def create_simulation_parameters(year=2006,
start=None,
end=None,
capital_base=float("1.0e5"),
num_days=None,
emission_rate='daily',
data_frequency='daily'):
"""Construct a complete environment with reasonable defaults"""
if start is None:
start = datetime(year, 1, 1, tzinfo=pytz.utc)
if end is None:
if num_days:
trading.environment = trading.TradingEnvironment()
start_index = trading.environment.trading_days.searchsorted(start)
end = trading.environment.trading_days[start_index + num_days - 1]
else:
end = datetime(year, 12, 31, tzinfo=pytz.utc)
sim_params = trading.SimulationParameters(
period_start=start,
period_end=end,
capital_base=capital_base,
emission_rate=emission_rate,
)
return sim_params
def create_simulation_parameters(self,
start=None,
end=None,
capital_base=float("1.0e5"),
emission_rate=None,
data_frequency=None):
if emission_rate is None:
emission_rate = 'minute' if str(self.period) == 1 else 'daily'
if data_frequency is None:
data_frequency = 'minute' if str(self.period) == 1 else 'daily'
if start is None:
start = datareader.timetastic(self.start, datareader.pytz.utc)
if end is None:
end = datareader.timetastic(self.end, datareader.pytz.utc)
return trading.SimulationParameters(period_start=start,
period_end=end,
capital_base=capital_base,
emission_rate=emission_rate,
data_frequency=data_frequency)
self.atr_plot[sym]['loss'].append(-(atr*3)+sym_price)
self.day_count += 1
if __name__ == '__main__':
data = load_bars_from_yahoo(stocks=sym_list, indexes={}, start=start, end=end)
trend_trader = trend_trader()
results = trend_trader.run(data)
###########################################################################
# Generate metrics
print 'Generating Risk Report...........'
print 'Using S&P500 as benchmark........'
start = results.first_valid_index().replace(tzinfo=pytz.utc)
end = results.last_valid_index().replace(tzinfo=pytz.utc)
env = trading.SimulationParameters(start, end)
returns_risk = create_returns_from_list(results.returns, env)
algo_returns = RiskMetricsBase(start, end, returns_risk).algorithm_period_returns
benchmark_returns = RiskMetricsBase(start, end, returns_risk).benchmark_period_returns
excess_return = RiskMetricsBase(start, end, returns_risk).excess_return
algo_volatility = RiskMetricsBase(start, end, returns_risk).algorithm_volatility
benchmark_volatility = RiskMetricsBase(start, end, returns_risk).benchmark_volatility
sharpe = RiskMetricsBase(start, end, returns_risk).sharpe
sortino = RiskMetricsBase(start, end, returns_risk).sortino
information = RiskMetricsBase(start, end, returns_risk).information
beta = RiskMetricsBase(start, end, returns_risk).beta
alpha = RiskMetricsBase(start, end, returns_risk).alpha
max_drawdown = RiskMetricsBase(start, end, returns_risk).max_drawdown
print '---------Risk Metrics---------'