Influence of some ARFIMA model parameters on the accuracy of financial time series forecasting

Robert Garafutdinov ()
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Robert Garafutdinov: Perm State University, Perm, Russian Federation;

Applied Econometrics, 2021, vol. 62, 85-100

Abstract: The influence of ARFIMA model parameters on the accuracy of financial time series forecasting on the example of artificially generated long memory series and daily log returns of RTS index is investigated. The investigated parameters are deviation of the integration order value from its «true» value, as well as the memory «length» considered by the model. Based on the research results, some practical recommendations for modeling using ARFIMA have been formulated.

Keywords: ARFIMA; financial time series; long memory; Hurst index; detrended fluctuation analysis. (search for similar items in EconPapers)
JEL-codes: C22 C53 G17 (search for similar items in EconPapers)
Date: 2021
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