def generateData(tickerList):
stockDataDict = {}
for ticker in tickerList:
stockDataDict[ticker] = Stock(ticker)
Stock.generateMACD(stockDataDict[ticker])
return stockDataDict
def generateData(tickerList):
stockDataDict = {}
for ticker in tickerList:
stockDataDict[ticker] = Stock(ticker)
Stock.generateTechnicalAnalysis1(stockDataDict[ticker])
return stockDataDict
def standardUpdateDef(tickerList):
for ticker in tickerList:
time.sleep(0.2)
stock = Stock(ticker)
if os.path.isfile(stock.dataPath):
dailyUpdate(ticker, stock)
else:
fullPriceUpdate(ticker, stock)
def standardUpdateDef(tickerList, ID):
count = 0
for ticker in tickerList:
count += 1
stock = Stock(ticker)
if os.path.isfile(stock.dataPath):
## dummy = Share(ticker)
## close = dummy.get_price()
## openValue = dummy.get_open()
## volume = dummy.get_volume()
## high = dummy.get_days_high()
## low = dummy.get_days_low()
## date = dummy.get_trade_datetime()[:10]
##
## value = str(date) + ',' + str(openValue)+ ',' + str(high)+ ',' + str(low)+ \
## ',' + str(close)+ ',' + str(volume)+ ',' + str(close)
##
## writeInFile(stock.dataPath,value)
lol = 'hier gebeurt echt niks'
else:
url = str('http://ichart.finance.yahoo.com/table.csv?s=' + ticker)
try:
## with open(stock.dataPath,'wb') as f:
## f.write(urllib2.urlopen(url).read())
## f.close()
u = urllib2.urlopen(url)
localFile = open(ticker + '.csv', 'w')
localFile.write(u.read())
localFile.close()
os.rename(ticker + '.csv', stock.dataPath)
except urllib2.HTTPError:
print stock.dataPath, 'not found'
#Move script to other directory
import os
abspath = os.path.abspath(__file__)
dname = os.path.dirname(abspath)
os.chdir(dname)
os.chdir('../')
import random
import sys
sys.path.insert(0, 'General')
from stockClass import Stock
import numpy as np
import matplotlib.pyplot as plt
tickerList = np.loadtxt('data/tickerOverview.txt',
delimiter=',',
skiprows=0,
usecols=(0, ),
unpack=False,
dtype='str')
#ticker = 'AAPL'
#ticker = tickerList[random.randint(0,len(tickerList)-1)]
stock = Stock(ticker)
Stock.generateStandard(stock)
import matplotlib.pyplot as plt import sys sys.path.insert(0, '../General') from stockClass import Stock ## Input ## ticker = 'AAPL' start = 200 end = 400 ## generate graphs stock = Stock(ticker) stock.generateMACD() plt.subplot(2, 1, 1) plt.plot(stock.closePrices[start:end]) plt.subplot(2, 1, 2) plt.plot(stock.MACDi[start:end]) plt.plot(stock.MACDScorei[start:end]) plt.plot(stock.MACDSignali[start:end]) plt.show()
import numpy as np
import sys
sys.path.insert(0, 'General')
from stockClass import Stock
import matplotlib.pyplot as plt
daysInPast = 2000
#tickerList = np.loadtxt('data/tickerOverview.txt', delimiter=',', skiprows=0, usecols=(0,), unpack=False,dtype = 'str')
tickerList = ['^DJI']
results = []
for ticker in tickerList:
stock = Stock(ticker)
stock.generateTrend()
if stock.status:
j = min(daysInPast, len(stock.closePrices) - 1)
stop = False
while j > 0 and not stop: # all start dates iterate
p0 = stock.closePrices[j]
found1 = False
i = 0
while not found1 and j - i > 0: # search for trend
pt = stock.closePrices[j - i]
found2 = False
if (pt - p0) / p0 > 0.1: #uptrend found