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WIP: Five Minute bars and FiveMinuteSimulationClock
This commit is contained in:
Conner Fromknecht
+41
-16
@@ -133,7 +133,10 @@ from catalyst.utils.security_list import SecurityList
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import catalyst.protocol
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from catalyst.sources.requests_csv import PandasRequestsCSV
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from catalyst.gens.sim_engine import MinuteSimulationClock
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from catalyst.gens.sim_engine import (
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MinuteSimulationClock,
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FiveMinuteSimulationClock,
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)
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from catalyst.sources.benchmark_source import BenchmarkSource
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from catalyst.catalyst_warnings import ZiplineDeprecationWarning
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@@ -170,7 +173,7 @@ class TradingAlgorithm(object):
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algo_filename : str, optional
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The filename for the algoscript. This will be used in exception
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tracebacks. default: '<string>'.
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data_frequency : {'daily', 'minute'}, optional
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data_frequency : {'daily', '5-minute', 'minute'}, optional
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The duration of the bars.
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instant_fill : bool, optional
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Whether to fill orders immediately or on next bar. default: False
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@@ -223,7 +226,7 @@ class TradingAlgorithm(object):
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script : str
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Algoscript that contains initialize and
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handle_data function definition.
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data_frequency : {'daily', 'minute'}
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data_frequency : {'daily', '5-minute', 'minute'}
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The duration of the bars.
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capital_base : float <default: 1.0e5>
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How much capital to start with.
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@@ -449,7 +452,7 @@ class TradingAlgorithm(object):
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self._in_before_trading_start = True
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with handle_non_market_minutes(data) if \
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self.data_frequency == "minute" else ExitStack():
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self.data_frequency in ('minute', '5-minute') else ExitStack():
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self._before_trading_start(self, data)
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self._in_before_trading_start = False
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@@ -505,10 +508,11 @@ class TradingAlgorithm(object):
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market_closes = trading_o_and_c['market_close']
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minutely_emission = False
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if self.sim_params.data_frequency == 'minute':
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if self.sim_params.data_frequency in set(('minute', '5-minute')):
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market_opens = trading_o_and_c['market_open']
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minutely_emission = self.sim_params.emission_rate == "minute"
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minutely_emission = self.sim_params.emission_rate in \
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set(('minute', '5-minute'))
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else:
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# in daily mode, we want to have one bar per session, timestamped
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# as the last minute of the session.
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@@ -528,10 +532,19 @@ class TradingAlgorithm(object):
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# FIXME generalize these values
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before_trading_start_minutes = days_at_time(
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self.sim_params.sessions,
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time(8, 45),
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"US/Eastern"
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time(0, 0),
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'UTC',
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)
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if self.sim_params.data_frequency == '5-minute':
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return FiveMinuteSimulationClock(
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self.sim_params.sessions,
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execution_opens,
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execution_closes,
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before_trading_start_minutes,
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minute_emission=minutely_emission,
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)
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return MinuteSimulationClock(
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self.sim_params.sessions,
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execution_opens,
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@@ -660,8 +673,11 @@ class TradingAlgorithm(object):
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# Assume data is daily if timestamp times are
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# standardized, otherwise assume minute bars.
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times = data.major_axis.time
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if np.all(times == times[0]):
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time_count = times.nunique()
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if time_count == 1:
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self.sim_params.data_frequency = 'daily'
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elif time_count == 288:
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self.sim_params.data_frequency = '5-minute'
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else:
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self.sim_params.data_frequency = 'minute'
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@@ -683,6 +699,8 @@ class TradingAlgorithm(object):
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if self.sim_params.data_frequency == 'daily':
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equity_reader_arg = 'equity_daily_reader'
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elif self.sim_params.data_frequency == '5-minute':
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equity_daily_reader = 'equity_5_minute_reader'
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elif self.sim_params.data_frequency == 'minute':
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equity_reader_arg = 'equity_minute_reader'
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equity_reader = PanelBarReader(
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@@ -926,9 +944,9 @@ class TradingAlgorithm(object):
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The arena from the simulation parameters. This will normally
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be ``'backtest'`` but some systems may use this distinguish
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live trading from backtesting.
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data_frequency : {'daily', 'minute'}
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data_frequency : {'daily', '5-minute', 'minute'}
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data_frequency tells the algorithm if it is running with
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daily data or minute data.
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daily, minute, or five-minute mode.
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start : datetime
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The start date for the simulation.
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end : datetime
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@@ -1102,12 +1120,19 @@ class TradingAlgorithm(object):
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'date_rule. You should use keyword argument '
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'time_rule= when calling schedule_function without '
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'specifying a date_rule', stacklevel=3)
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freq = self.sim_params.data_frequency
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date_rule = date_rule or date_rules.every_day()
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time_rule = ((time_rule or time_rules.every_minute())
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if self.sim_params.data_frequency == 'minute' else
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# If we are in daily mode the time_rule is ignored.
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time_rules.every_minute())
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if freq is 'daily':
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# ignore time rule in daily mode
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time_rule = time_rules.every_minute()
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else:
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# use provided time rule or default to every minute or 5 minutes
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# based on desired data frequency.
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time_rule = time_rule or (time_rules.every_5_minutes()
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if freq is '5-minute' else
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time_rules.every_minute())
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# Check the type of the algorithm's schedule before pulling calendar
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# Note that the ExchangeTradingSchedule is currently the only
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@@ -1782,7 +1807,7 @@ class TradingAlgorithm(object):
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@data_frequency.setter
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def data_frequency(self, value):
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assert value in ('daily', 'minute')
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assert value in ('daily', '5-minute', 'minute')
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self.sim_params.data_frequency = value
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@api_method
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