def test_short_strategy(self):
from_date = datetime(2012, 1, 1)
to_date = datetime(2012, 12, 31)
symbols = ['AZN.L', 'FRES.L', 'IAG.L']
init_marketdata(symbols, from_date, to_date)
sr = StrategyRunner('CDL3WHITESOLDIERS', 100, 3, 0,
0.02)(symbols, from_date, to_date)
self.assertAlmostEqual(295.808, sr.balance, 2)
def test_long_strategy(self):
from_date = datetime(2012, 1, 1)
to_date = datetime(2012, 1, 31)
symbols = ['BRBY.L', 'CNA.L', 'MGGT.L']
init_marketdata(symbols, from_date, to_date)
sr = StrategyRunner('CDL3LINESTRIKE', -100, 9, 1,
0.02)(symbols, from_date, to_date)
self.assertAlmostEqual(-353.443, sr.balance, 2)
def main(fname, from_date, to_date):
symbols = load_symbols(fname)
init_marketdata(symbols, from_date, to_date)
palg = talib_candlestick_funcs()
c = CandlestickPatternEvents(symbols, palg, from_date, to_date)()
diff_level = 0.02 # output patterns where up/down > diff_level
min_cnt = 5 # output patterns with > min_cnt events
output_results(c.average_changes, diff_level, min_cnt)
def test_CandlestickPatternEvents(self):
from_date = datetime(2012, 1, 1)
to_date = datetime(2012, 1, 31)
symbols = ['ABF.L', 'ADM.L']
init_marketdata(symbols, from_date, to_date)
palg = talib_candlestick_funcs()
c = CandlestickPatternEvents(symbols, palg, from_date, to_date)()
changes = list(c.average_changes)
self.assertEquals(20, len(changes))
self.assertEquals('CDLSPINNINGTOP:100', changes[19][0])
self.assertEquals(4, changes[19][1].cnt())
self.assertAlmostEquals(1.02994350282, changes[19][1].average('open')[-1])
def test_CandlestickPatternEvents(self):
from_date = datetime(2012, 1, 1)
to_date = datetime(2012, 1, 31)
symbols = ['ABF.L', 'ADM.L']
init_marketdata(symbols, from_date, to_date)
palg = talib_candlestick_funcs()
c = CandlestickPatternEvents(symbols, palg, from_date, to_date)()
changes = list(c.average_changes)
self.assertEquals(17, len(changes))
self.assertEquals('CDLSPINNINGTOP:100', changes[16][0])
self.assertEquals(3, changes[16][1].cnt())
self.assertAlmostEquals(1.02994350282,
changes[16][1].average('open')[-1])
def events_main(fname, from_date, to_date):
symbols = load_symbols(fname)
init_marketdata(symbols, from_date, to_date)
palg = talib_candlestick_funcs()
c = CandlestickPatternEvents(symbols, palg, from_date, to_date)()
diff_level = 0.02 # output patterns where up/down > diff_level
min_cnt = 10 # output patterns with > min_cnt events
average_changes = list(
filter_average_changes(c.average_changes, diff_level, min_cnt))
output_results(average_changes, [fname, from_date, to_date])
], txns, ['%s', '%s', '%s', '%f', '%f', '%f'])
def strategy_runner((outpath, symbols, from_date, to_date, strategy)):
sr = StrategyRunner(*strategy)(symbols, from_date, to_date)
output_transactions(
outpath,
(strategy[0], strategy[1], strategy[2], strategy[3], strategy[4]),
sr.txns)
return (strategy[0], strategy[1], strategy[2], strategy[3], strategy[4],
sr.balance)
def backtesting_main(fname, from_date, to_date, strategies, async=False):
symbols = load_symbols(fname)
init_marketdata(symbols, from_date, to_date)
strategies_cfg = load_strategies(strategies)
outpath = create_result_dir('backtesting')
pool = Pool(4)
res = pool.map(strategy_runner, [(outpath, symbols, from_date, to_date, x)
for x in strategies_cfg])
with open(os.path.join(outpath, 'backtesting.html'), 'w') as f:
create_table(f, [
'Pattern', 'Pattern params', 'Hold days', 'Buy side', 'Limit',
'Profit'
], res, ['%s', '%d', '%d', '%d', '%f', '%f'])
profitable = [x for x in res if x[5] > 1.0]
with open(os.path.join(outpath, 'profit.html'), 'w') as f:
def output_transactions(outpath, sparams, txns):
with open(os.path.join(outpath, 'txns_%s_%d_%d_%d_%d.html' % (sparams[0], sparams[1], sparams[2], sparams[3], sparams[4])), 'w') as f:
create_table(f, ['Symbol', 'Buy date', 'Sell date', 'Buy price', 'Sell prive', 'Profit'], txns, ['%s', '%s', '%s', '%f', '%f', '%f'])
def strategy_runner((outpath, symbols, from_date, to_date, strategy)):
sr = StrategyRunner(*strategy)(symbols, from_date, to_date)
output_transactions(outpath, (strategy[0], strategy[1], strategy[2], strategy[3], strategy[4]), sr.txns)
return (strategy[0], strategy[1], strategy[2], strategy[3], strategy[4], sr.balance)
def backtesting_main(fname, from_date, to_date, strategies, async=False):
symbols = load_symbols(fname)
init_marketdata(symbols, from_date, to_date)
strategies_cfg = load_strategies(strategies)
outpath = create_result_dir('backtesting')
pool = Pool(4)
res = pool.map(strategy_runner, [(outpath, symbols, from_date, to_date, x) for x in strategies_cfg])
with open(os.path.join(outpath, 'backtesting.html'), 'w') as f:
create_table(f, ['Pattern', 'Pattern params', 'Hold days', 'Buy side', 'Limit', 'Profit'], res, ['%s', '%d', '%d', '%d', '%f', '%f'])
profitable = [x for x in res if x[5] > 1.0]
with open(os.path.join(outpath, 'profit.html'), 'w') as f:
create_table(f, ['Pattern', 'Pattern params', 'Hold days', 'Buy side', 'Limit', 'Profit'], profitable, ['%s', '%d', '%d', '%d', '%f', '%f'])
if __name__ == '__main__':