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‎Tutorials/Beta Tutorial/Beta.py

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# -*- coding: utf-8 -*-
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# import libraries
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import pandas as pd
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import statsmodels.api as sm
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'''
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Download monthly prices of Facebook and S&P 500 index from 2014 to 2017
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CSV file downloaded from Yahoo File
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start period: 02/11/2014
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end period: 30/11/2014
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period format: DD/MM/YEAR
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'''
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fb = pd.read_csv('FB.csv', parse_dates=True, index_col='Date',)
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sp_500 = pd.read_csv('^GSPC.csv', parse_dates=True, index_col='Date')
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# joining the closing prices of the two datasets
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monthly_prices = pd.concat([fb['Close'], sp_500['Close']], axis=1)
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monthly_prices.columns = ['FB', '^GSPC']
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# check the head of the dataframe
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print(monthly_prices.head())
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# calculate monthly returns
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monthly_returns = monthly_prices.pct_change(1)
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clean_monthly_returns = monthly_returns.dropna(axis=0)
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# split dependent and independent variable
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X = clean_monthly_returns['^GSPC']
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y = clean_monthly_returns['FB']
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# Add a constant to the independent value
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X1 = sm.add_constant(X)
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# make regression model
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model = sm.OLS(y, X1)
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# fit model and print results
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results = model.fit()
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print(results.summary())
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# alternatively scipy linear regression
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from scipy import stats
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slope, intercept, r_value, p_value, std_err = stats.linregress(X, y)
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print(slope)
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# save OLS Regression Results as a PNG
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import matplotlib.pyplot as plt
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plt.rc('figure', figsize=(12, 7))
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plt.text(0.01, 0.05, str(results.summary()), {'fontsize': 10}, fontproperties = 'monospace')
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plt.axis('off')
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plt.tight_layout()
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plt.savefig('output.png')

‎Tutorials/Beta Tutorial/FB.csv

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Date,Open,High,Low,Close,Adj Close,Volume
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2014-11-01,75.470001,78.269997,72.510002,77.699997,77.699997,490965300
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2014-12-01,77.260002,82.169998,74.400002,78.019997,78.019997,534632100
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2015-01-01,78.580002,79.250000,73.540001,75.910004,75.910004,545698200
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2015-02-01,76.110001,81.370003,73.449997,78.970001,78.970001,474720300
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2015-03-01,79.000000,86.070000,77.260002,82.220001,82.220001,574223800
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2015-04-01,82.500000,85.589996,78.320000,78.769997,78.769997,541741400
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2015-05-01,79.239998,81.849998,76.790001,79.190002,79.190002,421283500
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2015-06-01,79.300003,89.400002,78.660004,85.769997,85.769997,537883500
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2015-07-01,86.769997,99.239998,85.230003,94.010002,94.010002,790781000
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2015-08-01,93.529999,98.739998,72.000000,89.730003,89.730003,794774200
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2015-09-01,86.849998,96.489998,85.720001,89.900002,89.900002,634526500
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2015-10-01,90.050003,105.120003,88.360001,101.970001,101.970001,571192300
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2015-11-01,101.720001,110.650002,100.470001,104.239998,104.239998,542369900
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2015-12-01,104.830002,107.919998,101.459999,104.660004,104.660004,440059600
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2016-01-01,101.949997,112.839996,89.370003,112.209999,112.209999,792410100
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2016-02-01,112.269997,117.589996,96.820000,106.919998,106.919998,873671800
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2016-03-01,107.830002,116.989998,104.400002,114.099998,114.099998,521306200
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2016-04-01,113.750000,120.790001,106.309998,117.580002,117.580002,741132500
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2016-05-01,117.830002,121.080002,115.879997,118.809998,118.809998,459696300
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2016-06-01,118.500000,119.440002,108.230003,114.279999,114.279999,450837700
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2016-07-01,114.199997,128.330002,112.970001,123.940002,123.940002,464098700
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2016-08-01,123.849998,126.730003,122.070000,126.120003,126.120003,365460600
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2016-09-01,126.379997,131.979996,125.599998,128.270004,128.270004,376355700
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2016-10-01,128.380005,133.500000,126.750000,130.990005,130.990005,313200300
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2016-11-01,131.410004,131.940002,113.550003,118.419998,118.419998,643698100
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2016-12-01,118.379997,122.500000,114.000000,115.050003,115.050003,408552500
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2017-01-01,116.029999,133.139999,115.510002,130.320007,130.320007,378873600
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2017-02-01,132.250000,137.179993,130.300003,135.539993,135.539993,384675700
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2017-03-01,136.470001,142.949997,136.080002,142.050003,142.050003,342098600
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2017-04-01,141.929993,151.529999,138.809998,150.250000,150.250000,275502100
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2017-05-01,151.740005,153.600006,144.419998,151.460007,151.460007,403586900
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2017-06-01,151.750000,156.500000,144.559998,150.979996,150.979996,414677400
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2017-07-01,151.720001,175.490005,147.800003,169.250000,169.250000,419907600
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2017-08-01,169.820007,173.050003,165.000000,171.970001,171.970001,303622800
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2017-09-01,172.399994,174.000000,161.559998,170.869995,170.869995,304818300
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2017-10-01,171.389999,180.800003,168.289993,180.059998,180.059998,318146600
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2017-11-01,182.360001,184.250000,174.000000,177.179993,177.179993,350998700

