def writePortfolioData(portData, fname):
""" Output portfolio data.
@param portData: a time series
@param fname: name of the output file, which has the format y | m | d | value
@return: nothing
"""
f = open(fname, 'w')
for i in xrange(portData.shape[0]):
curDate = portData.index[i]
f.write(str(curDate.year) + ',' + str(curDate.month) + ',' + str(curDate.day) + ',' + str(portData.ix[i]) + '\n')
f.close()
if __name__ == '__main__':
initialInvestment, ordersFname, outputFname = sys.argv
"""
Test data:
symbol numShares
2008-12-03 AAPL 130
2008-12-08 AAPL -130
2008-12-05 IBM 50
"""
# ordersData = pd.DataFrame([['AAPL', 130], ['AAPL', -130], ['IBM', 50]],
# index=[datetime(2008, 12, 3), datetime(2008, 12, 8), datetime(2008, 12, 5)],
# columns=['symbol', 'numShares'])
ordersData = readOrdersData(ordersFname)
portValues = marketsim(ordersData, initialInvestment, verbose=True)
writePortfolioData(portValues, outputFname)
marketBenchMark = 1
holdingPeriod = 5
numStocksTraded = 100
initialInvestment = 100000
# ----- compute prices and create events -----
prices = getPrices(startDate, endDate, symbols, 'close', isSymbolsList=True, additionalSymbol=marketSymbol)
# prices = getPrices(startDate, endDate, symbols, 'close', additionalSymbol=marketSymbol)
bollingerVals, _, _, _, _ = calculateBollingerValues(prices, lookBackPeriod, numOfStds)
eventFilter, actionDates = createBollingerEventFilter(bollingerVals,
{'type': 'CROSS_WRT_MARKET_FALL', 'bolBenchMark': bolBenchMark,
'marketBenchMark': marketBenchMark, 'marketSymbol': marketSymbol,
'lookBackPeriod': lookBackPeriod, 'numOfStds': numOfStds})
try:
eventprofiler(eventFilter, {'close': prices}, i_lookback=lookBackPeriod, i_lookforward=holdingPeriod,
b_market_neutral=True, b_errorbars=True, s_market_sym=marketSymbol, s_filename='eventPlot.pdf')
except:
print "There aren't enough events for the event profiler."
# ----- trade and evaluate -----
orders = makeOrdersAccordingToEvents(eventFilter, holdingPeriod, numStocksTraded, saveIntermediateResults=True)
portValues = marketsim(orders, initialInvestment)
# calculateMetrics(portValues, saveIntermediateResults=True)
analyze(portValues, '$SPX', plotFname='performancePlot.pdf', verbosity=0)
plt.show()
