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()
def simulate():
'''
strategy_params=dict(top=60,btm=40,rsi=14,average=111,duration=5))
+--------+-----+-------+------+---------+---------+---------+---------+
| _score | cnt | w_pct | pr | pnl | mtm_pnl | max_equ | max_dd |
+--------+-----+-------+------+---------+---------+---------+---------+
| 5.70 | 97 | 0.61 | 1.25 | 7163.57 | 7163.57 | 7608.81 | 1129.33 |
+--------+-----+-------+------+---------+---------+---------+---------+
equity curve = 570x.png
strategy_params=dict(top=60,btm=40,rsi=12,average=180,duration=7))
+--------+-----+-------+------+----------+----------+----------+---------+
| _score | cnt | w_pct | pr | pnl | mtm_pnl | max_equ | max_dd |
+--------+-----+-------+------+----------+----------+----------+---------+
| 7.56 | 106 | 0.67 | 1.22 | 11139.79 | 11139.79 | 11158.79 | 1330.16 |
+--------+-----+-------+------+----------+----------+----------+---------+
equity curve = 756x.png
'''
m = RSIStrategy(name='rsi2_spy',
strategy_params=dict(top=60,
btm=40,
rsi=12,
average=180,
duration=7))
s = Simulator()
s.add_strategy(m)
s.run(DataFeedList(['SPY.csv'], data_type='D'))
s.write('rsi2_SPY_%s' % datetime.now().strftime("%Y%m%d"))
def simulate_AAPL_SPY():
m = RSIStrategy(name='rsi2_aapl_spy',
strategy_params=dict(top=60,
btm=40,
rsi=12,
average=180,
duration=7))
s = Simulator()
s.add_strategy(m)
s.run(DataFeedList(['AAPL.csv', 'SPY.csv'], data_type='D'))
s.write('rsi2_AAPL_SPY_%s' % datetime.now().strftime("%Y%m%d"))
def simulate_SPY_AAPL_composite():
'''
test to make sure that a composite file (AAPL and SPY combined)
is the same as the individuals (AAPL.csv and SPY.csv separately)
'''
m = RSIStrategy(name='rsi2_spy_v_aapl',
strategy_params=dict(top=60,
btm=40,
rsi=12,
average=180,
duration=7))
s = Simulator()
s.add_strategy(m)
s.run(DataFeedList(['SPY_AAPL.csv'], data_type='D'))
s.write('rsi2_SPYvAAPL_%s' % datetime.now().strftime("%Y%m%d"))
from Treadmill import Treadmill from RetraceStrategy import RetraceStrategy from DataFeed import DataFeedList ''' testing the EOD flag making sure that treadmill output is consistent across multiple datafeed versus if the datafeed where combined into single data file ''' t = Treadmill() t.strategy_class = RetraceStrategy t.strategy_params = dict(average=141,momentum=21,duration=15) #t.data_feed = DataFeedList(['daily.SPY.csv','daily.SPY.csv'],data_type='D') t.data_feed = DataFeedList(['top.SPY.csv','bottom.SPY.csv'],data_type='D') t.reset_on_EOD = False t.run(20)
from Simulator import Simulator
from RetraceStrategy import RetraceStrategy
from DataFeed import DataFeedList
if __name__ == '__main__':
r = RetraceStrategy('tiger',
strategy_params=dict(average=150,
duration=20,
momentum=40))
d = DataFeedList(['tiger_data.csv'], data_type='D')
s = Simulator()
s.add_strategy(r)
s.run(d)
s.write('tiger_150_20_40')
s.show()
from Simulator import Simulator
from RetraceStrategy import RetraceStrategy
from DataFeed import DataFeedList
if __name__ == '__main__':
r = RetraceStrategy('retrace_mini',
strategy_params=dict(average=150,
duration=20,
momentum=65))
d = DataFeedList(['SPY.csv'], data_type='D')
s = Simulator()
s.add_strategy(r)
s.run(d)
s.write('retrace_spy_universe')
#data_feed = DataFeedList(['daily.SPY.csv','daily.SPY.csv'],data_type='D')
data_feed = DataFeedList(['daily.SPY.csv','daily.SPY.csv'],data_type='D')
s.run(data_feed)
s.write('R2')
## testing DataFeedBar serial files
strat = MStrategy2('M2',strategy_params = dict(length=20,duration=15))
#strat.capture_data = True
s.add_strategy(strat)
s.reset_on_EOD = False
data_feed = DataFeedList(['20081210.SPY.1min.csv','20081211.SPY.1min.csv','20081212.SPY.1min.csv'],data_type='B')
s.run(data_feed)
#strat.dump_data().to_csv('M2_data_dump.csv')
s.write('M2')
'''
## testing DataFeedIntraday serial files
strat = MStrategy2('M2', strategy_params=dict(length=30, duration=50))
#strat.capture_data = True
s.add_strategy(strat)
s.reset_on_EOD = False
#data_feed = DataFeedList(['20081210.SPY.30s.csv','20081211.SPY.30s.csv'],data_type='I')
#data_feed = DataFeedList(['combo.SPY.30s.csv'],data_type='I')
data_feed = DataFeedList(
['20081210.SPY.30s.csv', '20081211.SPY.30s.csv', '20081212.SPY.30s.csv'],
data_type='I')
s.run(data_feed)
#strat.dump_data().to_csv('M2_data_dump.csv')
s.write('MI2')
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 Simulator import Simulator
from RetraceStrategy import RetraceStrategy
from DataFeed import DataFeedList
if __name__ == '__main__':
r = RetraceStrategy('retrace_mini_universe',strategy_params=dict(average=150,duration=20,momentum=65))
d = DataFeedList(['mini_data.csv'],data_type='D')
s = Simulator()
s.add_strategy(r)
s.run(d)
s.write('retrace_mini_universe')