"""
from datetime import datetime, timedelta
import pandas as pd
import sys
from utilities import analyze
def readPriceData(fname):
""" Read orders data from csv of format y | m | d | value
@return a time series
"""
df = pd.read_csv(fname, header=None, names=['y', 'm', 'd', 'value'])
# parse dates
dates = df.apply(lambda row: datetime(int(row['y']), int(row['m']), int(row['d'])), axis=1)
return pd.Series(df['value'], index=dates)
if __name__ == '__main__':
pricesFname, marketSymbol = sys.argv
# test data:
# prices = pd.TimeSeries(data=[100., 150., 120., 300., 100., 150., 120., 300.],
# index=[datetime(2008, 12, 2), datetime(2008, 12, 3), datetime(2008, 12, 4), datetime(2008, 12, 5),
# datetime(2008, 12, 20), datetime(2008, 12, 30), datetime(2008, 12, 25), datetime(2008, 12, 15)])
prices = readPriceData(pricesFname)
analyze(prices, marketSymbol, verbosity=1)
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()
