import itertools
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()
import itertools
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
cnx = mysql.connector.connect(user='******', password='',
host='localhost',
database='quantcode')
cursor = cnx.cursor()
if not os.path.exists('ETF'):
os.makedirs('ETF')
for category in etf.etf_dict.keys():
ts = {}
if not os.path.exists('ETF/' + category):
os.makedirs('ETF/' + category)
for ticker in etf.etf_dict[category]:
filename = 'ETF/' + category + '/' + ticker + '.csv'
qs.download(ticker, filename)
ts.update({ticker: qs.load(filename)})
for key1 in ts.keys():
for key2 in ts.keys():
if key1 != key2:
# print key1 + "*" + key2
cadf = qs.cadf_helper(ts[key1], ts[key2])
volume1 = qs.getVolume(key1, category)
volume2 = qs.getVolume(key2, category)
add_database = ('INSERT INTO etfcadf '
'(ticker1, ticker2, volume1, volume2, category, cadf, hedgeRatio, pval, usedlag, nobs, cvalue1, cvalue5, cvalue10, icbest, hurst, halflife, vratio, vratiozscore, vratiopval) '
'VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)'
'ON DUPLICATE KEY UPDATE volume1 = %s, volume2 = %s, category = %s, cadf = %s, hedgeRatio = %s, pval = %s, usedlag = %s, nobs = %s, cvalue1 = %s, cvalue5 = %s, cvalue10 = %s, icbest = %s, hurst = %s, halflife = %s, vratio = %s, vratiozscore = %s, vratiopval = %s')
data = (key1, key2, volume1, volume2, etf.categories[category], float(cadf['results']['adf']), float(cadf['hedgeRatio']), float(cadf['results']['pval']), cadf['results']['usedlag'], cadf['results']['nobs'], float(cadf['results']['cvalues']['1%']), float(cadf['results']['cvalues']['5%']), float(cadf['results']['cvalues']['10%']), float(cadf['results']['icbest']), float(cadf['hurst']), float(cadf['halflife']), float(cadf['vratio']['vratio']), float(cadf['vratio']['zscore']), float(cadf['vratio']['pval']), volume1, volume2, etf.categories[category], float(cadf['results']['adf']), float(cadf['hedgeRatio']), float(cadf['results']['pval']), cadf['results']['usedlag'], cadf['results']['nobs'], float(cadf['results']['cvalues']['1%']), float(cadf['results']['cvalues']['5%']), float(cadf['results']['cvalues']['10%']), float(cadf['results']['icbest']), float(cadf['hurst']), float(cadf['halflife']), float(cadf['vratio']['vratio']), float(cadf['vratio']['zscore']), float(cadf['vratio']['pval']))
try:
#!/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])
