def optimize(): optimizer = Optimizer() optimizer.strategy_class = RSIStrategy #optimizer.data_feed = DataFeedList(['20081210.SPY.1m.csv','20081211.SPY.1min.csv','20081212.SPY.1min.csv'],data_type='B') #optimizer.data_feed = DataFeedList(['20081210.SPY.30s.csv','20081211.SPY.30s.csv','20081212.SPY.30s.csv'],data_type='I') optimizer.data_feed = DataFeedList(['SPY.csv'], data_type='D') ## set population size optimizer.size = 40 optimizer.max_generations = 50 optimizer.outfile = '%s_%s.xls' % (__file__[:-3], datetime.now().strftime("%Y%m%d")) optimizer.tolerance = 0.01 #optimizer.reset_on_EOD = False ## parameter space to search over ## rsi = rsi length ## top/btm = rsi buy sell thresholds ## average(optional) trend filter ## duration = trade duration optimizer.add_parameter( dict(name='rsi', min_val=10, max_val=40, steps=16, converter=int)) optimizer.add_parameter( dict(name='top', min_val=60, max_val=80, steps=4, converter=int)) optimizer.add_parameter( dict(name='btm', min_val=20, max_val=40, steps=4, converter=int)) optimizer.add_parameter( dict(name='average', min_val=20, max_val=200, steps=64, converter=int)) optimizer.add_parameter( dict(name='duration', min_val=5, max_val=20, steps=8, converter=int)) optimizer.run()
from RetraceStrategy import RetraceStrategy from DataFeed import DataFeedDaily from Optimizer import Optimizer if __name__ == '__main__': optimizer = Optimizer() optimizer.strategy_class = RetraceStrategy # optimizer.data_feed = DataFeedDaily('daily.SPY.csv') optimizer.data_feed = DataFeedDaily('SPY.csv') ## set population size optimizer.size = 40 optimizer.max_generations = 50 optimizer.outfile = 'optimize_retrace3.xls' optimizer.reset_on_EOD = True ## parameter space to search over ## strategy_params for RetraceStrategy = dict(average,momentum,duration) ## momentum = entry momentum crossover ## average = moving average filter ## duration = trade holding period param_list = [ dict(name='momentum', min_val=30, max_val=50, steps=16, converter=int), dict(name='average', min_val=70, max_val=120, steps=32, converter=int), dict(name='duration', min_val=10, max_val=20, steps=8, converter=int) ] for p in param_list: optimizer.add_parameter(p)
from RSIStrategy import RSIStrategy from DataFeed import DataFeedList from Optimizer import Optimizer from datetime import datetime if __name__ == '__main__': optimizer = Optimizer() optimizer.strategy_class = RSIStrategy #optimizer.data_feed = DataFeedList(['20081210.SPY.1m.csv','20081211.SPY.1min.csv','20081212.SPY.1min.csv'],data_type='B') #optimizer.data_feed = DataFeedList(['20081210.SPY.30s.csv','20081211.SPY.30s.csv','20081212.SPY.30s.csv'],data_type='I') optimizer.data_feed = DataFeedList(['SPY.csv'], data_type='D') ## set population size optimizer.size = 40 optimizer.max_generations = 50 optimizer.outfile = '%s_%s.xls' % (__file__[:-3], datetime.now().strftime("%Y%m%d_%H%M")) optimizer.tolerance = 0.01 #optimizer.reset_on_EOD = False ## parameter space to search over ## rsi = rsi length ## top/btm = rsi buy sell thresholds ## average(optional) trend filter ## duration = trade duration optimizer.add_parameter( dict(name='rsi', min_val=10, max_val=40, steps=16, converter=int)) optimizer.add_parameter( dict(name='top', min_val=60, max_val=80, steps=4, converter=int))
from RetraceStrategy import RetraceStrategy from DataFeed import DataFeedDaily from Optimizer import Optimizer if __name__ == '__main__': optimizer = Optimizer() optimizer.strategy_class = RetraceStrategy # optimizer.data_feed = DataFeedDaily('daily.SPY.csv') optimizer.data_feed = DataFeedDaily('mini_data.csv') ## set population size optimizer.size = 40 optimizer.max_generations = 50 optimizer.outfile = 'retrace_mini_opz.xls' optimizer.reset_on_EOD = True ## parameter space to search over ## strategy_params for RetraceStrategy = dict(average,momentum,duration) ## momentum = entry momentum crossover ## average = moving average filter ## duration = trade holding period param_list = [dict(name='momentum',min_val=10,max_val=100,steps=32,converter=int), dict(name='average',min_val=20,max_val=200,steps=32,converter=int), dict(name='duration',min_val=10,max_val=50,steps=16,converter=int) ] for p in param_list: