Function reference • InvestigatoR

All functions
`add_model_prediction()`	Add model prediction to returnPrediction S3 object
`add_weight_model()`	Add a new weight model to the portfolioReturns S3 object
`backtesting_portfolios()`	This function is for backtesting portfolios given return predictions
`backtesting_returns()`	This function is used to use ML to predict the returns that will later be used for a trading strategy
`calculate_errors()`	Calculate errors between predictions and actual returns
`convert_period_to_days()`	Helper function to convert any time period to days
`create_portfolios()`	Create portfolioReturns S3 object
`create_return_prediction()`	Create returnPrediction S3 object
`ensemble_weights()`	Create weights based on various predictions, potentially using their errors with given constraints
`find_largest_number()`	Helper function to find largest number after a certain string
`ols_pred()`	ols function for return prediction
`perf_met()`	Helper function to create performance metrics for a given set of returns, weights, and actual data
`plot(<portfolioReturns>)`	Plotting method for portfolioReturns S3 objects
`quantile_weights()`	Create weights based on predictions with given constraints
`retpred_map()`	Return Prediction Mapping Function (Helper)
`select_dates_by_offset()`	Helper function to create a tibble of training/prediction start and end dates based on a rolling window with an offset
`summary(<portfolioReturns>)`	Define the summary method for 'portfolioReturns' class
`summary(<returnPrediction>)`	Summary method for returnPrediction S3 object
`xgb_pred()`	xgb function for return prediction

Reference

All functions