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

Author

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  • Garafutdinov, Robert

    (Perm State University, Perm, Russian Federation;)

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.

Suggested Citation

  • Garafutdinov, Robert, 2021. "Influence of some ARFIMA model parameters on the accuracy of financial time series forecasting," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 62, pages 85-100.
    • Handle: RePEc:ris:apltrx:0420
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    References listed on IDEAS

    as
    1. Balagula, Yuri, 2020. "Forecasting daily spot prices in the Russian electricity market with the ARFIMA model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 57, pages 89-101.
    2. Rim Ammar Lamouchi, 2020. "Long Memory and Stock Market Efficiency: Case of Saudi Arabia," International Journal of Economics and Financial Issues, Econjournals, vol. 10(3), pages 29-34.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    ARFIMA; financial time series; long memory; Hurst index; detrended fluctuation analysis.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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