73 lines
2.4 KiB
Python
73 lines
2.4 KiB
Python
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import os
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import time
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import statistics
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import pandas as pd
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import numpy as np
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from pandas_datareader import data
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dir_path = os.path.dirname(os.path.realpath(__file__))
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start_date = '2014-01-01'
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end_date = '2018-01-01'
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SRC_DATA_FILENAME = dir_path + '/goog_data.pkl'
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try:
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goog_data = pd.read_pickle(SRC_DATA_FILENAME)
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print('File data found...reading GOOG data')
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except FileNotFoundError:
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print('File not found...downloading the GOOG data')
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goog_data = data.DataReader('GOOG', 'yahoo', start_date, end_date)
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goog_data.to_pickle(SRC_DATA_FILENAME)
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goog_data_signal = pd.DataFrame(index=goog_data.index)
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goog_data_signal['price'] = goog_data['Adj Close']
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close = goog_data_signal['price']
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exe_start_time = time.time()
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import statistics as stats
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import math as math
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time_period = 20 # history length for Simple Moving Average for middle band
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stdev_factor = 2 # Standard Deviation Scaling factor for the upper and lower bands
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history = []
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sma_values = []
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upper_band = []
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lower_band = []
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""" Calculate BBAND """
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for close_price in close:
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history.append(close_price)
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if len(history) > time_period:
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del(history[0])
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sma = stats.mean(history) # BBAND_Middle
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sma_values.append(sma)
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variance = 0
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# Calculate variance using pure python
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for hist_price in history:
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variance = variance + ((hist_price - sma) ** 2)
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stdev = math.sqrt(variance / len(history))
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upper_band.append(sma + stdev_factor * stdev)
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lower_band.append(sma - stdev_factor * stdev)
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""" Draw Gragh """
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goog_data = goog_data.assign(ClosePrice=pd.Series(close, index=goog_data.index))
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goog_data = goog_data.assign(MiddleBollingerBand20DaySMA=pd.Series(sma_values, index=goog_data.index))
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goog_data = goog_data.assign(UpperBollingerBand20DaysSMA2StddevFactor=pd.Series(upper_band, index=goog_data.index))
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goog_data = goog_data.assign(LowerBollingerBand20DaysSMA2StddevFactor=pd.Series(lower_band, index=goog_data.index))
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import matplotlib.pyplot as plt
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fig = plt.figure()
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ax1 = fig.add_subplot(111, ylabel='Google price in $')
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goog_data['ClosePrice'].plot(ax=ax1, color='g', lw=2., legend=True)
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goog_data['MiddleBollingerBand20DaySMA'].plot(ax=ax1, color='b', lw=2., legend=True)
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goog_data['UpperBollingerBand20DaysSMA2StddevFactor'].plot(ax=ax1, color='y', lw=2., legend=True)
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goog_data['LowerBollingerBand20DaysSMA2StddevFactor'].plot(ax=ax1, color='r', lw=2., legend=True)
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plt.savefig(dir_path + '/bbands.png')
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plt.show()
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