‎Tutorials/Beta Tutorial/^GSPC.csv

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Date,Open,High,Low,Close,Adj Close,Volume
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2014-11-01,2018.209961,2075.760010,2001.010010,2067.560059,2067.560059,63600190000
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2014-12-01,2065.780029,2093.550049,1972.560059,2058.899902,2058.899902,80743820000
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2015-01-01,2058.899902,2072.360107,1988.119995,1994.989990,1994.989990,77330040000
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2015-02-01,1996.670044,2119.590088,1980.900024,2104.500000,2104.500000,68775560000
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2015-03-01,2105.229980,2117.520020,2039.689941,2067.889893,2067.889893,76675850000
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2015-04-01,2067.629883,2125.919922,2048.379883,2085.510010,2085.510010,72060940000
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2015-05-01,2087.379883,2134.719971,2067.929932,2107.389893,2107.389893,65187730000
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2015-06-01,2108.639893,2129.870117,2056.320068,2063.110107,2063.110107,73213980000
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2015-07-01,2067.000000,2132.820068,2044.020020,2103.840088,2103.840088,77920590000
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2015-08-01,2104.489990,2112.659912,1867.010010,1972.180054,1972.180054,84626790000
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2015-09-01,1970.089966,2020.859985,1871.910034,1920.030029,1920.030029,79989370000
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2015-10-01,1919.650024,2094.320068,1893.699951,2079.360107,2079.360107,85844900000
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2015-11-01,2080.760010,2116.479980,2019.390015,2080.409912,2080.409912,75943590000
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2015-12-01,2082.929932,2104.270020,1993.260010,2043.939941,2043.939941,83649260000
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2016-01-01,2038.199951,2038.199951,1812.290039,1940.239990,1940.239990,92409770000
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2016-02-01,1936.939941,1962.959961,1810.099976,1932.229980,1932.229980,93049560000
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2016-03-01,1937.089966,2072.209961,1937.089966,2059.739990,2059.739990,92639420000
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2016-04-01,2056.620117,2111.050049,2033.800049,2065.300049,2065.300049,81124990000
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2016-05-01,2067.169922,2103.479980,2025.910034,2096.949951,2096.949951,78883600000
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2016-06-01,2093.939941,2120.550049,1991.680054,2098.860107,2098.860107,86852700000
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2016-07-01,2099.340088,2177.090088,2074.020020,2173.600098,2173.600098,69530250000
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2016-08-01,2173.149902,2193.810059,2147.580078,2170.949951,2170.949951,75610310000
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2016-09-01,2171.330078,2187.870117,2119.120117,2168.270020,2168.270020,77270240000
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2016-10-01,2164.330078,2169.600098,2114.719971,2126.149902,2126.149902,73196630000
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2016-11-01,2128.679932,2214.100098,2083.790039,2198.810059,2198.810059,88299760000
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2016-12-01,2200.169922,2277.530029,2187.439941,2238.830078,2238.830078,75251240000
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2017-01-01,2251.570068,2300.989990,2245.129883,2278.870117,2278.870117,70483180000
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2017-02-01,2285.590088,2371.540039,2271.649902,2363.639893,2363.639893,69162420000
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2017-03-01,2380.129883,2400.979980,2322.250000,2362.719971,2362.719971,81547770000
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2017-04-01,2362.340088,2398.159912,2328.949951,2384.199951,2384.199951,65265670000
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2017-05-01,2388.500000,2418.709961,2352.719971,2411.800049,2411.800049,79607170000
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2017-06-01,2415.649902,2453.820068,2405.699951,2423.409912,2423.409912,81002490000
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2017-07-01,2431.389893,2484.040039,2407.699951,2470.300049,2470.300049,63169400000
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2017-08-01,2477.100098,2490.870117,2417.350098,2471.649902,2471.649902,70616030000
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2017-09-01,2474.419922,2519.439941,2446.550049,2519.360107,2519.360107,66337980000
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2017-10-01,2521.199951,2582.979980,2520.399902,2575.260010,2575.260010,70871570000
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2017-11-01,2583.209961,2657.739990,2557.449951,2647.580078,2647.580078,73173260000

‎Tutorials/Beta Tutorial/output.png

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