本文整理汇总了Python中zipline.utils.factory.create_returns_from_list函数的典型用法代码示例。如果您正苦于以下问题：Python create_returns_from_list函数的具体用法？Python create_returns_from_list怎么用？Python create_returns_from_list使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了create_returns_from_list函数的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: init_instance_fixtures
def init_instance_fixtures(self):
super(TestRisk, self).init_instance_fixtures()
self.start_session = pd.Timestamp("2006-01-01", tz='UTC')
self.end_session = self.trading_calendar.minute_to_session_label(
pd.Timestamp("2006-12-31", tz='UTC'),
direction="previous"
)
self.sim_params = SimulationParameters(
start_session=self.start_session,
end_session=self.end_session,
trading_calendar=self.trading_calendar,
)
self.algo_returns = factory.create_returns_from_list(
RETURNS,
self.sim_params
)
self.benchmark_returns = factory.create_returns_from_list(
BENCHMARK,
self.sim_params
)
self.metrics = ClassicRiskMetrics.risk_report(
algorithm_returns=self.algo_returns,
benchmark_returns=self.benchmark_returns,
algorithm_leverages=pd.Series(0.0, index=self.algo_returns.index)
)示例2: init_instance_fixtures
def init_instance_fixtures(self):
super(TestRisk, self).init_instance_fixtures()
self.start_session = pd.Timestamp("2006-01-01", tz='UTC')
self.end_session = self.trading_calendar.minute_to_session_label(
pd.Timestamp("2006-12-31", tz='UTC'),
direction="previous"
)
self.sim_params = SimulationParameters(
start_session=self.start_session,
end_session=self.end_session,
trading_calendar=self.trading_calendar,
)
self.algo_returns = factory.create_returns_from_list(
RETURNS,
self.sim_params
)
self.benchmark_returns = factory.create_returns_from_list(
BENCHMARK,
self.sim_params
)
self.metrics = risk.RiskReport(
self.algo_returns,
self.sim_params,
benchmark_returns=self.benchmark_returns,
trading_calendar=self.trading_calendar,
treasury_curves=self.env.treasury_curves,
)示例3: test_drawdown
def test_drawdown(self):
returns = factory.create_returns_from_list([1.0, -0.5, 0.8, 0.17, 1.0, -0.1, -0.45], self.sim_params)
# 200, 100, 180, 210.6, 421.2, 379.8, 208.494
metrics = risk.RiskMetricsPeriod(
returns.index[0], returns.index[-1], returns, env=self.env, benchmark_returns=self.env.benchmark_returns
)
self.assertEqual(metrics.max_drawdown, 0.505)示例4: init_instance_fixtures
def init_instance_fixtures(self):
super(TestRisk, self).init_instance_fixtures()
start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_date = datetime.datetime(
year=2006, month=12, day=29, tzinfo=pytz.utc)
self.sim_params = SimulationParameters(
period_start=start_date,
period_end=end_date,
trading_schedule=self.trading_schedule,
)
self.algo_returns_06 = factory.create_returns_from_list(
answer_key.ALGORITHM_RETURNS.values,
self.sim_params
)
self.cumulative_metrics_06 = risk.RiskMetricsCumulative(
self.sim_params,
treasury_curves=self.env.treasury_curves,
trading_schedule=self.trading_schedule,
)
for dt, returns in answer_key.RETURNS_DATA.iterrows():
self.cumulative_metrics_06.update(dt,
returns['Algorithm Returns'],
returns['Benchmark Returns'],
0.0)示例5: init_instance_fixtures
def init_instance_fixtures(self):
super(TestRisk, self).init_instance_fixtures()
start_session = pd.Timestamp("2006-01-01", tz='UTC')
end_session = pd.Timestamp("2006-12-29", tz='UTC')
self.sim_params = SimulationParameters(
start_session=start_session,
end_session=end_session,
trading_calendar=self.trading_calendar,
