GridSearchResult#
API documentation for tradeexecutor.backtest.grid_search.GridSearchResult Python class in Trading Strategy framework.
- class GridSearchResult[source]#
Bases:
object
Result for one grid combination.
Result for one grid search combination
Calculate various statistics and curves ready in a multiprocess worker
Results can be cached on a disk, as a pickle
Some of the data might not be available or discarded as per
GridSearchDataRetention
- __init__(combination, state, summary, metrics, equity_curve, returns, universe_options, cached=False, process_id=None)#
- Parameters:
combination (GridCombination) –
state (tradeexecutor.state.state.State | None) –
summary (TradeSummary) –
metrics (DataFrame) –
equity_curve (Series) –
returns (Series) –
universe_options (UniverseOptions) –
cached (bool) –
- Return type:
None
Methods
__init__
(combination, state, summary, ...[, ...])Get name for this result for charts.
get_metric
(name)Get a performance metric from quantstats.
has_result
(combination)load
(combination)Deserialised from the cached Python pickle.
save
()Serialise as Python pickle.
Attributes
For which grid combination this result is
The full back test state
Calculated trade summary
Performance metrics
Needed for visualisations
Needed for visualisations
What backtest data range we used
Was this result read from the earlier run save
Child process that created this result.
- combination: GridCombination#
For which grid combination this result is
- state: tradeexecutor.state.state.State | None#
The full back test state
- summary: TradeSummary#
Calculated trade summary
Internal stats calculated about trades
- universe_options: UniverseOptions#
What backtest data range we used
- get_metric(name)[source]#
Get a performance metric from quantstats.
A shortcut method.
Example:
grid_search_results = perform_grid_search( decide_trades, strategy_universe, combinations, max_workers=8, trading_strategy_engine_version="0.4", multiprocess=True, ) print("Sharpe of the first result", grid_search_results[0].get_metric("Sharpe")
- static load(combination)[source]#
Deserialised from the cached Python pickle.
- Parameters:
combination (GridCombination) –
- __init__(combination, state, summary, metrics, equity_curve, returns, universe_options, cached=False, process_id=None)#
- Parameters:
combination (GridCombination) –
state (tradeexecutor.state.state.State | None) –
summary (TradeSummary) –
metrics (DataFrame) –
equity_curve (Series) –
returns (Series) –
universe_options (UniverseOptions) –
cached (bool) –
- Return type:
None