Fractionally differenced price series, especially with a differencing order estimated from an ARFIMA model, improved LSTM forecasts and portfolio trading metrics compared to logarithmic returns.
Statistical inference for ARTFIMA time series with stable innovations
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abstract
Autoregressive tempered fractionally integrated moving average with stable innovations modifies the power-law kernel of the fractionally integrated time series model by adding an exponential tempering factor. The tempered time series is a stationary model that can exhibits semi-long-range dependence. This paper develops the basic theory of the tempered time series model, including dependence structure and parameter estimation.
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Comparative analysis of financial data differentiation techniques using LSTM neural network
Fractionally differenced price series, especially with a differencing order estimated from an ARFIMA model, improved LSTM forecasts and portfolio trading metrics compared to logarithmic returns.