)
self.algo_returns = factory.create_returns_from_list(
RETURNS,
self.sim_params
)
self.cumulative_metrics = risk.RiskMetricsCumulative(
self.sim_params,
treasury_curves=self.env.treasury_curves,
trading_calendar=self.trading_calendar,
)
for dt, returns in self.algo_returns.iteritems():
self.cumulative_metrics.update(
dt,
returns,
BENCHMARK_BASE,
0.0
)示例6: setUp
def setUp(self):
start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_date = datetime.datetime(
year=2006, month=12, day=29, tzinfo=pytz.utc)
self.sim_params = SimulationParameters(
period_start=start_date,
period_end=end_date
)
self.algo_returns_06 = factory.create_returns_from_list(
answer_key.ALGORITHM_RETURNS.values,
self.sim_params
)
self.cumulative_metrics_06 = risk.RiskMetricsCumulative(
self.sim_params)
for dt, returns in answer_key.RETURNS_DATA.iterrows():
self.cumulative_metrics_06.update(dt,
returns['Algorithm Returns'],
returns['Benchmark Returns'])示例7: init_instance_fixtures
def init_instance_fixtures(self):
super(TestRisk, self).init_instance_fixtures()
start_session = pd.Timestamp("2006-01-01", tz='UTC')
end_session = pd.Timestamp("2006-12-29", tz='UTC')
self.sim_params = SimulationParameters(
start_session=start_session,
end_session=end_session,
trading_calendar=self.trading_calendar,
)
self.algo_returns_06 = factory.create_returns_from_list(
answer_key.ALGORITHM_RETURNS.values,
self.sim_params
)
self.cumulative_metrics_06 = risk.RiskMetricsCumulative(
self.sim_params,
treasury_curves=self.env.treasury_curves,
trading_calendar=self.trading_calendar,
)
for dt, returns in answer_key.RETURNS_DATA.iterrows():
self.cumulative_metrics_06.update(dt,
returns['Algorithm Returns'],
returns['Benchmark Returns'],
0.0)示例8: test_factory
def test_factory(self):
returns = [0.1] * 100
r_objects = factory.create_returns_from_list(returns, self.sim_params)
self.assertLessEqual(
r_objects.index[-1],
pd.Timestamp('2006-12-31', tz='UTC')
)示例9: test_drawdown
def test_drawdown(self):
returns = factory.create_returns_from_list(
[1.0, -0.5, 0.8, .17, 1.0, -0.1, -0.45], self.sim_params)
#200, 100, 180, 210.6, 421.2, 379.8, 208.494
metrics = risk.RiskMetricsBatch(returns[0].date,
returns[-1].date,
returns)
self.assertEqual(metrics.max_drawdown, 0.505)示例10: setUp
def setUp(self):
start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_date = datetime.datetime(
year=2006, month=12, day=31, tzinfo=pytz.utc)
self.benchmark_returns, self.treasury_curves = \
factory.load_market_data()
self.trading_env = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=start_date,
period_end=end_date
)
self.onesec = datetime.timedelta(seconds=1)
self.oneday = datetime.timedelta(days=1)
self.tradingday = datetime.timedelta(hours=6, minutes=30)
self.dt = datetime.datetime.utcnow()
self.algo_returns_06 = factory.create_returns_from_list(
RETURNS,
self.trading_env
)
self.metrics_06 = risk.RiskReport(
self.algo_returns_06,
self.trading_env
)
start_08 = datetime.datetime(
year=2008,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_08 = datetime.datetime(
year=2008,
month=12,
day=31,
tzinfo=pytz.utc
)
self.trading_env08 = TradingEnvironment(
self.benchmark_returns,
self.treasury_curves,
period_start=start_08,
period_end=end_08
)示例11: init_instance_fixtures
def init_instance_fixtures(self):
super(TestRisk, self).init_instance_fixtures()
start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_date = datetime.datetime(
