def __request(self, symbol, stat):
try:
url = 'http://finance.yahoo.com/d/quotes.csv?s=%s&f=%s' % (symbol, stat)
return urllib.urlopen(url).read().strip().strip('"')
except IOError:
raise ufException(Errors.NETWORK_ERROR, "Can't connect to Yahoo server")
except BaseException as excep:
raise ufException(Errors.UNKNOWN_ERROR, "Unknown Error in YahooFinance.__request %s" % excep)
def readCol(self, colNumber, startRow=0, endRow=-1):
if abs(colNumber) > self.sheet.ncols:
raise ufException(Errors.INDEX_RANGE_ERROR,
"Excellib.readCol: col number too big: col %s, max %s" % (colNumber, self.sheet.ncols) )
if max(abs(startRow), abs(endRow)) > self.sheet.nrows:
raise ufException(Errors.INDEX_RANGE_ERROR,
"Excellib.readCol: row number too big: row %s, max %s" % (max(abs(startRow), abs(endRow)), self.sheet.nrows) )
if -1 == endRow:
endRow = self.sheet.nrows
return [self.readCell(i, colNumber) for i in range(startRow, endRow)]
def readRow(self, rowNumber, startCol=0, endCol=-1):
if abs(rowNumber) >= self.sheet.nrows:
raise ufException(Errors.INDEX_RANGE_ERROR,
"Excellib.readRow: row number too big: row %s, max %s" % (rowNumber, self.sheet.nrows) )
if max(abs(startCol), abs(endCol)) > self.sheet.ncols:
raise ufException(Errors.INDEX_RANGE_ERROR,
"Excellib.readRow: col number too big: col %s, max %s" % (max(abs(startCol), abs(endCol)), self.sheet.ncols) )
if -1 == endCol:
endCol = self.sheet.ncols
return [self.readCell(rowNumber, i) for i in range(startCol, endCol)]
def linearRegression(self):
if self.__regressioned:
return
if not self.__benchmarkValues:
self.__benchmarkValues = YahooFinance().get_historical_prices(self.__benchmark, self.__dateValues[0].date, self.__dateValues[-1].date)
tradeSuspended = False
if 0 in map(lambda x: float(x.adjClose), self.__dateValues):
tradeSuspended = True
#filter out date tha't not in both stock and benchmark
dateSet = set([dateValue.date for dateValue in self.__dateValues]) & set([dateValue.date for dateValue in self.__benchmarkValues])
self.__dateValues = filter(lambda dateValue: dateValue.date in dateSet, self.__dateValues)
self.__benchmarkValues = filter(lambda dateValue: dateValue.date in dateSet, self.__benchmarkValues)
if len(self.__dateValues) <= 1 or tradeSuspended:
msg = "Not enought dateValues" if len(self.__dateValues) <= 1 else "trade suspended"
LOG.debug(msg)
self.__beta = 0
self.__alpha = 0
self.__regressioned = True
return
try:
x = [float(self.__benchmarkValues[index + 1].adjClose)/float(self.__benchmarkValues[index].adjClose) for index in range(len(self.__benchmarkValues) - 1)]
y = [float(self.__dateValues[index + 1].adjClose)/float(self.__dateValues[index].adjClose) for index in range(len(self.__dateValues) - 1)]
(self.__beta, self.__alpha) = numpy.polyfit(x, y, 1)
self.__regressioned = True
except BaseException as excep:
raise ufException(Errors.UNKNOWN_ERROR, "stockMeasurement.linearRegression got unknown error %s" % excep)
def plot(self):
""" plot dataValue """
try:
fig = pyplot.figure()
i = 0
ax0 = None
for label, dateValues in self.dateValueDict.items():
if 0 == i:
ax = fig.add_axes(self.rect[i])
ax0 = ax
else:
ax = fig.add_axes(self.rect[i], sharex=ax0)
i += 1
ax.plot_date(
[datetime.strptime(dateValue.date, self.dateFormat) for dateValue in dateValues],
[dateValue.value for dateValue in dateValues],
fmt="b-",
)
ax.set_ylabel(label)
ax.set_ylim(
min([int(dateValue.value) for dateValue in dateValues]) / 1.1,
max([int(dateValue.value) for dateValue in dateValues]) * 1.1,
)
# ax.set_ylim(0, 1000)
pyplot.show()
except ufException as excep:
raise excep
except BaseException as excep:
raise ufException(Errors.UNKNOWN_ERROR, "plotDateValueDict.plot got unknown error %s" % excep)
def calculateReturn(self, dateValues, *args):
try:
return self.strategy(dateValues, *args)
except ufException as excep:
raise excep
except BaseException as excep:
raise ufException(Errors.UNKNOWN_ERROR, "tradingStrategyFactory.calculateReturn got unknown error %s" % traceback.print_exc())
def get_historical_prices(self, symbol, start_date, end_date):
"""
Get historical prices for the given ticker symbol.
