password='',
host='localhost',
database='quantcode')
cursor = cnx.cursor()
qs.ensure_path('TS')
ts = {}
for stock in sp500.sp500:
filename = 'TS/' + stock + '.csv'
# qs.download(stock, filename)
if os.path.isfile(filename):
ts.update({stock: qs.load(filename)})
for key in ts.keys():
adf = qs.adf(ts[key])
hurst = qs.hurst(ts[key])
halflife = qs.halflife(ts[key])
vratio = qs.vratio(ts[key], adf['usedlag'])
cnx.commit()
add_database = (
"INSERT INTO adfresults "
"(ticker, adf, 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)"
"ON DUPLICATE KEY UPDATE adf = %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 = (key, float(adf["adf"]), float(adf["pval"]), adf["usedlag"],
adf["nobs"], float(adf["cvalues"]["1%"]),
float(adf["cvalues"]["5%"]), float(adf["cvalues"]["10%"]),
float(adf["icbest"]), float(hurst), float(halflife),
float(vratio["vratio"]), float(vratio["zscore"]),
import csv
import os
import shutil
import sys
import quantcode.johansen as johansen
import quantcode.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)
for i in enumerate(ts):
# augmented Dickey-Fuller test from statsmodels
results = qs.adf(ts[i], 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[i])
print 'Hurst exponent: ', qs.hurst(ts[i])
# print qs.hurst2(closes)
print 'CADF results: ', qs.cadf(ts[0], ts[1])
import csv
import os
import shutil
import sys
import quantcode.johansen as johansen
import quantcode.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)
for i in enumerate(ts):
# augmented Dickey-Fuller test from statsmodels
results = qs.adf(ts[i], 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[i])
print 'Hurst exponent: ', qs.hurst(ts[i])
# print qs.hurst2(closes)
print 'CADF results: ', qs.cadf(ts[0], ts[1])
cnx = mysql.connector.connect(user='******', password='',
host='localhost',
database='quantcode')
cursor = cnx.cursor()
qs.ensure_path('TS')
ts = {}
for stock in sp500.sp500:
filename = 'TS/' + stock + '.csv'
# qs.download(stock, filename)
if os.path.isfile(filename):
ts.update({stock: qs.load(filename)})
for key in ts.keys():
adf = qs.adf(ts[key])
hurst = qs.hurst(ts[key])
halflife = qs.halflife(ts[key])
vratio = qs.vratio(ts[key], adf['usedlag'])
cnx.commit()
add_database = ("INSERT INTO adfresults "
"(ticker, adf, 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)"
"ON DUPLICATE KEY UPDATE adf = %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 = (key, float(adf["adf"]), float(adf["pval"]), adf["usedlag"], adf["nobs"], float(adf["cvalues"]["1%"]), float(adf["cvalues"]["5%"]), float(adf["cvalues"]["10%"]), float(adf["icbest"]), float(hurst), float(halflife), float(vratio["vratio"]), float(vratio["zscore"]), float(vratio["pval"]), float(adf["adf"]), float(adf["pval"]), adf["usedlag"], adf["nobs"], float(adf["cvalues"]["1%"]), float(adf["cvalues"]["5%"]), float(adf["cvalues"]["10%"]), float(adf["icbest"]), float(hurst), float(halflife), float(vratio["vratio"]), float(vratio["zscore"]), float(vratio["pval"]))
cursor.execute(add_database, data)
cnx.commit()
cursor.close()
cnx.close()