Esempio n. 1
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def test_optimizer2():
    optimizer = Optimizer()
    run_id = 0

    ## set population size
    optimizer.size = 40
    optimizer.max_generations = 5

    ## if not given: outfile will default to using the strategy name
    ## optimizer.outfile ='retrace_optimized.xls'

    ## parameter space to search over
    ## 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)
    ]

    optimizer.add_parameters(param_list)

    while not optimizer.converged():
        params_set = optimizer.generate_set()
        for strategy_params in params_set:
            log.debug('Testing: %s' % pprint.pformat(strategy_params))
            sim_stats = test_retrace_strategy(strategy_params, run_id)
            optimizer.score(sim_stats, run_id)
            run_id += 1
        optimizer.dump()

    optimizer.write()
Esempio n. 2
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def test_optimizer3():
    optimizer = Optimizer()
    run_id = 0

    ## set population size
    optimizer.size = 40
    optimizer.max_generations = 5
    optimizer.outfile = 'triple_optimized.xls'

    ## parameter space to search over
    ## mo1 = short term momentum crossover
    ## mo2 = medium term mo filter
    ## mo3 = long term mo filter
    ## duration = trade holding period

    param_list = [
        dict(name='mo1', min_val=5, max_val=50, steps=32, converter=int),
        dict(name='mo2', min_val=60, max_val=100, steps=32, converter=int),
        dict(name='mo3', min_val=110, max_val=200, steps=32, converter=int),
        dict(name='duration', min_val=10, max_val=50, steps=16, converter=int)
    ]

    optimizer.add_parameters(param_list)

    while not optimizer.converged():
        params_set = optimizer.generate_set()
        for strategy_params in params_set:
            log.debug('Testing: %s' % pprint.pformat(strategy_params))
            sim_stats = test_triple_strategy(strategy_params, run_id)
            optimizer.score(sim_stats, run_id)
            run_id += 1
        optimizer.dump()

    optimizer.write()
Esempio n. 3
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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()
Esempio n. 4
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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)