTx4p4+nhRBEr5isvtrlQmiS/dsxdfvdftBG9oGvrzfoDSGPDdhw62tYZrMRnUE4dnWgoSNSWDUpsk3J/987Ci17Xk3737uAjwkwtYjbhq2Qt6P+dc9OILuvjUJgl5/DjuXYua5bRkNnrs4EzktYPe5JBKLIzwcgrLCMv3yE4gGpkkLIfD0Bgyhu6uqOs9G2KdJs9mDrgP+q3bjwpKrYLjBNveAH4jWCfEoJpJfPKxy/j4LTvw9fv2ewzKPba5qi32Ndydxb4kDEp6MMa8ABVgUIo6KBpgaHkBOk/EoJJIiwRiUKrBWGYd6jqo4ESCAlTdcdCbd4+tnNBmvmt8rqXO2aWa5TLW2aq0AJ98/RqbJP7uO49i17gr0xg6C0h8v9gxjj/92kP45dPt671MA+DxYq2t7Y4453jdZ+/Bf/xsZ+L3KCW+iM3cCbQfI9B2u8eL4vovpMC5WncWJBHSCtxuHVRrJgl5slBMuBqBZTt4WpL3CAcmy97f3XNipgzq5IKfgwo+CJRsNTQNGZ2hbkVdfIbumySqlo3f/8I2vO6z98R+lu11EZChSwxqtmKhJ2dAYyzg4lNJfIB68P4/Nz3lmSSYcCAWq5YIUGet7Mb+iVLTmhp5UB7zApNcK6PqJEHHGWFQXg6qlQBFDi2VO7LWhEFZIQZ1eMZ/SHs9BpWk3VG5ZuPX/v12fLmFta0oiI/PVgXTk880tToCyCQRn2MztKDER4E2rotCpW63XJhdqbsd+22HBwb0T962Ez99bP6uwclSHVOlOiZbcG7KwYiYXbhOrGY5voQsy32SeYjOaSOred12cP/eydi/Vy23lkp+TqbLdbz5C/eJCVcj0PFnjWAOynJ4QAGg7R7aP4UfPHwYQFCpSJqH2j9ZVtbUTZfrmK3UlWuTLTekAUoBO4ZB0SBn6gymN5CEZUBDY8gZyU0SjTpJONztJNGbM0WAon3GMYZGeShD18SDXKxaYkA+c0UPZqtW04GjopL4ZlsLUBEG1YKMNNWgUFcemORrEmZQxA6OTlfBubv6L1nvJ0t1PHE4KonIODxdRtVycGAyeVcCCuazVUu4sOSv4EiTlIyX21RB1xgYY4H+eHQfhIuMi1ULR6Yr+JsbHsHbv3R/4mMF3KC2pj8PIDgB+eJde/A9b8CcDyjPKdfgNWNo8gCrUg8A99rT/RVkUL7rj66/zIAe2j8VmHTd+NAhvOo/7sLYbDTPZDtuN3XL4QEn3S93H8ct28fw0P7G7bcAX8rLZ4J1UEDIUu5t9+mf78K7v+u2Z5Kvw2w1WYDfOTYX+7eDU37wMlOJb/mDK1hIOPhYoobFM0nYTuABowGkFZu5w6MzGLmbOTEoXYtPBnMOMcCp2uQQDI2hy5NCilVbHB8lk5v1uJO/Dz0w8oOjspmHTRJVy/3c48UaNDY/F19dMagFBibp73NhBiXNwieKNVi2O7gxBvz33Xvwso/f0dAcQKaSVoo+x2b8/R3y3i/fb7TcBhBfqAv4yWxZ4iOEnVgfu2UHXvfZe3BoqiycmklgeYPw2oECAODYrP89y3Ubcwnq5eKw3wvq5JY8NlfFRe/7KT4vJfHDULv4ojZzKp+oBQIUF//7OSj3+0yX6vjN/3sn/t8D/tJ1e4+7cphKQpMnDXIe6onDs4FjawQKPDlDB0ODAFWjzhiWmHgcn6uKZ5ys9FWrcSeRRgHqwERZfE44WC4npAHKg6o4MhKgHJpxMG+mywMzYQoscg5K7Cu2BYtC4gt1kujNmdA0pmQmdJxnr+wFANz0eHxdkaEzGLqGrKGhWPMlvuduGoaps4a5Mvo+VHdDD+lsxRIPp8+g/PdQ0rpHykHRIH/GSDdKNTtxJ3GqYVH11VPVhQF+HZTIQUnbHZmpuDlFXUPe1DFZqsN2eMA6H8Z8cmfj0oz8sPd+HmJQwmYeUwcF+AFKlvgIpZCMd3i6gvHZKip1B+Oz1cSJdap1WzdIDMo/dlcunL+RhHIfZPTZN1HCTMXC+77/uDCBhFFXMKi6zQMDc81yRPmEfO7IBCB/9wlPJZit1uFw9x4g0H2pur+C+/Cv/fYjLuNOopbQNjlTV3Rkt6Xt7MB7HIfj2FwNq/vcazJXcZn4pR+8BTf+6lDs5+0YmxVGkTAOTpXF+dxzrIiN7/pB4L6vWc6ycHGmAcqDapAMT05kizBJfLKkZooARRKfv8+pmEaWKomPLKg120GpZqMnZwaMFFlDC8gctsNxxeZhnL+mD/9+yw7sHlfPnKi9TnfW8CQ+9yEZKGRw8boB3OocSbgAACAASURBVL27SYCybBQyOnKmFpA5KIHrB6go06MBpGo5YpA/f00fAOB4Qqv5dJnyb40lvrhOEpzzgBPxyHTFXSFZYyLJDgAP7otnkpTzmSjWMF2uJ+qFNyY96DQIcikLJZskzCYSH+BerzDCDKpYdScOdA8enU52jmn7MIOybHep9VZtzjLCEh8x4tOHu/A3NzyCGx48EHmPKgcFBFlyzXLEBEhlkpAlRWJQNCGVC3fp2qiMRtUAg5ID1Kz39+QMKp/RsKovh+dtHsbrL1vvvr8eDcTy78fmqjhtuAuAWyLy+KEZTJfrDdnxrrE5bBrtjryuMbeDDJ3PXx1w68VufMgPdn/05ftxyQdvXpRej60gDVAeVBbjMIOiGZmueyYJaT0owB9ARB2UPOuKGYRVEh9Zjunh6c0bgSCWM/XAWlScu/b297x8C2YrdVz3qbuVkgPNwLsoQNVtZLyE7bPOGMKjB6cbdoQmiywFGwLNtFQMSuSgJAZFNtfzKEAlsJpzzkUnCfqcuaqFv/jmrzA2WwlKO4HuEP6Aajs8MJAcnq54dW0sUPD6YCMG5Q1ijx2awYX/8FN88/7ooAoAjx6cFgnusdmqWC1X5KCkc2Q7fh1UxmDKxLZ7Dtz/R3qyOH2kSzSOBaIMaq5qBfIlBxMk8cdmK6IZ6Uh3FllDExIuMav5dsIH3KQ94E8Gqc3VJ17/DDzrtCH8+Tcfxo8fDea4VDZzIBiIZJOE/Dr9LAc2kpQpIMgSM3WJUJUxyAGEjCOlmoU9niyYjEH5Ep+ha/ifN1+GyzcNu/sX/QR55NmdrViYKtWxYcidNMxWLTx+yA0qcSyHc45d40VsGunGNVtW4NKNg+JvG4e6cGCyHAmEchC++YmxyGsnAmmA8qCyGIcnUjQwmhoTM115tk7JRlUnibi+Zm6ro+BrxKDItNDjSXwEktnknI/OGC7ZOIhPvP4ZmCjWcIt3g8mgwbmQ0THn5aBoX885YwgOB+59Or6df7XuIGtqKGSDxaH03ehc7J0oCrnQN0n4zsbDnoPv/LVugBpLICWU67ZgTpT8/tX+KXzz/gP40j37Aqwq0ElCkqQshwfYydGZilfArAVaBj18YDrgqrrliaOi91241c1dO9Utoj5/59Ni5eHx2So2j3YHrrPMoDjnojdfI5MEtazJmTpu/bMX4CXnrfS/Z5hBefczWfOTtOh517cfwee8fFDW1DDcnRUmGAoqFPA45/juQwcT9XAkHIhhUCt6s/jPN27FhWv78CdffSjQn1GVg3Jf989f1Va7+MJMSNeYCC70LNDvnPMmDEqebLrveeronJg0JMlB0TZZ6V7LGkG1hazoMg5OuedNMKiKhcc9M09cgDoyU8Fc1cKm0W585g1b8Y23P1v8bc1AHgenypFjVuU+l6L9VyOkAcqD6kLEmSQMXRN24EY5KNVNrfoMFinUdf8XDCpnBCQ+kqNE5wYph/HcTcMY7cnihgf95G/4O3ZnDZRqluisDAAXr+9H1tAa5qGoCr5gBhlUWOL79M934y1fvA+Ow1HzjrE76+ZNap7EN9KTFQ/cwQSOOHn9IxpA6HO/8+DBQLGjqpME4J5reUZ4eLriFTAz5D1WyJg7gMrSyZu/uA2v/YxbKkASH2GoW63xz5T9BPfYbBWr+nIYlNx3YRdfEpNEOHAVJCZLn+V4eUuyIlNASWKDlvefM3WM9GR9BlUPBqjHDs3gT7/2EH70SDJXn+NwkYOiAEXXtC9voitr4K1XnIGa7QgzBaDuJOG+7jOOoIuPR7YhDHVlUKq5EzO6Dya8XKprSLCV7wNCEp/3XMqOzyRMg85hPhCgaKzw2J6ioz7VKK4dKEDXGOaqdRGg4iZ3ZJDYNNoT+dvagQIOTPoBisYOsfCjNOlYCGNuB9IA5UGdgwpJfFI7I9fFxwMJeWJQWclmTnElLqnOebRQlzHmzfZ8BiU7QSkAksznuvjcfegaw7UXrcbPnhyLBEX6jrLER9JW1tCxdWPjPFTFspGTGBQtP06zODKRFKsWijUbh2cqwlVIEl/VcnBouozV/XkMdWWQMzUxcDUCzbYZ8wctkgb3TZQCzC9gkqjZ4hpYksQ32pPFkekKbNutayt45/QCT3YkmS/8gB6aKgfyVSTdhTFbqaPsrbs1PlvBSE8WfVIHiKBJQpb4ggyqkQ1bHuiIKX7hrj143odvi+Q8D003b9EjH1/O1DHcnRXXVm4zVLMccb7nqjaOz1Xxydt2NszDjM1WUbPdtZDoPpwq19CdNUQngxFvtWDZGRov8fHA/75JwolsQxiRViMO56DkiYeKQcmfTUFt++EZdGcN9GSNhAyKGLB/z4S7zqiWwdk/UfaOP4PurIHJUh1PHXEDUByD2nGUAlQ0B7V2II+JYk2MSfR16b6TO8wUQ8pSqWbhPd99FLfvGG/0VduGjgtQR2cqOPNvf4SvhVxD6hxU8Hd5yYOMHq2DIrsmYwxZQ0O1bouHPq7ex5ba3MjQmS9H9OSMAMuSF0ykj5fzWL9x8VpYDscPHj4UGODo5u/K6pjzApTcy+3Zpw81bEVTqbuLNdJg0Jsz0Jc3BZOhj6IHfOfYXFTiq7s5qDX9OTDGsHagEJgxE3aOzeLHjx4RkwSabQ8WMiIQHi9WRXPeb9zvr4tEYxTnHMWahR5vdm3bvsS3cagLR2YqqHtNdCnobFndi5GerDBK7JCsusWqhZmKhS2resVrszES12zFAueuzf14sYaRnlwoQIVNEu7Ppq7BcvyJT73B0iJyoCQG9dPHj2C6XI+suJuEQfXJPf4MDSM9WXFt5QG4WLVE54rZSh3P+dCt+JefPBkwl/z8qXF85CdPit+pbmzzaA/K3kKL0+V64JyMegFErq2rBxhUNL9EASyf0aCxcLlB8NzR/ieLdcG4J7zC20OSBKqqs1OZJJ44MouzVvYgl9ETmSQEg8qoJD7H+47R/RCDGurKYqg7g7t2HkPNdrBxqIDjxaqS8e0cn0Nf3gzkKdcO5HH5pmGsHXDdgLtCNnT6DrJ6IEvkR2cqeM2n78Z/37236arW7ULHBSiNuUnosIyiYlDh2WtduPg0mDpzc1AKiQ9wZ6DBWVe8xBd28dG+ZAlEV+WgbC5chHJ+45xVPThrRQ9uePBgYIAjCaMrYwipIy/N5p59xhAAt/hQBZL4BOsiGSjEoAi7AgHKHYgoB7XKs8yuHcgrGdT7vv8E3v6l+/GhH7vdo4lBDXVnRAA8PlfDYFcGV29ZKWaZgO8irNTdAN7rDYIug3L/tn6ogCPTFVi227oq532n3ryJi9f1C8utPJukHMW5q+UApZZAqJjS7dDhDo6BACVtK9dBkQxIs9tGizPKAaro2fUf2Kt2IMoBinOOD3z/cbz5C/cFlkspyNKTqWOkO4OJYg22wwPPx1zVEgzqvj0T4pzK7rY3fv5efOI2v6XRfhGgukXR63QpGKAEI5dr62K6zdM9QBOOjO7XJvrvbc6gqpaDct0OMCiVxEqDd9bQMFlyg9r2wzM4e2UPsoaWyCQh10ERqA8kTXRU4xC5H4d7sjh/TR/2eH0zn3/mCDhXjy07x+awebQ7MLG946+uxJfecpkIULtDbZDoXpMnGjTxefzQDF75yTuxe7yInBmfJ203Oi5AmR7LCT/46hxU8Hd/LR8mcgXyTNiUqFDOdG9afx2aOJs5YgOUzKD0kIvP/Q4+g5NvRMYYXnnxGjywbwq7x6O9uLqyhsuganZgNnfB2n4UMnqszOe7+HTxHYe7M34OKnROd47PiRwUFVIenamiXLex2utUsM7Tw8OgJSd+tt2VEsjBN9SV9SW+Yg1DXRn8xsWrA++loE35EmplZEsBasNgQTjdDN2X+HpzJp6xYQB7jpcwUazhSW8A78kZwmhw5kpf148NUN7re73BJCzxRXvxuT9T/RHNmhsNBHk5B1W1cN+eCaUDUNeYMKYAbgL9P+94GrdsH8NXJCVBHphzpsugHO4yVXlm/+D+KSE/yw5MlYxNzwdNIDatcCWnSs3BdLmOfom15TM6urNGQLYKmCQsO/K6CFCG7qoaUrPYcKChADVRrAUY0USxJurTaJ/hdZfIxbeqL4fJUg2HpiuYqVg4Z1UvcmZSBuWbXAhDHsMRTFWxnwOTZeRMDV0ZXRTVZw0Nl53uTijHZqsYn63i+q88IAJdnMUc8EsIwvcW/b5t74QIYsWqjbt2HcOrP3UXOAe++fZnY7QnF+s0bTc6LkCR3h2e7auoNUdwwJWXPCCThCwHRBiUZQsWFtdtWuXio33RGNadNYIuvoycg4p+NgBce9FqMAZ8S2GD7srqKFbdpLCcxzB1DZdsHMRdMUaJinDxuQNjztAx0pPzbeahnJ3MoHo8BvW0Z8td058D4DKo6XI94gajgE4PQpBBeRLfXBXD3Vk8b/MIhiQDAl0nmv1RM1jLccTAtG6w4H9vqQ6qz2NQgJuHesoLUOWa7z687LQhPHfTEEydKSU+zrkIUNSsM8KgQiYJmmCs946LZs2N+vLJ165Us8USImGsHyxgtmqJc3xU6mxxyxNjIojIg3bO0AWjOTZbC6gBt3qLTDIWbL6q6q5B12//RAmjPVlRw1Wu25gKSXwAAozcfb9cB9UoQGmiNpFgOf5SKgAw2uPecy6DkmoUS3XBjgG3Oe957/1JgL3RuVnZl8NEsY7tnknhnFU9YjLaDMLFJx1TT9ZAxtBEoFetSXZ4uoyhriwYYyJAnb2yByv73O8zPlvF/Xsn8f2HD+PRgzMivxQXoEa6s8go2htVbQdjMxXsPV7C888cAeDKuZ/++W705k185x3Pxbmr+yJ50sVEWwIUY+wljLEnGWM7GWPvUvw9yxj7uvf3XzLGNkp/+2vv9ScZYy9ux/E0AtUCRRiUwq0iDyJzVUvcPKZiPSj39WAxbaVui0E7bplyh/PIgoWAH3C6Mm7NhNyNhGQ5y/ZXCg3vYnV/Hhev68dt26N2866sAYe7g354PaFnbhjAzrG5SG83wJU5cqYu2EZWMKigzZywa3xOmCTIWLHHG7B9ic8dkA+GWBTJFjWRzK7D0Bh686b4nOPFGoa6MzB1DS+/0GdRNCkg/TzIoGxkDbdQkqBLLr6+vInz1/ZB1xge3DclGJDlcFHzsm4wjy+/5Vl4wVmjSgZVrtviGOn7jvbmGjAo//rR+UjCoIISn4U7dx3DxqFCZDtyS1KAJTnrdZeux76JknB8BQKUJ98CruQmT+B+9tQ4VvbmMNqTDfRvJAYl3wckWe2fLGHdYEEE1VLNre3pD3XFGOkOBii5dVclkIPyJD5vCfOM4cvuBMvmAYWA2MpEsRaoa5oo1nB4uiLOp+idKF1bCmir+vKYKtWEg+/MFT3IGnpCk4R778nPO2MMw13+M0TnWX6eHe7Ke4CbI80aGras7sOIZFKi53W6XBPX84yYAKVpDKv7c5HXa5aDbV6z3BecNQrAvU5js1Wcu7pPBMRGpRDtxoIDFGNMB/BJAC8FsAXA6xhjW0KbvRnAJOd8E4CPAviw994tAF4L4FwALwHwf739LRrIaRfWp1WdHuRB5JWfvBP/dssOAG7wyBjUi8/fPpqD8v8ex6AaSXyAnz9R1UHJEp9qH4NdGWXlP1lyx+eqkSXDadYVlga/8st9mPAktSCDygq5MPwdj83VMD5Xhcbc857RNTFgk8Q30OV+P1kC5dzvoi0zqL68CVPzF/Q7PlfDUJf7kP7RC87AX73kbHRnDWGS8BkU5b8cVGpucTIFSMCVZuk89OZNFDIGzlnVg3v3TODgVFl0Kdg5Nofh7qywBvfkDGWAkl+jADfcnRHHEYbcTSRn6ljR6y9/0pBBeQPqQMHETLmOxw7N4GUXrI5sd7oXoA5NlXHr9qO4f6+bP3r9pW4XA78o0x9kSeIDgP/42U589V7fhDJVquPS0wbdgnGJwdA1kwMMDbj7J8pYN5AXE6JSzXYbIasYVKC/o7rDArGbaigHFXDxOU7E0t2XNzEZkvgmSzUcni5j3UAwuE+WauL7yQzKcjju2zOJdYN59ORM5MzoEikqVEKmJMJQd1Z0U6HvGGGWXnDNGjq+/JbL8L+v2iyuz9hsRaQoJkt1EaA2xwQowK2FCqNq2bhvzwRypiYKe4s1G+OzVfFZAMTYtxRoB4O6FMBOzvluznkNwNcAXBva5loAX/R+/haAFzFX07gWwNc451XO+dMAdnr7WzS4DV2jjGZKsc6LPN7umyiJWb6pWLAQCC78lTNcXZoYVMsSnzdg0eAY6CSRkQMUIn8nmLqmTLpS/UzNciJLhp8x4t7Uu7x2SZW6jXd9+2H8zQ2P4PLNI3jL5aeHclCeDDRXVdpztx+eDdjvi16AIEmOHIG7xufwiVt3wLKdwNLogkGV6+grmDB0zevqbmOuaolZ8WhvDn/4gjPcdbPI7l4LPuzXfPQX+OLde5E1dIxKPcpkFx9te/G6Ady3ZwK2w4Vrb+fYXIB59WQNpcQnv7bneBH9BVMMjoQog/Kv3/rBgiTxxZsk6Nyt6M3B4e5k54VnjwSYFQCc7l3Tg1Nl/P4XtuGztz8NQ2M4d3UvzlvTi5s9yS5cB0XX9p7dE5EC7ktPGwwk+9f25wXrlbtWlGs26rbjBoDBgji2yVINNdtBfz7Ytmm4OxMr8dUsR8hj1I/vP293C4tX9+cCA6fb2iromDN0hsGuDCZK9UiN4uHpisj/Ed5742N4+cfvCLTIout/165jOMfrf5mLYVBuCUjQRRueEAIus6McFD2v4XZWw1K93daNgxjtzSFn6ujNuTm7sghQNRyZLkNjEL37VFjbH2XalZqNbXsmcdG6fs857N7LE8VogFqqDhPtCFBrAOyXfj/gvabchnNuAZgGMJTwvQAAxthbGWPbGGPbxscX5sE3tWhDTpUTRl4tt2Y5Ykburgelw3Z4oLO2vAhZNmSSCA/ee48X8frP3oMjMxXleiz0Grl8VC6+ulSHpQpyGUMTx/yyC1bh5ndeAcC3fMv7ImwYKkBjwK7xIg5Pl/Fbn74bX7tvP65/4Sb81+9dgr6CKQYZWQYam60GgjAlWZ84PCP07rM8c8GqvpxghNQB4IYHD+IjP30KP3jksLgWg10Zv3jQY1CG5raYIjlJzj3RefrOQ4fwJ199UNQwkcRHyBruopLkmDM0v9URBZFnbOgXEu8Wz7W3d6IUDFA5E3NVK1IvNyMxqLHZqrA3y13Iozko//d1gQAVPxBsWd2Lv3jxWfj181cBcJnxBWv7I4Pb+sECDI2JfBrg5sQ0jeFFZ6/AA/smcXyuiqrl4JxVvfj+H1/ummGywYJsGc86fTBQz7NaClBy14pSzXXIOdw1xNB5psleuPHtSE820IC4bjmBWjO5pdEjB6dxw4MH8SdXbsIFa/tF6Yd83uT7m9bSIgZleJPVvcdLKNVsIa8S7tszgSePzmL3saI4npW9OW//HGd7E5ewY5fw0ZuewnWfulv8Xqk7gXNGGO7OihwUycgDoft6qDvaf5HO1/hcVdQrTXvrbfXlTWXqgLBWwaAmSjU8fngGl2wchKYxFEwd+yfKcDgCASrr5aB+8PDhRVl1WcZJY5LgnH+Gc76Vc751ZGRkQfsydBapHVCthUQDDw10RKN1jcE03IsvdzAIMChTj/SBk/f7W5++R5gRwp0k6DMAf8CUXXxKiU9xM5q6JhjWVeesEFXlcgeCsOSQM3WsGyxg1/gcPvCDJ7BjbA6f+p1n4s9ffJY4Jnp/ztSFDn5sLhigThvuQsbQMFu1YHoDDNnYZSZB7j7Ki/zHz3aJ4DPakxUz4qlSHf15E4a3kB61wwnnMHSNYbpcx02PHxXXjVgogWbhK7zBxtA1vOCsEfzeczZinffgXrxuQGx/7mq3eNd2uJAmab8Oj7YZCst+9HC3wqAOz1RQteyGUoquMbzjhZsEG7zstEGYuiZkU0I+o2NFbw4Pe01BAX8AvOqcFeAcuO3JcVTrDvrzpuiRGAYd4mBXBmeMdIuWPRpzzyUFKJI1AZeBU7BdO5gX9y7JUGGpiYIE1U1ZjhMwFdD9Yjl+sfBvP2sDAOrCEZwQygFK1zwG5eWg8hkd/XkTjx+a8T47eCyU87pjxzFULQcaCw7UF0uOurBJgnOObz9wMGDjj5f4Mjg+V8P2IzP47C+exq+dv1LkewjDMR1LRntyGJsJMqjJUk3ZUFiGSuKjCfVWT97ryhoiYI5In5/RNRwvVvGOrzyA3//CfQ0/Z6FoR4A6CGCd9Pta7zXlNowxA0AfgOMJ39t2GBqLMJqpUk1IVwRSAclySrSW8inya0Bw6eTw0t3y4H1wqhxo86+a6BAb6835LXgI+RYkPrE/yWUhz4zDEh/gyny7xuYwNlPBhWv7Az3f3PfLJgl1gMoamsh9kHnkWZ4tVq7JoWOhReK2H5nFDd4aPav6crAd1whCOShd0wJNUMOzfArkFctfSTac56AZObEhQ3MLhv/+FeeKScaGoQIGuzLIGpowGQAIDBzhGhZC+Hdyj8W6+EIy7/rBAjh3WUaj9b0INGF4rtd4NDw45UwNq/tzgdY85Io8b00vVvRmccsTR10DiWKGLx9z3tRx6cbBwLpneVPHkFczddfOY/j4rTvEe8p1W9RAyQzqKS9AhVkLNUTdc8yXOOVBndps1W2O+/e6eSCaaJheA2fAL3mQ729T19BfyAgXX9bQMVDIiPMiOztl3L7jmNhebld18XovQJl6RPLaMTaHg1PlQPlKuDCeMNzlTsTe8eUH0Js38P5rzxNBmcaBuABFDErOQanMJ2GEzztBY8AzvO/VlTVEznikx//eGUMTk7BGa061A+0IUPcB2MwYO40xloFrergxtM2NAN7o/XwdgFu5S09uBPBaz+V3GoDNAO5twzE1hFutH2VQ4b5qNMsN10QYOhODv0ztZRlO14KOInnwDtdchVsdAT4josE1bMAAEMiBqQJURgpKhlSj1S0HKMUDs3Ygj8PTFRSrtghGMsjxljN0IT2Mz1YDNnND00Q+i87VM9a7rOSac/2AJ6/j018wsbovJ2pzKBjULAdTpRr6CxkxCaABNhKgvL9z7htfwglnmvnT/lULtjHGcNlpgzhzRU+AgQUlPvf1MGMK/z6qYFBhiU++vmQ13zdREgzq7JU9ePfLwt4jF5tGuzFQMHHVOSsA+AGKbomcqWN1fz4wiJKkxBjDlWevwC+eGsdsxQqwFQD4/eeeFvj9H649F9dfucndr7dtPmNgoJBB1XLwpi/chw2DXfjv33dTyaWajf0TZegaw6q+nM+gPGYRdpNtHHInAzRzl/NO7mf5k7P79kzikg1+l255qRIqUM8pGNRkqeaWTBgaBiQjUdgkQbhn93HMVd3gLUtvJNnmTC2gpADArZ57Vm5QXI2T+LzBf9d4Ef/0mxdgqDsrjpuerziJb7Qni7GZsMTXnEGpJD4AOHtlr5h4FTK6kKtHuv3rlDU0zHjP1mLnohYcoLyc0vUAfgLgCQDf4Jw/xhh7H2PsFd5mnwMwxBjbCeCdAN7lvfcxAN8A8DiAHwN4B+d80dvnuhJfUHKbKtUiNwHFlHA/NirUBYIBKsBYQgFKZmzhvIJS4mPEoBrloGQXX/R7ho+HIH9PVYCi9aKKNUuZh+iSclCmrmGgYGJsthoYdA2dCZsrsc18Rsd9f3sV/v7l5/rf02tVBAD9eRN/cMXpIpjTzLhStzFbtdCbN6F7wYRMLd0xAQpw84p6aK0nAMh6x0P5BEPVawrAh37zAnzu97YGzkFY4gPiGRRdVpXEF1wPKngPrJNqoehe+dCrLsCbLw8GC8I5q3rx4HuuwXqPfQx2ZaAx/97JmXrAtbi6L4eP/taF4vcrNg+jWLOx+1hROBQJ73n5FhFsAOA1W9cJCVAwqIxvetkwVMCX/+AyISG9+zuPio4StDAk4PYGXNGbjXxef8FEb86Q7P3BAEXXctdYEcfmqnjmRl+KpdpEwHfpRnNQGVTqDqbLNTfgeAO5xqLBEgAuXNvndc44jpyhi7ZZstpCNY8y5PIOkt8qltokQezoVc9Yi6u3uJMM+s7kUh1pwKDKdVsYSyZLNUwWa8pVl2Ws7M3hbc8/Hc/cMBB4/RLpfMrL6gyHGBQNZ3Hmr3ahLTkozvkPOedncs7P4Jx/0HvtPZzzG72fK5zzV3PON3HOL+Wc75be+0HvfWdxzn/UjuNpBiNkkijW3KUcwgl3ykGFrdrUzRwIziCSMqiwQUPFfuiGpyJTeZtCUonPUEt8w91ZnLfGTfCqchxdWQOWwzFRrAXyVf7nUw7Kb/J5NNSM1NQ1nDHSJX4mjPRkIw1WKch05wz81iXrMFAwYepMXI/jxRo4dwMYdetoxqAAlyUUMnogOAN+4CAGZSoYFOD2phvtyaFbOgcU1AA/QMmmiKeOzuIff+i2Z6LBjwKUPHuWn2vOgxIfrcW0b6IkViSOO0YVrnvmWvz1S88Rg2He1EVhNAD8/C9fiJect0r8PhxKgIcRJy/R98mbOi7fPIzfvmw9vvIHz8Jwd1Z8NtUUkUwsS24qmYkxhg1DXYJB1W0eCGK037t3u0XJl2wMMii/iazKJKFh0MvPHZ6ueBKf+/tIT1Ypv738Qrfgfdd4EVlTA2MM//WmS3DTO58vtsl6qyD/7ud+iamSu5Dltr2T4rqX6n4OW/UZl542iL/5tbPx96/wGfKa/jzWDuTFs9FI4gP8urlJzyShWnVZhqYx/PVLz8HZK4PdzrdK55PUk+6sERgH4hokLwZOGpNEO2HoLCDxTUquMRlxDMpdD8rLdQRMEizwc9VWB6iwQUNR1B0pMpUHXqLgc1XLd/HFmCTE8YRYwkdefSEGuzKRGZS7f1+66lZIfCIHZfhdzeWcmvt5TNRUkaEkDnTz04PwVy85Gy89b5V4ECg/1eeZJAA/QHVnGgSoYhVdGSMi4ZVDjqw4BhX+tUcrRwAAIABJREFUvowFc1AUHOXq/+95S3A/c8OAeB/loBhj+MGfXI7z1/QpmsX6x6hpDOsGC9gnMShV4IjDeWv68AdXnC4CiJuDchlNf8EM3BdA0ESiykHJs2cZcg5qdX8eH/yN88VAKrPWa7aswEdfc5H4HsSo42SmDUMFvw7McgLHRAHugb1T6M0Z2DTi1/rIOShhkgjZzGnScGS6gqyhiWd+VV9e6aY9Y7RbdLina/DCs0YDTJrOw+07juHnT43j9h3jsB2Ol3pBmST98dmqMtBkDR1vveIM8VwDwJueexpufufzkc/o0DUWkakJdG9Ru7BjXlF12AUYB7oXVvfl8LvP2oAXnj0q/kbP5YZQ8XdGX9RS1QA6M0BpQYlPdMruislBhXIKusbEQybPhI2EDCrMWlTsJ5zgl5+d1f05ZHR3ht1I4svGMCjA1ZofePfVOEfqzE2QZTMVg1o/WMCfX3OmkCNGvKUrZBi6htOHgzmoONBATw1lX3vpenzsdReLAEXyRX/BFOfYZ1DBh0XO500Ua+jK6mKpewINGBev78fLLliFCz03VhwMXUPW0DDSnQ18F5qdywWkxaqN7qyBb//hc4REIju/zl3dh4GuTGg9qOg94NZClcWA2+wcqkADZ87wJb6wSgAgMDCqBp/BGLlI7F/BCoL95nzWzBjDmy7fKI5LhbUDBWFDr9lqia9mO9jq2aEJcrNYmgSqclCAy8opBwW4ucUw0wZcA8Plm13zSViOFN9VOr5teyZx6/Yx9BdMPMdzrZa8xUGny/WIOy8OrvSto5DRMdSVibWM070VltqamSQIwoTRk8X7X3le4Nnf5hV0h/OQKYNaZIQrzie8fMZwJAcVZ5LQlAOG0YCxyIwt3MVClYOiQY8YlDyAZQwN6wbz2Hus1MTFJ5skkktEsmymMkkwxnD9lX4l+3B3NtIo1PSWUV/Tn28eoKiTeMgOTu+jAOUyKPe1qVIdOVMLnHMgyCTdAGVETCglYT838YnXPyMQQOLQnTUCBglAHaBKNUsMovS/XBQMAAzBbubhOijAL9atWQsLUBndba2zxpvxq2bw8qCkYlDhcyz2L0wS0Xska2jiO4XlpndefSbe8OwNeMNzNij3mzX8JUcsJ+jikyW7rRuD7D9YBxXNQZla0OSQNXURfFf25cQ6bDKGezK4fNOIOC7l8Uqfce/TE/j5k+N4/pkjIvCXapaYwK3oTRagCK+8eA3+4Hmnx/497t5tZpIg0LVV3V9/fOVmrB8s4NqLgt1JljJAxVfincJwJT6ZQXlFn93hHJT7fzhAmV6z2Mh+QwxKhjzBCZskGo09lIOS92doGjZ6Or2dVOJrYYDrCQSo5reI6iGhAP2qZ6xpekN3STkoGRk9yqB0iUGFDRLu5wYD1KbR7si1UK391Qx9BTOSM6GOHnK3jmLNFt+nkDGQM7XA+QRctitLfKp2V+u8Bq/03ecToPKmLgJOb95AIaM3D1ANrlXYgUYDc9iEAriTGPqK4cEya+h437XnxX6O6JfpuHU5QReff6xbJQcfEHTx0YQwn/Hfq+sMPTkpQBmaYBrUdcHtROJfm8GuDAa7MoFzGYZ8Xqj7/ZVnj4rAXarbQgJf2WKAevG5Kxv+vT9viq42F67tw6+8WrekDIomsaoc5+88awN+51nRSUT4HqnbzrzuzyTozAClBRmUn4NSS3zhHJQuufjC+/V/Dl5wmUElMUkQBIOSA5TuJpLv3n18Xi6+ZggwKIXEF4Zq0KMb/p3XnJXg8/xkrAw/B+UO0r3ewwi4FnJV8JTPk8OhzEGpllZphn99zUXoD+UBaHYu5yFLVZ9BdWV1jPbkIgxZHrzd44y2uyKr+U6v5ZSq+3Qz5ExNsA/GGN52xRk4Z1V0CXBdY6I2ME7GuuevXxSZaDSS+GQkzYcQ6BqSAUllksjoGi5YGywozhiySYJyUP49Qs2GNebeG1lDE5NSYZjRGEgL2LKqV3z2W553WqwzjrY5Y6QLhqbh8HQZzz9zRASlstd30P2c5my9FWgaw3B3FoenK7h4/YAIUIkZlDdmZWKuuwrhe3GmHC3RaRc6MkCZIZv5pLRaqwwnjkFpGjKKxL88EMqzdo0F10pKYjMn+DmooFy3YaiAUs3GmLd0groOKj4H1Qgyk0nCoJRMpoXPoyAYYVChHBQV6gLuQ6EKnuFA3JU1IgxqPp2YL1LkqUxdg6GxYA6qZonj+sMXbFIuQeEOkPEmCcAPUNQTsZnRRIV8Rg/M7v/0qs2x27q1gXYsg1LlTmQXXyM0c5SFQdeLAn8uYJJwfz5vTW8kMJq6JgqbLaWLz5Xw1gzksX+ijKyh46J1A3j3y7aIfCp99tVbVuCzb9gq3vtnDSZalMO+eP0A/uW6C2B7a4zNlH33Hq2o3arElwSjPW6A6srqeN7mYdy+41hs3VQYdF9lWnhewxOV6TRAtReGFizUnSrV0JszIoOAn4PyByCNubMWNYNS53wynqZOiEh8DRmUEdlG9wIUAOw+Nucdl8pmri7UbYbuAINqPrNS5SBa+TwKgj2KnnmAG6Dypo6soYtC3alSDSOjCjbAwgEqajP/s6vPTHxszZA3dZRrUsftmi1m2qqg5iLEoJzoJIUal1JX+flIKK9+5jo8+4zhRNtmDA3leuNOEmGQyaFZgGpWkxMGXa9KLcqgTN2tubp8c7TdmWkw3yShaHVE9+RZK3rcAGVq0DUWqC8zRU4m+YBNweA5ZwyBMSYmZ7TETLlm4chMBV0ZPXKPtwMksRcyBj7zu1uxbe+EcPc1A5VttHJ/qQLUYqEzA5TOUK4HGdRAVyYyyId78QEyJW6cTJadYxldC8yYwyaJRuob7VMe700vBwX4A5iyWawenD0mRcDFl4BBqXIQrTzgJPGFczV0/ONzVb8noZSDUhk4wnGxkAkyqJvfeYXoSdgO5DJ6iEHZWDPQeMAOM6hwHRTgHjettcVYa9ePIFuGm4Hu51akRL9Qt70Mip7DirTMOsHQNfzoT5+HPsU+lc1iQzkowF3D6eYnxmIXCgVaG7Cv2bIC37v+cpwfkhzpuSjWbBydqWBFQgdfq6AAlTd15DM6nqcI3nEw9Na/b/geWcwA1bEuvkAdlNdGJ3zDColPspk3uqABBqXLDEoPMKiIzTzB4EPMgHkMbs2AW7dBK7Y2dfG1EDAKGV04sFR1UGGoZtCtmDLkOigZNGhOFGsi6Uvn3eFq+TEs53Vl9ACba3cNRz7UydrNQTUO6uFLZSskPsDvKGHqWkMZuB2gQSfbhA3J8OusmgWo1hhUWOKTWZ2pMYz25pS5MmqObDtcTAJzZnSSRl31D01VIvugbVpRABhjkeAE+AyzVLNxeLrSskEiKUY8tqSaKDYDPaetOPOWkkF1ZIBS1UENFMzIIKCymdMNrJppGjG27ozOAjkoK1R8qRqcwvKQmNlJlHxNf14EKFWRYaCTRIsPHBXANhts3W1UEl/rjC2cg5IDrKonoSr3FV64OJyDakXCSgJX4gu5+JoMFBpj0W7misOiPNR8DBKtgu7FVgqCcw1cfDLiFmqMgx+gvFqmkMQXB/pb3XZ8F58iQG32GDR1q5DhD9gLnxBoGvPuDwv7J0rierYbQuJLoHaEYc6DMYYD1Ewq8bUXLoOSJb4aNo92R/IXKpt5o7qBOJt51tQDy3nUpU7L1MY/jP/3h88JDGIUPOX9bhgq4M6dx7y/R/cxX5ME4AaL2aq6F18YKomnlRueBrg4BgVAOOjiurITwk2AC+EA1eYajrDEV6pZTQcKxoLNYnkMg1ovGNTisifAP9etBahkJgnV5CnJ9ioG1eg+pvNUs53AMxbe7+leC67fvixqoZ4Pg2qEQkbH+GwVx+Zqoldiu0HNiAstsF+CCMjzMEkMd2fwi798YdPrvxB0ZIAKrwdFzRWT5aDi6wbibOYZXQt0+hadlg0dQF05OGkag4ZowJP3u3GoC7fvcANUs+U2zBYfOBr8k5gkaAkEGa0ExEtPG8SLzh4V3c8JcoCiHJR8jtUBKpjf6/JaxRDibNTzRd7URICqWe7A2GygYCoG1UTiW2z4qx4nPz+0bVwO6k3P3Yi7dh5v+VjEkikUoBIyKLpf6pbPoOi97kra7n5zpo49H/p19WfPg1E0QiGrY/sRtzaK8sbtxpZVvRjuzojmzK3AnEcOipotu50uFjeEdGaAkprF1iwHxZrtSXzB7Wism61aok7EbKDZBmzmcnAwgsV/dSs4u2slByV/htwjSynxBY6nRQaVNZA1op0aVFAyqBYC4oahLnzu9y6JvJ6V8kWUg5K/vyo/FjagFDJGxFHZTuRNXXTRIKmvKYNCtJOE6hZYv4QBis5LK2xn02g3rnvmWrHOVxjvlbrWtwLBoKygFA40lo7pPJXrtni+Da9vZqNaQxm+QtIe1lowDRGgFkviWzdYwLa/u3pe76UJnzmPHFSz3GM70JE5KFNqFktdJPoV/a4czsVy71Rs2GiG1ZBBOVwwMstxwJj/ECQZE2jXsjtwgzQjU0p8CR9sFbqzRiJ5L/w5hPnU7TTar8+g/P2qLLthBtUdkvhalZuaIZ/xc1C0Jk+SHFR4wUKVCULkoJagtUxGyt8kRc7U8ZFXX9j22p5oHZTEoBqcCzI/3L93UkxU3Fo1LfH9b7SZQcmTt3DT1eUAmvC1kuek+3ExpT1CRwYoXTJJUG5ooGBGclAO9+W9gdAMvpUcFF1QGjtrXmsQCjZJZne0jTyz2yjd8E0LdecRoObjCvI/b+G3ViBAeU4web+jihZL4U7xBUUdVDuRM/0cVMkLUMlyUI1bHQFuUWdG15YkB0VLbiz+JzUHPTvVetRm3oiZX7S2H8PdWdz0+FExAdU1ty4p6cSEnu9Wc7ZxoGdoqCuzKDVQCwXdW/Nx8akWX2w3OlLik5vFTnoMakBhM+fcX1qcrLL0gOheVbos3cW6+Dwd3HIc6JoOy+YwvfYyQEKJT4uaJNYNFkTCXS3xaZH3J8VvP2t9YGn2VtGOQVU+x30Kk4Rq5h7NQUU7SbQTss2clkhJ5uLzf4+T+KjrwVIwqA9cex7OXtkTK9ctJcIuvqQmCU1juOqcUfzg4cNiUUVTZy2xg3YzKOoysWV1dNWA5QAh8bVikpByUIuNjgxQlE8CfIlvoJBR2swpQA2GJD7AvVBlJ37Jd38792cKZnXbgWloIjAlkvhY9MHJmTpW9eZwaLqi7sXnDWyGlCBOilaK/WTQuW2XC4rOcb9C4gt3FwcULr6Mvqg1RLLNnHr8NStcdXNQYZu5+hjPW9Mnuq8vJvoKJt7xwk2L/jlJoDU0STS+lledswJfu2+/cLcaugZDD0qqjeBL+O25Z645dwXqtoOPvPrC5hufAMyrUFc4PtMAtSgwdC0q8XWZkZl2QOLzApR845o6g1wCELdAYFYwKL+RpayLJ5H4VAwKcPNQh6YrykHYbLNckQQZQ4NVs9v2mXSOVS6+8AKTQLDnIZCsl+BCkPds5pxzIfE1a7DLGAvUa6mW2yD8y3UXJB5cTxWIVkeKThLNBtLnbhpGztRw967jYl+GpgUk1UbwWx21Z4L1v646E//rqva11mo3MvP4viIHtYAUQFJ0ZA7K1JmwejeS+BzOxXLvfg5K6koQkl6a5qAkBpXRfYmvUS8+Au0unE+hxKtqH+LmaxObSQL6ru16wEkeVbn4VEG57p1japukaofUTuRMHQ5384pFj0E1+8zwYcfloGj/SzEQLCdEJD5ppt6MmVOrH5oMml4OL2lnE1HOsQTOyeWA+XSSIHdtbgmk5864CiG4MypXcpss1sSyBOEBjwdMElGJjwZhUdwXk4MiJkMPjeVJfLSvJAqUprCZA76TT2mSIOvwUjKo0DlZKGj2rHLxqUAyam/eXX13sbswiCU3ao6Q4prVhoR78cXloDoVmghQ0W7mSaS3q89xO5MzRiaJ1l18rRSunsxo1BknDqnNfJFhiIDhuI1iveATYVAOF334hEki0GMvyBbk2Z2u2M4OSHwsVrZTwd82eMnO9qy1PbnooKg6rsUGfdd2zUAz3sqs5IBqtl8yv/TlzUXPPwGQFqWzcMfOY9BY89Y+LNzNPKaTRKfCaMSgEtxXV54z6pZxaP5kKbGLT1v6Z+ZEgpSJVtbsWkoXX2dchRAEo7E5prxGsYB6FVzh4uuK5kBEAKBcj/T+YB2U+4BRgCKb+XxyUGboGF9w1gh+9KfPw8bhaJW637Zl8Qc/YVdtc6FjRndXpA0H87ivROd4qDuj7HjdbhCD+tgtO/D9hw/jf111prJHoAxN8xkU5xwOb7wmWKch0s1cdvEluJeHu7N4xvqBgAEgscRH71nCZc1PJNYOFHDT/74CV2xOtiwL4D6Dm0e7RU/DxURnmiS8IGPZ3GNQ0UUBgaCLr1/U4UQlPiFrxdi6wwzKEnVQrUt84SDKGMM5q9QWVsZciWspTBKudd/2GVS7XHyGFlhPiGZtf/Ii9eJ7ZH75ixefFbGcLwZI5vjqvfvx6+evwh9fmcQJx4SHj5hUKvH5CNdBZRrkfePw9uefITn5kp9cM2YieCpj84rWA81N73z+IhxJFAsKUIyxQQBfB7ARwB4Ar+GcTyq2eyOAv/N+/QDn/Ive6x8E8AYAA5zz1htJzRM0u687DiZLNTHAR5PXHKWajbypi47KgWU0Qi45VX5K3k528Zl6axKfMEm0GGxMyYyxmMgaGko1f0XWtjEoQxP5J/dzdDz9T78Wuz2ZXzaNdi96nzDAl/jOXd2Lj7z6wkRMSGN+oS4xqSRGmU5B2CQxn44oV29ZIVbJNTUNnCfrkKGLuqDOYFDLHQu9Cu8CcAvnfDOAW7zfA/CC2HsBXAbgUgDvZYwNeH/+nvfakoKYjivxNWJQ7mq63TlDtN+XWVI4xxPofSc3KDVJ4vMXUzO8FiwAEtmI/WaxrV0yM2E/vYVCLHjX5hzUC88awTXeQENgLL6ui87lUixRAQAXru3Day9Zh8++YWtit53czZxIXpJi7U5BuNVRwHw0j+u6si+XeC0mleEpxYnDQqeY1wJ4gffzFwH8DMBfhbZ5MYCbOOcTAMAYuwnASwB8lXN+j/faAg+jNdBNWLcdTJVqvkMvRuLrzhoRxx4gmySiTCjciw8AqAtP3XYCK73aCaQoTQSo1s5VpgUH00JA54KuZbs+8/or1VJeHN5/7bn4yE+figxk3/7DZ2OoK9oaaaHoL2TwoVdd0NJ75PWg6P+UQPnQQzkoM5D3bf1E/fN1ya/PfHrTpVg8LDRAreCcH/Z+PgJghWKbNQD2S78f8F47YaBgc7xYg8P9/JKqm3kxEqCiDEpV3BeU+3zXoPs/hyFJb0kClKqbeRKYS5SDyghW6ojPPRH43WdvxO8+e2Pk9WduGFz6g4kBAxQ5qDRCEWSJz9BYgF3O575qxQ7tM6g0QC0HNL0KjLGbGWOPKv5dK2/HXVF90bLSjLG3Msa2Mca2jY+PL2hfNGCPz1YB+EW4rnTkb8e5azPvyupSEIo+LHQzBxmUnNgNufisoEkiEYMSzKS1BydjaEtimf3n6y7EZacN4nRvTadUIomH20kiyKBShc8HPRdlRUeSxVYD9Hn0pkuxeGg6cnHOr+Kcn6f4910ARxljqwDA+39MsYuDANZJv6/1XmsJnPPPcM63cs63jozMr08cgW5yP0D5LjFZ5vMlPlMwhKA7L1jUJ0sRKhefKNR1giaJJG4zf7mN5WmSeOaGAXz9bc8WLrul7F5xsoExfybnB6h0QCQQeal6EzkZi50OmM8CfikWDwu9CjcCeKP38xsBfFexzU8AXMMYG/DMEdd4r50wEKOYKLoBqjfvK51aIEDBC1C6soUPBa1VfXnkzKDbTNVJQm51FGRQzR1Gy13iI8z3ODsJ8npQNDdJ66B8EIup1u0lzwW1e0XdFAvDQq/ChwBczRjbAeAq73cwxrYyxv4TADxzxPsB3Of9e59kmPhnxtgBAAXG2AHG2N8v8HgSgQZP6j4tV6rL44TDuZuDyhl+41WFHn7lOaO492+vChSGBpcZDzGoULPYJAxKteR7EvTkjKaFo+0EDS5pgIoHg28z56nEFwFNcsr19jUdTgpDT+/f5YQFjVyc8+MAXqR4fRuAt0i/fx7A5xXb/SWAv1zIMcwH8tLQ8u9AkEFx7i733uV1MmAs2MJIXs6iN7QYmXyDZ8M5KNtBxmBiME+Sg6L8WKvJ2w/95gWLuh5SGHR4qcQXD03z14NyUpNEBHTruFL40t5HYj2o9P5dFujQThJ+EhaIr1+qesu992QNMMbwqmesxXPO8FuCkPygGlyadZIwNF96SxKg6HNaZVCqFkiLCU1j0Fha19MIrosvNUnEIWAwOlESn5FekOWAzgxQ3k1fqkUZlBxrZivuYk+0plB40TEKPKrBWGVHtwOdJLSWTBKAK30s9yaW1Ek6RTwYkxkUF6+lcCHf4kvNoHwpf3k/Z52CjgxQZigHFSfxzXqdzOMWvaP9qGa/jVx8rkmC4U3P3YgH9k7itZesi+5Agd68ETBiLEds3TiIrRuXT83RcgSTCqHIH5NKfD5kJ+1S54L6CxlkDA2FDluDa7miIwMUzY4q9ajEJwebGY9B9cQGKM96rhhcVC4+udWRqWsY7cnh6297duLj/tbbn4PhnvZ3Q0ixtJDXg0olvihU6sNS4ZUXrcElGwcXfSXmFMnQkVfBZ1AuQ5Jb68vMpzmDCrb3kSF3KvclPlfmc/j8ZoZLnU9KsThgUjdzEaDSCCUgq2tLnYPKGBpOS5+zZYOOFFpJcitWo72+5GAzU3YZVLdiMUAAyuJdgsyu/FyTIxbUS+ssOhcyg0pbHUUR6MiS2r07Gh05SlKAorWe4iQ+YlBxdUTCJKF4hug1XQv23KMAlTaj7GAECnVTiS+MuGVrUnQeOvLqU3Ao1iy3tkl6IOR8EtVJxQUoenhU8gzzLOG6xsTs2HK4WFAvnRl2Luh2odV03dfS+4EgP4NpgOpsdOTVJ+ZTqtowdS0g66nySc1dfOrBRdeYaw2XWh0dnCoDAIa6U7NDp4LBux94utyGCqp+lyk6Ex0doGq2E5HaVOUPzSS+uNVQaakAud7p0YPTAIAL1vTN69hTnPyQGRRPm8VGwBjzV5BO65E6Gh3p4pODUlhqCw8UeVOPbRXkd5JQf47uBScKYLbD8fjhGfTkDGwYKsz38FOc5CBJ2GVQ3mtpgApA1xgc2291dOHaPqzsS7YqbopTBx0ZoBhjyOgaana0nX+YDcU5+IDGOSjA7VihSd0fbIfjkQPTOH9NX9o5IAU4eGqSiIGuMdRtLiS+715/+Qk+ohQnAh3Ln0meC0t8TEgL7g+NOoELiS9mdHEZlN9gtly3sf3IDM5fm8p7nQxiS5z7nSTSCUsQYtmWVOLraHTs1ffXd1JLfHqCAHXpaYP4s6vPxIVr+5V/NzQWWFbj8UMzqNscF6xRb5+iM8BEDiq1mceBVInUxdfZ6EiJD/CZU/gBCAeormx8T66cqeOPX7Q59u+0RAft88F9kwCA81ODREeDgpHDeVqoGwOx7EXq4utodG6AorWcIi6+MIOaf3NWesjo/0PTFfTlTawbzM97nylOfpDNnAOwRaujE3hAyxBi2Yv0xHQ0Oj5AZSISn/u/n4Oaf1djXXN7rmkek+IcuGBtapDodDCJQaXLbahBjDKV+DobHXv1m0t87uuNXHzNYGiaSPbS/+el8l7Hg0kmCaqDiqul61SkEl8KoJMDlBEToEKy3ELa7lMdFP0MpAW6KdJWR0lAz2Has7Kz0bFXXwQoI8yg3P9FDioz/wBl6n4fPgp4qcU8BYUi12aeuvhU0EMTxRSdiY7NQWUpQGnhHFTIJLEAiY9yUPTzQMHEmv7UINHp8DtJ+AwK6TgcgDBJGB07h06BTmZQsTko9/92SHyGpgUC3vlr+9NkeAqfQcFf1TlvpkuMy9BTk0QKdDCDipf4ggwqbrn3JNA1Bp27+3nNJetw8bqBee8rxakDmqQ4nKNYa7xqc6dCMKh0WZqORsc+FUk7SSxk4HjrFaeLBQr/+qXnzHs/KU4tsP/f3r1H2VWWdxz//mZyvxiSEkMkLRcJiqB4ibdGIGqIWETAitYLRClN1YrWSwWvWKEW10IXKrWIiqRqWcvlBVhYiZF6QdCWSLlWl0GhikYMFzWJZsjl6R/vu5OdyTmTmTlnztnn7N9nrVkz+3Jm3mf2OfvZ77vf992lKtSWISeoRnYnKNeg6qyloy9pnqS1ktbn7w2rCJJW5n3WS1qZ182Q9DVJP5Z0l6QLWynLWBVNfM0et9GOe1DPffyjWXHkAeN+vfWngV01KNgylJr4Zk5xE1+ZE5RB6/egzgWuj4jFwPV5eQ+S5gHnAc8EngGcV0pkF0XE44GnAEslvbDF8oza7pkkGtegRjNZrNl47K5Axa4a1IwWeov2o90Ddd3EV2etJqiTgdX559XAKQ32eQGwNiIeioiHgbXACRHxh4j4FkBEPALcAixqsTyj1nQcVP5gDDhB2QQp16A2P7KdKYMDu96PlkxyDcpoPUEtiIgN+edfAwsa7HMg8IvS8n153S6S9gNOItXCGpK0StI6Ses2btzYWqlp/riNdvbiM2uoNFD3D0M7RpyQuK48m7nBKDpJSPom0OhGyrvLCxERkqLBfvv6/ZOAK4GPRcTPmu0XEZcBlwEsWbJkzH9nuKn7mOqo+O4alLVb+XlQW4a2u3mvAXczNxhFgoqI5c22Sbpf0sKI2CBpIfCbBrv9ElhWWl4EfLu0fBmwPiIuHlWJ22SfUx0NasTHvZuNV3kmiS2PbPdFUAPFvWHfg6q3Vi9PrgFW5p9XAlc32GcNsELS3Nw5YkVeh6QLgDnA37dYjjFr3kkifR8cGGipB59ZM0VP0Z0RbBnawQw38e3Fs5kbtJ6gLgSOl7QeWJ6XkbRE0qcBIuIcXnV0AAAQw0lEQVQh4Hzg5vz1gYh4SNIiUjPhE4BbJN0q6awWyzNqUyelk8Le96B29+Lzla1NhPLzoFyDaszdzA1aHKgbEQ8Cz2+wfh1wVmn5cuDyYfvcRxdnINvXQN1jF+/P4Qtmd7xc1v/Kz4PaMrSdBbOndbdAFeSZJAzqPJNE0Uli+FRH+YPxmqWHdLxMVg/ao5OEm/gacScJgzpPFtt0HFRpKhqzCVB+HpSb+BpzE5+BE1TDJj4/PM4m0h73oNzNvKEiQfmBhfVW26M/0kwS7lluE6l4fw1t28m2HcEsN/HtZbA03MPqq7YJqvlAXfzMJptQxdtr09A2wPPwNeJu5gY1TlAjNfE5PdlEKi6ANm9NE8X6HtTeJrkXn1HjBHXUgXM4c+khPP3geXusHxjA96BsQhXvrs3FTOZu4tvLwICYNCC3ZtRcbS/dpk0e5H0nPWGv9b4HZROtuADa7IcVNjU44OY9q3ENqhn34rOJtuseVG7im+l7UHuZPW0yc6ZP7nYxrMv8yRhmQHRxfgurg71rUG7iG+51xz6Wlz6tY4+Hs4pyghpmxZEH8ChfudlEyhdAm12DamrOjMnMmeHPYd35kzHM0sP2Z+lh+3e7GNbHfA/KbHR8D8qsw4oW5E3uZm42Iicosw7bXYPaxoBg2mR/DM0a8SfDrMOKXnybh7Yzc8okj/Uxa8IJyqzDVOok4UG6Zs05QZl1WDGZ1uah7e4gYTYCJyizDhsoDdR1F3Oz5pygzDqsuOc0tH2nB+majcAJyqzDynM9ugZl1pwTlFmHlXvt+R6UWXNOUGYdVu5V7iY+s+acoMw6rDxbvpv4zJprKUFJmidpraT1+fvcJvutzPusl7SytP46SbdJukvSpZJ8OWl9rzws1018Zs21WoM6F7g+IhYD1+flPUiaB5wHPBN4BnBeKZG9LCKOBo4C5gOntVges8rbowblJj6zplpNUCcDq/PPq4FTGuzzAmBtRDwUEQ8Da4ETACLi93mfScAUIFosj1nl7XkPyjUos2ZaTVALImJD/vnXwIIG+xwI/KK0fF9eB4CkNcBvgE3Al5r9IUmrJK2TtG7jxo0tFtuse+Ru5majss8EJembku5s8HVyeb+ICMZRA4qIFwALganA80bY77KIWBIRS+bPnz/WP2NWGcLdzM1GY5+fjohY3mybpPslLYyIDZIWkmpCw/0SWFZaXgR8e9jf2CrpalKT4dpRlNusZw2ULgtnTvE9KLNmWm3iuwYoeuWtBK5usM8aYIWkublzxApgjaRZOakhaRJwIvDjFstjVnmuQZmNTqsJ6kLgeEnrgeV5GUlLJH0aICIeAs4Hbs5fH8jrZgLXSLoduJVU+7q0xfKYVd6AB+qajUpLl28R8SDw/Abr1wFnlZYvBy4fts/9wNNb+ftmvci9+MxGxzNJmHVYeS6+Ge7FZ9aUE5RZh+0xk4Q7SZg15QRl1mHFTBJTJw0wadAfQbNm/Okw67CihW+W7z+ZjcgJyqzDihqUO0iYjcwJyqxLZvj+k9mInKDMOmwgD4RyE5/ZyJygzDqs6MU3wwnKbEROUGYdVtyDmuVZJMxG5ARl1mFFLz4P0jUbmROUWYe5m7nZ6DhBmXVYMZu5e/GZjcwJyqzDitnMPQ7KbGROUGYdNn3KIDOmDLJo7vRuF8Ws0nwJZ9ZhM6ZM4nvnPI/9pk/udlHMKs0JyqwL5s2c0u0imFWem/jMzKySnKDMzKySnKDMzKySnKDMzKySnKDMzKySnKDMzKySnKDMzKySFBHdLsOYSdoI/N8YX7Y/8MAEFKcq+j2+Qh3irEOMhTrEWocYobU4D4qI+cNX9mSCGg9J6yJiSbfLMVH6Pb5CHeKsQ4yFOsRahxhhYuJ0E5+ZmVWSE5SZmVVSnRLUZd0uwATr9/gKdYizDjEW6hBrHWKECYizNvegzMyst9SpBmVmZj3ECcrMzCrJCaqHSFK3y2A2Fn7PWiucoHrLrgdM9vMHX9LjJPX1e1PSKyUdnX/u22OJzzHWgr5480g6RdL53S7HRJF0gqQ1wEWSTgWIPuzdIul4Sf8FnEWfvDeHk7Rc0g3AxcBToG+P5YmSrgXOl7S02+WZKPnc83FJ87pdlonSzfNrzz7yPV91DgCvBc4FDpL0jYi4obsla48c32Tgg8CzgQ8Bi4DTJN0ZEeu7Wb52yXFOAt4LvAI4JyK+Ut7e6yfwHOM0YDXwaOAC4GRgRt4+GBE7ulfC9pL0NOA84P3Ao4CVkhZHxBWSBiJiZ1cL2Ab5mJ4K/BMwG/i2pK/2Q2xQnfNrz16lRrIDuJt0JfoGoG9qUTm+R4DrgOMi4hrgJmAbcE9XC9dGOc5twE7gS0VyknSMpMndLV175Bj/CHwhIpZFxBrSsTw9b++b5JQtB26IiP8ArgZ+DbxJ0pyI2NkPTZr5oulnwHOANwOvJl1A9oWqnF97LkFJepOkT0k6K6/6TkRsiohPATMl/XXer+dig73ji4hvRsR2SX8BfAV4HPBBSS/P+/fkh70U56q86lJgoaTPSroDeAfwGeDMvH/PxVmK8W8AIuLqvH6QdJFxl6Q/7WYZ22F4nMC3gJMkzc2JeRvwO+Ac6N0mTUkrJR1fWnVnRDwYEV8mxfgSSVO6VLy2qNr5tadO4pJeA7wS+DJwuqR3AoeWdnkf8Nb8wei5qnaD+N4l6bC8+QHghIh4FukEcKakg3vxwz4szldJeg8wBFwFTAFOA16ct79E0p/1WpzDYnx1PpaHwq4a0++Bo4Hfdq2QbdAgzncD9wJrgM/l+22HAhcC+0ma2aWijpukuZK+RIrhw/kCA6BcG/wocBJw1LDX9syFVRXPrz2VoIDnAx+KiOuAt5Ha9V9VbIyIrwM/AlZJmi3ptO4Uc9yGxzeFHF9E/HdE/CTv9yNgI7C9K6Vs3fA4pwJ/GxFXAasi4sc5Id1OOoFv615Rx63RsXx1sTEi7gC2An/VneK1TaPP5BkRcTapWegDEfFaUqzTI2JL94o6PhHxMPAN4Ajgh6QTdbEt8vcbgVuBF0p6fNEy0GMXVpU7v/ZEgipVJ/8HeBFARKwDvg8cOKyX0DnAPwPrgQM6Wc7xGiG+HwCPadAL6jWkG+wPdqqM7TBCnDcCh0haOuwEthKYDjzc0YK2YB/H8kBJz8n7iVTLmNZLV9mFfRzLwyUdExE/j4i1eb8TgZ92vqStKR2bf4uI3wKfINXqD8r30wZL/4uLgXcC3yF1humJGlSVz6+VTFCSjpQ0rVguVSdvBAYkHZuX7wQ2AI/JrzuM9Aa6CnhqRHy8c6UevTHG9yt2x3eGpDuBQ4DX5/b9ymrhOP6lpNtIzQuvj4itHSz2mIzjWC7M+wXpJLalF66yxxHnAfl1x0r6DrCYdJ+x0hrEWdSQtubvNwNfJ/XeIyJ25ES1ALgE+E/gyRFxQfn1VSJpqaTHFstVPr9WKkFJepKk75G64f5JaX1RzvXAXcDLlbrm3gcsAA7O238HvDEiXhIRv+pcyUdnnPEdQEpIkJq8VkXEyoi4v4NFH5MWjmMR50+A10XEGVWNs4VjeXDp17w9Ii7vUJHHpQ3H8l7gDRFxakRU9qmyI8SpBh0CLgEOy8lsvqRDSPeIz46IF0fEhs6VfPQkPVXSN0hJdE5pfWXPr5VKUMB7SF2NT42IX8KuMSJFht8E3EC6Z3GRUjfkueSmrojYGNUeHzTe+B4AiIhbI+KmLpR7rFqN846I+H4Xyj0WLb1XASINI6i6Vo/lzyPiri6Ue6yaxRm5hjRd0ixIMQFfBe4gxT4316R+3rXSj0DSZEmfJD0O42OkpuVleVulz6+VSFCSBnIPp80RcXFed7yk/QDl5QuAfydl8feS/nE35OXVXSn4KPV7fIU6xFmHGMFxDovzfOAL5B5tkl5B6gByEfDEiLilK4UfvanAd4FjIuJa0nCVIyRNyj1KkfSPVPBYdm0mCUnPAh6KiJ/kK5QHgGMkvYg01c104H7gR5KuJL053hkRd+fXnwnMjIhNXQphRP0eX6EOcdYhRnCcI8T5WOAdRZykMWzLIqKyA+bLMZLuc36htHkQ2BFpfKWAJ5LuEZ4bET/Nr6/GsYyIjn4B+wFfI1Un30P6JxTb3gXcArw4Lx9LGon+7NI+A50us+OrZ5x1iNFxjinOwW7HMN4YSbXBgfzzYaQEPLfYVtVj2Y0mvpmkNtCz88/HlrZdS7ohV0y8uI40TcpWSNXxqP4A3H6Pr1CHOOsQIzhOGF2cvTAlVcMYI9mZO0Tcm/c5rtgG1TyWHUlQSt2jj5P0qEg3IC8Dvkg6+M+UdCBARNwO/APwd5L2Jw1sfCK7b9JV6p9X6Pf4CnWIsw4xguOkj+IcRYxFN3HlOKbmlxbJV1DNGJWTZ/t/cQr6ANKNt52kQXozgTdH7m6qNADsZcC6iPhc6bVvJbVvLwbeEhH/OyGFbEG/x1eoQ5x1iBEcJ30U5xhjvDkiPp/XDUbEDkmfB+6OiPd3o/yjNkHtoIP5++HA54t1wMeBrwzb9y2ksQdzgNml9ZO73f5Z1/jqFGcdYnSc/RVnCzHOKK2f0u04RvPV1iY+pWk/Pkiabfs40szbO2DXBJlvBv48byt8CpgFrAXuLqqjkR7BUCn9Hl+hDnHWIUZwnNA/cbYhxntKMfbCGLz2Jaj8T/khqf/83aRnh2wDnivpGbCrjfP9+atwImlMwW2kMQWVmwEC+j++Qh3irEOM4DjpozjrEGMj7RwHtRP4cOT2XElPIU138j7gX4Gn5R4kVwHPU3pUxL2kG3XLI+K7bSzLROj3+Ap1iLMOMYLj7Kc46xDjXtrZxPdD4Iva/ayUG4E/i4grgEFJZ+cMv4g0SOxeSA9x65F/Xr/HV6hDnHWIERznFfRPnHWIcS9tS1AR8YeIGIrdYwWOJz2zCNJz7Y+QdC1wJWlA3K7ujb2g3+Mr1CHOOsQIjjP/3Bdx1iHGRto+1VHO8EGaBfeavHoTaaT2UcA9kSdjjIjKTUW/L/0eX6EOcdYhRnCc9FGcdYixbCIG6u4EJpNmM35SzurvBXZGxPeKf14P6/f4CnWIsw4xguPspzjrEOMuEzJQV2miwpvy12cj4jNt/yNd1O/xFeoQZx1iBMfZT+oQY2GiEtQi4HTgIxEx1PY/0GX9Hl+hDnHWIUZwnP2kDjEWJmyqIzMzs1ZU4oGFZmZmwzlBmZlZJTlBmZlZJTlBmZlZJTlBmZlZJTlBmXWQpB2SbpV0l6TbJL0tT/I50msOlvTKTpXRrCqcoMw6648R8eSIOJI0n9oLgfP28ZqDAScoqx2PgzLrIEmbI2JWaflQ4GZgf+Ag4HOkR3cDvDEibpL0A+AI4B5gNfAx4EJgGTAV+JeI+GTHgjDrECcosw4anqDyut+Sno66iTSn2lZJi4ErI2KJpGXA2yPiRXn/VcCjI+ICSVNJj144LSLu6WgwZhOs7bOZm9m4TQYukfRk0qO8D2+y3wrSRKEvzctzgMWkGpZZ33CCMuui3MS3A/gN6V7U/cDRpPvDW5u9DDg7ItZ0pJBmXeJOEmZdImk+cClwSX52zxxgQ34y6ulA8fTUTcDs0kvXAK+XNDn/nsMlzcSsz7gGZdZZ0yXdSmrO207qFPGRvO0TwJclnQFcB2zJ628Hdki6DbgC+CipZ98t+ampG4FTOhWAWae4k4SZmVWSm/jMzKySnKDMzKySnKDMzKySnKDMzKySnKDMzKySnKDMzKySnKDMzKyS/h84sPIuKvnqyAAAAABJRU5ErkJggg==\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"dc": {
"key": "46"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "PmbAad3QoEOi"
},
"cell_type": "markdown",
"source": [
"## 7. Calculating Excess Returns for Amazon and Facebook vs. S&P 500\n",
"<p>Next, we need to calculate the relative performance of stocks vs. the S&amp;P 500 benchmark. This is calculated as the difference in returns between <code>stock_returns</code> and <code>sp_returns</code> for each day.</p>"
]
},
{
"metadata": {
"dc": {
"key": "46"
},
"tags": [
"sample_code"
],
"trusted": true,
"id": "x31myunOoEOi",
"outputId": "754ea25c-729c-4739-fd85-2630b8f55d8d"
},
"cell_type": "code",
"source": [
"# calculate the difference in daily returns\n",
"excess_returns = stock_returns.sub(sp_returns, axis=0)\n",
"print(excess_returns.head())\n",
"\n",
"# plot the excess_returns\n",
"excess_returns.plot()\n",
"\n",
"# summarize the excess_returns\n",
"excess_returns.describe()"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": " Amazon Facebook\nDate \n2016-01-04 NaN NaN\n2016-01-05 -0.007036 0.002977\n2016-01-06 0.011317 0.015452\n2016-01-07 -0.015358 -0.025343\n2016-01-08 0.009374 0.004813\n",
"name": "stdout"
},
{
"output_type": "execute_result",
"execution_count": 68,
"data": {
"text/plain": " Amazon Facebook\ncount 251.000000 251.000000\nmean 0.000360 0.000168\nstd 0.016126 0.015439\nmin -0.100860 -0.051958\n25% -0.006229 -0.005663\n50% 0.000698 -0.000454\n75% 0.007351 0.005814\nmax 0.100728 0.149686",
"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>Amazon</th>\n <th>Facebook</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>count</th>\n <td>251.000000</td>\n <td>251.000000</td>\n </tr>\n <tr>\n <th>mean</th>\n <td>0.000360</td>\n <td>0.000168</td>\n </tr>\n <tr>\n <th>std</th>\n <td>0.016126</td>\n <td>0.015439</td>\n </tr>\n <tr>\n <th>min</th>\n <td>-0.100860</td>\n <td>-0.051958</td>\n </tr>\n <tr>\n <th>25%</th>\n <td>-0.006229</td>\n <td>-0.005663</td>\n </tr>\n <tr>\n <th>50%</th>\n <td>0.000698</td>\n <td>-0.000454</td>\n </tr>\n <tr>\n <th>75%</th>\n <td>0.007351</td>\n <td>0.005814</td>\n </tr>\n <tr>\n <th>max</th>\n <td>0.100728</td>\n <td>0.149686</td>\n </tr>\n </tbody>\n</table>\n</div>"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"dc": {
"key": "53"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "FM6WrwG3oEOj"
},
"cell_type": "markdown",
"source": [
"## 8. The Sharpe Ratio, Step 1: The Average Difference in Daily Returns Stocks vs S&P 500\n",
"<p>Now we can finally start computing the Sharpe Ratio. First we need to calculate the average of the <code>excess_returns</code>. This tells us how much more or less the investment yields per day compared to the benchmark.</p>"
]
},
{
"metadata": {
"dc": {
"key": "53"
},
"tags": [
"sample_code"
],
"trusted": true,
"id": "_-DUcm9joEOk",
"outputId": "2d0eb67b-0550-4b0d-a047-663a90cbeb32"
},
"cell_type": "code",
"source": [
"# calculate the mean of excess_returns \n",
"avg_excess_return = excess_returns.mean()\n",
"\n",
"# plot avg_excess_returns\n",
"avg_excess_return.plot.bar()\n",
"plt.title('Mean of the Return Difference')"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 70,
"data": {
"text/plain": "Text(0.5, 1.0, 'Mean of the Return Difference')"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"dc": {
"key": "60"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "ZpSMZNLOoEOk"
},
"cell_type": "markdown",
"source": [
"## 9. The Sharpe Ratio, Step 2: Standard Deviation of the Return Difference\n",
"<p>It looks like there was quite a bit of a difference between average daily returns for Amazon and Facebook.</p>\n",
"<p>Next, we calculate the standard deviation of the <code>excess_returns</code>. This shows us the amount of risk an investment in the stocks implies as compared to an investment in the S&amp;P 500.</p>"
]
},
{
"metadata": {
"dc": {
"key": "60"
},
"tags": [
"sample_code"
],
"trusted": true,
"id": "8EQD7CR6oEOk",
"outputId": "d78c37f2-bbe5-4efe-8ee3-7533ab6b8756"
},
"cell_type": "code",
"source": [
"# calculate the standard deviations\n",
"sd_excess_return = excess_returns.std()\n",
"\n",
"# plot the standard deviations\n",
"sd_excess_return.plot.bar()\n",
"plt.title('Standard Deviation of the Return Difference')"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 72,
"data": {
"text/plain": "Text(0.5, 1.0, 'Standard Deviation of the Return Difference')"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"dc": {
"key": "67"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "2cr2rr_5oEOl"
},
"cell_type": "markdown",
"source": [
"## 10. Putting it all together\n",
"<p>Now we just need to compute the ratio of <code>avg_excess_returns</code> and <code>sd_excess_returns</code>. The result is now finally the <em>Sharpe ratio</em> and indicates how much more (or less) return the investment opportunity under consideration yields per unit of risk.</p>\n",
"<p>The Sharpe Ratio is often <em>annualized</em> by multiplying it by the square root of the number of periods. We have used daily data as input, so we'll use the square root of the number of trading days (5 days, 52 weeks, minus a few holidays): √252</p>"
]
},
{
"metadata": {
"dc": {
"key": "67"
},
"tags": [
"sample_code"
],
"trusted": true,
"id": "VA1jiMzDoEOl",
"outputId": "bd3ae7de-93d0-4312-e29d-24f963154749"
},
"cell_type": "code",
"source": [
"# calculate the daily sharpe ratio\n",
"daily_sharpe_ratio = avg_excess_return.div(sd_excess_return)\n",
"\n",
"# annualize the sharpe ratio\n",
"annual_factor = np.sqrt(252)\n",
"annual_sharpe_ratio = daily_sharpe_ratio.mul(annual_factor)\n",
"\n",
"# plot the annualized sharpe ratio\n",
"annual_sharpe_ratio.plot.bar()\n",
"plt.title('Annualized Sharpe Ratio: Stocks vs S&P 500')"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"execution_count": 74,
"data": {
"text/plain": "Text(0.5, 1.0, 'Annualized Sharpe Ratio: Stocks vs S&P 500')"
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": "<Figure size 432x288 with 1 Axes>",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"metadata": {
"dc": {
"key": "74"
},
"deletable": false,
"editable": false,
"run_control": {
"frozen": true
},
"tags": [
"context"
],
"id": "OqHiFtcEoEOm"
},
"cell_type": "markdown",
"source": [
"## 11. Conclusion\n",
"<p>Given the two Sharpe ratios, which investment should we go for? In 2016, Amazon had a Sharpe ratio twice as high as Facebook. This means that an investment in Amazon returned twice as much compared to the S&amp;P 500 for each unit of risk an investor would have assumed. In other words, in risk-adjusted terms, the investment in Amazon would have been more attractive.</p>\n",
"<p>This difference was mostly driven by differences in return rather than risk between Amazon and Facebook. The risk of choosing Amazon over FB (as measured by the standard deviation) was only slightly higher so that the higher Sharpe ratio for Amazon ends up higher mainly due to the higher average daily returns for Amazon. </p>\n",
"<p>When faced with investment alternatives that offer both different returns and risks, the Sharpe Ratio helps to make a decision by adjusting the returns by the differences in risk and allows an investor to compare investment opportunities on equal terms, that is, on an 'apples-to-apples' basis.</p>"
]
},
{
"metadata": {
"dc": {
"key": "74"
},
"tags": [
"sample_code"
],
"collapsed": true,
"trusted": true,
"id": "jV11Ir9xoEOm"
},
"cell_type": "code",
"source": [
"# Uncomment your choice.\n",
"buy_amazon = True\n",
"# buy_facebook = True"
],
"execution_count": null,
"outputs": []
}
],
"metadata": {
"kernelspec": {
"name": "python3",
"display_name": "Python 3",
"language": "python"
},
"language_info": {
"name": "python",
"version": "3.6.7",
"mimetype": "text/x-python",
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"pygments_lexer": "ipython3",
"nbconvert_exporter": "python",
"file_extension": ".py"
},
"colab": {
"name": "notebook.ipynb",
"provenance": [],
"include_colab_link": true
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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