Date format is 'YYYY-MM-DD'
Returns a nested list.
"""
try:
start_date = str(start_date).replace('-', '')
end_date = str(end_date).replace('-', '')
url = 'http://ichart.yahoo.com/table.csv?s=%s&' % symbol + \
'd=%s&' % str(int(end_date[4:6]) - 1) + \
'e=%s&' % str(int(end_date[6:8])) + \
'f=%s&' % str(int(end_date[0:4])) + \
'g=d&' + \
'a=%s&' % str(int(start_date[4:6]) - 1) + \
'b=%s&' % str(int(start_date[6:8])) + \
'c=%s&' % str(int(start_date[0:4])) + \
'ignore=.csv'
days = urllib.urlopen(url).readlines()
values = [day[:-2].split(',') for day in days]
# sample values:[['Date', 'Open', 'High', 'Low', 'Close', 'Volume', 'Adj Clos'], \
# ['2009-12-31', '112.77', '112.80', '111.39', '111.44', '90637900', '109.7']...]
data = []
for value in values[1:]:
data.append(StockDailyType(value[0], value[1], value[2], value[3], value[4], value[5], value[6]))
dateValues = sorted(data, key=itemgetter(0))
return dateValues
except IOError:
raise ufException(Errors.NETWORK_ERROR, "Can't connect to Yahoo server")
except BaseException as excep:
raise ufException(Errors.UNKNOWN_ERROR, "Unknown Error in YahooFinance.get_historical_prices %s" % excep)
#sample output
#[stockDaylyData(date='2010-01-04, open='112.37', high='113.39', low='111.51', close='113.33', volume='118944600', adjClose='111.6'))...]
def __buildExl(self, stock, workbook):
''' get one stock historical data and store it '''
try:
ws = workbook.add_sheet(stock)
#get data
yahooFinance = YahooFinance()
allData = yahooFinance.get_historical_prices(stock, self.__startDate, self.__endDate)
for col, field in enumerate(['date', 'open', 'high', 'low', 'close', 'volume', 'adjClose']):
ws.write(0, col, field)
for row, data in enumerate(allData):
for col, field in enumerate(['date', 'open', 'high', 'low', 'close', 'volume', 'adjClose']):
ws.write(row+1, col, getattr(data, field) )
except ufException as excp:
raise excp
except Exception:
raise ufException(Errors.UNKNOWN_ERROR, "historicalStorage.__buildExl got unknown error %s"
% traceback.print_exc())
def plot(self):
''' plot '''
try:
returns = []
deviations = []
portfolio1 = self.labelReturnDeviations[0]
portfolio2 = self.labelReturnDeviations[1]
for i in range(100):
returns.append(portfolio1['return']*i/100 + portfolio2['return']*(100-i)/100)
deviations.append(pow(portfolio1['deviation']*i/100, 2) + pow(portfolio2['deviation']*(100-i)/100, 2) + 2*(i/100)*((100-i)/100)*portfolio1['cov'])
pyplot.plot([math.sqrt(deviation) for deviation in deviations], returns,'b-')
pyplot.ylabel('Returns')
pyplot.xlabel('Deviations')
except ufException as excep:
raise excep
except BaseException as excep:
raise ufException(Errors.UNKNOWN_ERROR, "plotPortfolio.plot got unknown error %s" % excep)
def buildExls(self, stocks, div=1):
''' get a list of stock data and store '''
print "BuildExls %s, div %s" % (stocks, div)
if div < 1:
raise ufException(Errors.INDEX_RANGE_ERROR, "div need to be at least 1, %s are given" % div)
for i in range(div):
workbook = Workbook()
stocksToProcess = stocks[i * len(stocks)/div: (i+1) * len(stocks)/div]
for stock in stocksToProcess:
try:
self.__buildExl(stock, workbook)
except Exception:
print "failed buildExl for stock %s: %s" % (stock, traceback.print_exc())
#sleep for 2 seconds, or Yahoo server will throw exception
time.sleep(2)
fileName = '%s%d.xls' % (self.__outputPrefix, i)
print "Saved %s to %s" % (stocksToProcess, fileName)
workbook.save(fileName)
def readCell(self, rowNumber, colNumber):
''' read a cell'''
try:
return self.sheet.cell(rowNumber, colNumber).value
except BaseException as excep:
raise ufException(Errors.UNKNOWN_ERROR, "Unknown Error in Excellib.readCell %s" % excep)
