import johansen
import quantstats as qs
import sp500
if not os.path.exists('TS'):
os.makedirs('TS')
ts = {}
for stock in sp500.sp500:
filename = 'TS/' + stock + '.csv'
qs.download(stock, filename)
ts.update({stock: qs.load(filename)})
# shutil.rmtree('TS', True)
results_file = open('results.csv', 'w')
results_file.write('Creation date: %s UTC\n' % str(datetime.datetime.utcnow()))
results_file.write('Pair Member 1,Pair Member 2,p-value')
results = []
counter = 1
for pair in itertools.combinations(ts.keys(), r=2):
results_file.write('\n%s,%s,%f' %
(pair[0], pair[1], qs.cadf(
ts[pair[0]], ts[pair[1]])['results']['pval']))
print counter
counter += 1
results_file.close()
import os
import shutil
import johansen
import quantstats as qs
import sp500
if not os.path.exists('TS'):
os.makedirs('TS')
ts = {}
for stock in sp500.sp500:
filename = 'TS/' + stock + '.csv'
qs.download(stock, filename)
ts.update({stock: qs.load(filename)})
# shutil.rmtree('TS', True)
results_file = open('results.csv', 'w')
results_file.write('Creation date: %s UTC\n' % str(datetime.datetime.utcnow()))
results_file.write('Pair Member 1,Pair Member 2,p-value')
results = []
counter = 1
for pair in itertools.combinations(ts.keys(), r=2):
results_file.write('\n%s,%s,%f' % (pair[0], pair[1], qs.cadf(ts[pair[0]], ts[pair[1]])['results']['pval']))
print counter
counter += 1
results_file.close()
#!/usr/bin/env python
import csv
import os
import shutil
import sys
import johansen
import quantstats as qs
ts = []
for i in xrange(1, 3):
filename = sys.argv[i] + '.csv'
qs.download(sys.argv[i], filename)
ts.append(qs.load(filename))
if len(sys.argv) >= 4 and sys.argv[3] == '-r':
os.remove(filename)
# augmented Dickey-Fuller test from statsmodels
results = qs.adf(ts[0], maxlag=None, regression='c', autolag='AIC')
print 'ADF results: ', results
# https://www.quantopian.com/posts/some-code-from-ernie-chans-new-book-implemented-in-python
print 'half-life: ', qs.halflife(ts[0])
print 'Hurst exponent: ', qs.hurst(ts[0])
# print qs.hurst2(closes)
print 'CADF results: ', qs.cadf(ts[0], ts[1])