def parameters_generator():
instrument = ["dia"]
entrySMA = range(150, 251)
exitSMA = range(5, 16)
rsiPeriod = range(2, 11)
overBoughtThreshold = range(75, 96)
overSoldThreshold = range(5, 26)
return itertools.product(instrument, entrySMA, exitSMA, rsiPeriod, overBoughtThreshold, overSoldThreshold)
# Load the feed from the CSV files.
feed = yahoofeed.Feed()
feed.addBarsFromCSV("dia", "dia-2009.csv")
feed.addBarsFromCSV("dia", "dia-2010.csv")
feed.addBarsFromCSV("dia", "dia-2011.csv")
# Run the server.
server.serve(feed, parameters_generator(), "localhost", 5000)
import itertools
from pyalgotrade.optimizer import server
from pyalgotrade.barfeed import quandlfeed
def parameters_generator():
instrument = ["ibm"]
entrySMA = range(150, 251)
exitSMA = range(5, 16)
rsiPeriod = range(2, 11)
overBoughtThreshold = range(75, 96)
overSoldThreshold = range(5, 26)
return itertools.product(instrument, entrySMA, exitSMA, rsiPeriod,
overBoughtThreshold, overSoldThreshold)
# The if __name__ == '__main__' part is necessary if running on Windows.
if __name__ == '__main__':
# Load the bar feed from the CSV files.
feed = quandlfeed.Feed()
feed.addBarsFromCSV("ibm", "WIKI-IBM-2009-quandl.csv")
feed.addBarsFromCSV("ibm", "WIKI-IBM-2010-quandl.csv")
feed.addBarsFromCSV("ibm", "WIKI-IBM-2011-quandl.csv")
# Run the server.
server.serve(feed, parameters_generator(), "localhost", 5000)
import itertools
from pyalgotrade.barfeed import yahoofeed
from pyalgotrade.optimizer import server
def parameters_generator():
instrument = ["dia"]
entrySMA = list(range(150, 155))
exitSMA = list(range(5, 6))
rsiPeriod = list(range(2, 5))
overBoughtThreshold = list(range(88, 92))
overSoldThreshold = list(range(16, 20))
return itertools.product(instrument, entrySMA, exitSMA, rsiPeriod, overBoughtThreshold, overSoldThreshold)
# The if __name__ == '__main__' part is necessary if running on Windows.
if __name__ == '__main__':
# Load the feed from the CSV files.
feed = yahoofeed.Feed()
feed.addBarsFromCSV("dia", "dia-2009.csv")
feed.addBarsFromCSV("dia", "dia-2010.csv")
feed.addBarsFromCSV("dia", "dia-2011.csv")
# Run the server.
server.serve(feed, parameters_generator(), "localhost", 6000)
from pyalgotrade.barfeed import csvfeed
from pyalgotrade import bar
def parameters_generator():
instrument = ["btc"]
entrySMA = range(120, 155)
exitSMA = range(10, 15)
rsiPeriod = range(2, 4)
overBoughtThreshold = range(70, 90)
overSoldThreshold = range(19, 35)
initialAmount = [5000]
return itertools.product(instrument, entrySMA, exitSMA, rsiPeriod,
overBoughtThreshold, overSoldThreshold,
initialAmount)
# The if __name__ == '__main__' part is necessary if running on Windows.
if __name__ == '__main__':
instrument = "btc"
year = "2015"
# Load the feed from the CSV files.
barFeed = csvfeed.GenericBarFeed(bar.Frequency.MINUTE * 30)
barFeed.addBarsFromCSV(instrument, "30min-%s-%s.csv" % (instrument, year))
#feed = yahoofeed.Feed()
# feed.addBarsFromCSV("btc", "btc_all_daily.csv")
# Run the server.
server.serve(barFeed, parameters_generator(), "0.0.0.0", 5000)
def parameters_generator():
instrument = ["BTC"]
initialCash = [1000]
vwapWindowSize = range(89, 180, 1)
buyThreshold = map(lambda x: float(x) / 1000, range(5, 40, 1))
sellThreshold = map(lambda x: float(x) / 1000, range(5, 40, 1))
lenparams = len(sellThreshold) * len(buyThreshold) * len(vwapWindowSize)
return (lenparams,
itertools.product(instrument, initialCash, vwapWindowSize,
buyThreshold, sellThreshold))
# The if __name__ == '__main__' part is necessary if running on Windows.
if __name__ == '__main__':
instrument = "BTC"
year = "2016"
minutes = 30
# Load the feed from the CSV files.
barFeed = csvfeed.GenericBarFeed(bar.Frequency.MINUTE * 30)
barFeed.addBarsFromCSV(instrument,
"%smin-%s-%s.csv" % (minutes, instrument, year))
# Run the server.
lenp, params = parameters_generator()
print "Running %s variations" % lenp
server.serve(barFeed, params, "0.0.0.0", 5001)
