65 lines
1.8 KiB
Python
65 lines
1.8 KiB
Python
|
import os
|
||
|
|
import time
|
||
|
|
import statistics
|
||
|
|
import pandas as pd
|
||
|
|
import numpy as np
|
||
|
|
from pandas_datareader import data
|
||
|
|
|
||
|
|
dir_path = os.path.dirname(os.path.realpath(__file__))
|
||
|
|
|
||
|
|
start_date = '2014-01-01'
|
||
|
|
end_date = '2018-01-01'
|
||
|
|
SRC_DATA_FILENAME = 'goog_data.pkl'
|
||
|
|
|
||
|
|
try:
|
||
|
|
goog_data = pd.read_pickle(SRC_DATA_FILENAME)
|
||
|
|
print('File data found...reading GOOG data')
|
||
|
|
except FileNotFoundError:
|
||
|
|
print('File not found...downloading the GOOG data')
|
||
|
|
goog_data = data.DataReader('GOOG', 'yahoo', start_date, end_date)
|
||
|
|
goog_data.to_pickle(SRC_DATA_FILENAME)
|
||
|
|
|
||
|
|
goog_data_signal = pd.DataFrame(index=goog_data.index)
|
||
|
|
goog_data_signal['price'] = goog_data['Adj Close']
|
||
|
|
close = goog_data_signal['price']
|
||
|
|
exe_start_time = time.time()
|
||
|
|
|
||
|
|
import statistics as stats
|
||
|
|
import math as math
|
||
|
|
|
||
|
|
time_period = 20
|
||
|
|
|
||
|
|
history = [] # history of prices
|
||
|
|
sma_values = [] # to tracking sma
|
||
|
|
stddev_values = [] # history of computed stdev values
|
||
|
|
|
||
|
|
for close_price in close:
|
||
|
|
history.append(close_price)
|
||
|
|
if len(history) > time_period: # track at most 20 prices
|
||
|
|
del(history[0])
|
||
|
|
|
||
|
|
sma = stats.mean(history)
|
||
|
|
sma_values.append(sma)
|
||
|
|
|
||
|
|
variance = 0
|
||
|
|
for hist_price in history:
|
||
|
|
variance = variance + ((hist_price - sma) ** 2)
|
||
|
|
|
||
|
|
stdev = math.sqrt(variance / len(history))
|
||
|
|
stddev_values.append(stdev)
|
||
|
|
|
||
|
|
|
||
|
|
goog_data = goog_data.assign(ClosePrice=pd.Series(close, index=goog_data.index))
|
||
|
|
goog_data = goog_data.assign(StandardDeviationOver20Days=pd.Series(stddev_values, index=goog_data.index))
|
||
|
|
|
||
|
|
""" Visualization """
|
||
|
|
|
||
|
|
import matplotlib.pyplot as plt
|
||
|
|
|
||
|
|
fig = plt.figure()
|
||
|
|
ax1 = fig.add_subplot(211, ylabel='Google price in $')
|
||
|
|
goog_data['ClosePrice'].plot(ax=ax1, color='g', lw=2., legend=True)
|
||
|
|
ax2 = fig.add_subplot(212, ylabel='Stddev in $')
|
||
|
|
goog_data['StandardDeviationOver20Days'].plot(ax=ax2, color='b', lw=2., legend=True)
|
||
|
|
plt.savefig(dir_path + '/stdev.png')
|
||
|
|
plt.show()
|