PandasTraderRunner

tradeexecutor.strategy.pandas_trader.runner.PandasTraderRunner class.

class PandasTraderRunner

Bases: StrategyRunner

A trading executor for Pandas math based algorithm.

__init__(*args, decide_trades, max_data_age=None, **kwargs)

Parameters

• decide_trades (TradeDecider) –

• max_data_age (Optional[timedelta]) –

Methods

__init__(*args, decide_trades[, max_data_age])
check_position_triggers(clock, state, ...)	Check stop loss/take profit for positions.
on_clock(clock, executor_universe, ...)	Run one strategy tick.
on_data_signal()
pretick_check(ts, universe)	Check the data looks more or less sane.
report_after_execution(clock, universe, ...)
report_after_sync_and_revaluation(clock, ...)
report_before_execution(clock, universe, ...)
report_strategy_thinking(clock, universe, ...)	Strategy runner subclass can fill in.
revalue_portfolio(ts, state, valuation_method)	Revalue portfolio based on the data.
setup_routing(universe)	Setups routing state for this cycle.
sync_portfolio(ts, universe, state, ...)	Adjust portfolio balances based on the external events.
tick(clock, universe, state, debug_details)	Perform the strategy main tick.

__init__(*args, decide_trades, max_data_age=None, **kwargs)

Parameters

• decide_trades (TradeDecider) –

• max_data_age (Optional[timedelta]) –

on_clock(clock, executor_universe, pricing_model, state, debug_details)

Run one strategy tick.

Parameters

• clock (datetime) –

• executor_universe (TradingStrategyUniverse) –

• pricing_model (PricingModel) –

• state (State) –

• debug_details (dict) –

Return type

List[TradeExecution]

pretick_check(ts, universe)

Check the data looks more or less sane.

Parameters

• ts (datetime) –

• universe (TradingStrategyUniverse) –