indicator#
API documentation for tradeexecutor.strategy.pandas_trader.indicator Python module in Trading Strategy.
Module description#
Indicator definitions.
Defining technical analysis and external indicators for trading strategies
Precalculating indicators and caching the results on a disk
Continuing indicator calculator in the case of crash
Support both single backtest and grid search modes
Support indicators depending on other indicators via dependency order resolution using
IndicatorDependencyResolver
Support external data sources
To get started with indicators see examples in CreateIndicatorsProtocolV2
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Classes#
Call signature for create_indicators function. |
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Call signature for create_indicators function. |
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Store calculated indicator results on disk. |
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A definition for a single indicator. |
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A helper class allowing access to the indicators we depend on. |
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Cache key used to read indicator results. |
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One result of an indicator calculation we can store on a disk. |
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Define the indicators that are needed by a trading strategy. |
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The data on which the indicator will be calculated. |
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Base class for cached indicators and live trading indicators. |
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Store calculated indicator results on disk. |
Functions#
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Precalculate all indicators. |
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Calculate indicators in the notebook itself, before starting the backtest. |
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Calculate indicators for which we do not have cached data yet. |
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Backwards compatible wrapper for create_indicators(). |
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Split indicator calculations to the groups based on their dependency resolution order. |
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Load cached indicators. |
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Call the strategy module indicator builder. |
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Set up multiprocessing for indicators. |
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Check that we can pass the given kwargs to a function. |
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Precalculate all indicators. |
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Turn None return values to empty pandsa Series. |