year=2006, month=12, day=31, tzinfo=pytz.utc)
self.sim_params = SimulationParameters(
period_start=start_date,
period_end=end_date,
trading_schedule=self.trading_schedule,
)
self.algo_returns_06 = factory.create_returns_from_list(
RETURNS,
self.sim_params
)
self.benchmark_returns_06 = \
answer_key.RETURNS_DATA['Benchmark Returns']
self.metrics_06 = risk.RiskReport(
self.algo_returns_06,
self.sim_params,
benchmark_returns=self.benchmark_returns_06,
trading_schedule=self.trading_schedule,
treasury_curves=self.env.treasury_curves,
)
start_08 = datetime.datetime(
year=2008,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_08 = datetime.datetime(
year=2008,
month=12,
day=31,
tzinfo=pytz.utc
)
self.sim_params08 = SimulationParameters(
period_start=start_08,
period_end=end_08,
trading_schedule=self.trading_schedule,
)示例12: setUp
def setUp(self):
start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_date = datetime.datetime(
year=2006, month=12, day=31, tzinfo=pytz.utc)
self.sim_params = SimulationParameters(
period_start=start_date,
period_end=end_date,
env=self.env,
)
self.algo_returns_06 = factory.create_returns_from_list(
RETURNS,
self.sim_params
)
self.benchmark_returns_06 = \
answer_key.RETURNS_DATA['Benchmark Returns']
self.metrics_06 = risk.RiskReport(
self.algo_returns_06,
self.sim_params,
benchmark_returns=self.benchmark_returns_06,
env=self.env,
)
start_08 = datetime.datetime(
year=2008,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_08 = datetime.datetime(
year=2008,
month=12,
day=31,
tzinfo=pytz.utc
)
self.sim_params08 = SimulationParameters(
period_start=start_08,
period_end=end_08,
env=self.env,
)示例13: setUp
def setUp(self):
start_date = datetime.datetime(
year=2006,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_date = datetime.datetime(
year=2006, month=12, day=31, tzinfo=pytz.utc)
self.sim_params = SimulationParameters(
period_start=start_date,
period_end=end_date
)
self.onesec = datetime.timedelta(seconds=1)
self.oneday = datetime.timedelta(days=1)
self.tradingday = datetime.timedelta(hours=6, minutes=30)
self.dt = datetime.datetime.utcnow()
self.algo_returns_06 = factory.create_returns_from_list(
RETURNS,
self.sim_params
)
self.metrics_06 = risk.RiskReport(
self.algo_returns_06,
self.sim_params
)
start_08 = datetime.datetime(
year=2008,
month=1,
day=1,
hour=0,
minute=0,
tzinfo=pytz.utc)
end_08 = datetime.datetime(
year=2008,
month=12,
day=31,
tzinfo=pytz.utc
)
self.sim_params08 = SimulationParameters(
period_start=start_08,
period_end=end_08
)示例14: test_sharpe_value_when_null
def test_sharpe_value_when_null(self):
# Sharpe is displayed as '0.0' instead of np.nan
null_returns = factory.create_returns_from_list(
[0.0]*251,
self.sim_params
)
test_period = RiskMetricsPeriod(
start_session=self.start_session,
end_session=self.end_session,
returns=null_returns,
benchmark_returns=self.benchmark_returns,
trading_calendar=self.trading_calendar,
)
assert test_period.sharpe == 0.0示例15: test_sharpe_value_when_null
def test_sharpe_value_when_null(self):
# Sharpe is displayed as '0.0' instead of np.nan
null_returns = factory.create_returns_from_list(
[0.0]*251,
self.sim_params
)
test_period = ClassicRiskMetrics.risk_metric_period(
start_session=self.start_session,
end_session=self.end_session,
algorithm_returns=null_returns,
benchmark_returns=self.benchmark_returns,
algorithm_leverages=pd.Series(
0.0,
index=self.algo_returns.index
)
)
self.assertEqual(test_period['sharpe'], 0.0)