Quant.Strategy.Utils (quant v0.1.0-alpha.1)

Utility functions for strategy operations.

This module provides common utility functions used across different strategy types, including DataFrame validation, column management, and data preprocessing.

Summary

Functions

add_timing_analysis(dataframe)

Add timing information for strategy signals.

calculate_position_sizes(dataframe, strategy, opts \\ [])

Calculate position sizing based on strategy configuration and risk parameters.

cleanup_intermediate_columns(dataframe, strategy)

Remove intermediate indicator columns that are not needed in final output.

validate_dataframe(dataframe, strategy, opts \\ [])

Validate that a DataFrame has the required structure for strategy execution.

Functions

add_timing_analysis(dataframe)

@spec add_timing_analysis(Explorer.DataFrame.t()) :: Explorer.DataFrame.t()

Add timing information for strategy signals.

Adds columns for signal timing analysis:

  • signal_duration: How long each signal lasts
  • time_since_last_signal: Time elapsed since previous signal
  • signal_sequence: Sequential numbering of signals

calculate_position_sizes(dataframe, strategy, opts \\ [])

@spec calculate_position_sizes(Explorer.DataFrame.t(), map(), keyword()) ::
  Explorer.DataFrame.t()

Calculate position sizing based on strategy configuration and risk parameters.

Parameters

  • dataframe - DataFrame with price data
  • strategy - Strategy configuration
  • opts - Position sizing options

Options

  • :method - Position sizing method (:fixed, :percent_capital, :volatility)
  • :capital - Total available capital
  • :risk_per_trade - Risk percentage per trade
  • :atr_multiplier - ATR multiplier for volatility-based sizing

Returns

DataFrame with position sizes added.

cleanup_intermediate_columns(dataframe, strategy)

@spec cleanup_intermediate_columns(Explorer.DataFrame.t(), map()) ::
  Explorer.DataFrame.t()

Remove intermediate indicator columns that are not needed in final output.

Parameters

  • dataframe - DataFrame with intermediate columns
  • strategy - Strategy configuration

Returns

DataFrame with only essential columns retained.

validate_dataframe(dataframe, strategy, opts \\ [])

@spec validate_dataframe(Explorer.DataFrame.t(), map(), keyword()) ::
  {:ok, Explorer.DataFrame.t()} | {:error, term()}

Validate that a DataFrame has the required structure for strategy execution.

Parameters

  • dataframe - DataFrame to validate
  • strategy - Strategy configuration
  • opts - Additional validation options

Returns

{:ok, dataframe} if valid, {:error, reason} if invalid.

Validations Performed

  • Check for required columns
  • Validate minimum number of rows
  • Check for proper data types
  • Ensure datetime index if required