ExecutionLoop

tradeexecutor.cli.loop.ExecutionLoop class.

class ExecutionLoop

Bases: object

Live or backtesting trade execution loop.

__init__(*ignore, name, command_queue, execution_model, sync_method, approval_model, pricing_model_factory, valuation_model_factory, store, client, strategy_factory, cycle_duration, stats_refresh_frequency, max_data_delay=None, reset=False, max_cycles=None, debug_dump_file=None, backtest_start=None, backtest_end=None, backtest_setup=None, backtest_stop_loss_time_bucket=None, tick_offset=datetime.timedelta(0), trade_immediately=False)

See main.py for details.

Parameters

• name (str) –

• command_queue (Queue) –

• execution_model (ExecutionModel) –

• sync_method (Callable[[Portfolio, datetime, List[AssetIdentifier]], List[ReserveUpdateEvent]]) –

• approval_model (ApprovalModel) –

• pricing_model_factory (Callable[[ExecutionModel, StrategyExecutionUniverse, RoutingModel], PricingModel]) –

• valuation_model_factory (ValuationModelFactory) –

• store (StateStore) –

• client (Optional[Client]) –

• strategy_factory (Callable) –

• cycle_duration (CycleDuration) –

• stats_refresh_frequency (timedelta) –

• max_data_delay (Optional[timedelta]) –

• max_cycles (Optional[int]) –

• debug_dump_file (Optional[Path]) –

• backtest_start (Optional[datetime]) –

• backtest_end (Optional[datetime]) –

• backtest_setup (Optional[Callable[[State], None]]) –

• backtest_stop_loss_time_bucket (Optional[TimeBucket]) –

• tick_offset (timedelta) –

Methods

__init__(*ignore, name, command_queue, ...)	See main.py for details.
init_execution_model()
init_state()	Initialize the state for this run.
run()	The main loop of trade executor.
run_backtest(state)	Backtest loop.
run_backtest_stop_loss_checks(start_ts, ...)	Generate stop loss price checks.
run_live(state)	Run live trading cycle.
tick(unrounded_timestamp, state, cycle, live)	Run one trade execution tick.
update_position_valuations(clock, state, ...)	Revalue positions and update statistics.
warm_up_backtest()	Load backtesting trading universe.

__init__(*ignore, name, command_queue, execution_model, sync_method, approval_model, pricing_model_factory, valuation_model_factory, store, client, strategy_factory, cycle_duration, stats_refresh_frequency, max_data_delay=None, reset=False, max_cycles=None, debug_dump_file=None, backtest_start=None, backtest_end=None, backtest_setup=None, backtest_stop_loss_time_bucket=None, tick_offset=datetime.timedelta(0), trade_immediately=False)

See main.py for details.

Parameters

• name (str) –

• command_queue (Queue) –

• execution_model (ExecutionModel) –

• sync_method (Callable[[Portfolio, datetime, List[AssetIdentifier]], List[ReserveUpdateEvent]]) –

• approval_model (ApprovalModel) –

• pricing_model_factory (Callable[[ExecutionModel, StrategyExecutionUniverse, RoutingModel], PricingModel]) –

• valuation_model_factory (ValuationModelFactory) –

• store (StateStore) –

• client (Optional[Client]) –

• strategy_factory (Callable) –

• cycle_duration (CycleDuration) –

• stats_refresh_frequency (timedelta) –

• max_data_delay (Optional[timedelta]) –

• max_cycles (Optional[int]) –

• debug_dump_file (Optional[Path]) –

• backtest_start (Optional[datetime]) –

• backtest_end (Optional[datetime]) –

• backtest_setup (Optional[Callable[[State], None]]) –

• backtest_stop_loss_time_bucket (Optional[TimeBucket]) –

• tick_offset (timedelta) –

init_state()

Initialize the state for this run.

Return type

State

tick(unrounded_timestamp, state, cycle, live, backtesting_universe=None)

Run one trade execution tick.

Parameters

• backtesting_universe (Optional[StrategyExecutionUniverse]) – If passed, use this universe instead of trying to download and filter new one. This is shortcut for backtesting where the universe does not change between cycles (as opposite to live trading new pairs pop in to the existince).

• unrounded_timestamp (datetime) –

• state (State) –

• cycle (int) –

• live (bool) –

Return type

StrategyExecutionUniverse

update_position_valuations(clock, state, universe)

Revalue positions and update statistics.

A new statistics entry is calculated for portfolio and all of its positions and added to the state.

Parameters

• clock (datetime) – Real-time or historical clock

• state (State) –

• universe (StrategyExecutionUniverse) –

warm_up_backtest()

Load backtesting trading universe.

Display progress bars for data downloads.

run_backtest_stop_loss_checks(start_ts, end_ts, state, universe)

Generate stop loss price checks.

Backtests may use finer grade data for stop loss signals, to be more realistic with actual trading.

Here we use the finer grade data to check the stop losses on a given time period.

Parameters

• start_ts (datetime) – When to start testing (exclusive). We test for the next available timestamp.

• end_ts (datetime) – When to stop testing (exclusive).

• state (State) –

• universe (TradingStrategyUniverse) –

param universe:

Trading universe containing price data for stoploss checks.

run_backtest(state)

Backtest loop.

Parameters

state (State) –

Return type

dict

run_live(state)

Run live trading cycle.

Parameters

state (State) –

run()

The main loop of trade executor.

Main entry point to the loop.

• Chooses between live and backtesting execution mode

• Loads or creates the initial state

• Sets up strategy runner

Returns

Debug state where each key is the cycle number

Return type

dict