本文整理汇总了Python中zipline.finance.trading.TradingEnvironment.capital_base方法的典型用法代码示例。如果您正苦于以下问题:Python TradingEnvironment.capital_base方法的具体用法?Python TradingEnvironment.capital_base怎么用?Python TradingEnvironment.capital_base使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类zipline.finance.trading.TradingEnvironment
的用法示例。
在下文中一共展示了TradingEnvironment.capital_base方法的1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: test_tracker
# 需要导入模块: from zipline.finance.trading import TradingEnvironment [as 别名]
# 或者: from zipline.finance.trading.TradingEnvironment import capital_base [as 别名]
def test_tracker(self, parameter_comment, days_to_delete):
"""
@days_to_delete - configures which days in the data set we should
remove, used for ensuring that we still return performance messages
even when there is no data.
"""
# This date range covers Columbus day,
# however Columbus day is not a market holiday
#
# October 2008
# Su Mo Tu We Th Fr Sa
# 1 2 3 4
# 5 6 7 8 9 10 11
# 12 13 14 15 16 17 18
# 19 20 21 22 23 24 25
# 26 27 28 29 30 31
start_dt = datetime.datetime(year=2008,
month=10,
day=9,
tzinfo=pytz.utc)
end_dt = datetime.datetime(year=2008,
month=10,
day=16,
tzinfo=pytz.utc)
trade_count = 6
sid = 133
price = 10.1
price_list = [price] * trade_count
volume = [100] * trade_count
trade_time_increment = datetime.timedelta(days=1)
benchmark_returns, treasury_curves = \
factory.load_market_data()
trading_environment = TradingEnvironment(
benchmark_returns,
treasury_curves,
period_start=start_dt,
period_end=end_dt
)
trade_history = factory.create_trade_history(
sid,
price_list,
volume,
trade_time_increment,
trading_environment,
source_id="factory1"
)
sid2 = 134
price2 = 12.12
price2_list = [price2] * trade_count
trade_history2 = factory.create_trade_history(
sid2,
price2_list,
volume,
trade_time_increment,
trading_environment,
source_id="factory2"
)
# 'middle' start of 3 depends on number of days == 7
middle = 3
# First delete from middle
if days_to_delete.middle:
del trade_history[middle:(middle + days_to_delete.middle)]
del trade_history2[middle:(middle + days_to_delete.middle)]
# Delete start
if days_to_delete.start:
del trade_history[:days_to_delete.start]
del trade_history2[:days_to_delete.start]
# Delete from end
if days_to_delete.end:
del trade_history[-days_to_delete.end:]
del trade_history2[-days_to_delete.end:]
trading_environment.first_open = \
trading_environment.calculate_first_open()
trading_environment.last_close = \
trading_environment.calculate_last_close()
trading_environment.capital_base = 1000.0
trading_environment.frame_index = [
'sid',
'volume',
'dt',
'price',
'changed']
perf_tracker = perf.PerformanceTracker(
trading_environment
)
events = date_sorted_sources(trade_history, trade_history2)
events = [self.event_with_txn(event, trade_history[0].dt)
for event in events]
#.........这里部分代码省略.........