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True or spurious long memory in European non-EMU currencies

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  • Walther, Thomas
  • Klein, Tony
  • Thu, Hien Pham
  • Piontek, Krzysztof

Abstract

We examine the Croatian Kuna, the Czech Koruna, the Hungarian Forint, the Polish Złoty, the Romanian Leu, and the Swedish Krona whether their Euro exchange rates volatility exhibits true or spurious long memory. Recent research reveals long memory in foreign exchange rate volatility and we confirm this finding for these currency pairs by examining the long memory behavior of squared residuals by means of the V/S test. However, by using the ICSS approach we also find structural breaks in the unconditional variance. Literature suggests that structural breaks might lead to spurious long memory behavior. In a refined test strategy, we distinguish true from spurious long memory for the six exchange rates. Our findings suggest that Czech Koruna and Hungarian Forint only feature spurious long memory, while the rest of the series have both structural breaks and true long memory. Lastly, we demonstrate how to extend existing models to jointly model both properties yielding superior fit and better Value-at-Risk forecasts. The results of our work help to avoid misspecification and provide a better understanding of the properties of the foreign exchange rate volatility.

Suggested Citation

  • Walther, Thomas & Klein, Tony & Thu, Hien Pham & Piontek, Krzysztof, 2017. "True or spurious long memory in European non-EMU currencies," Research in International Business and Finance, Elsevier, vol. 40(C), pages 217-230.
  • Handle: RePEc:eee:riibaf:v:40:y:2017:i:c:p:217-230
    DOI: 10.1016/j.ribaf.2017.01.003
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    9. Cevik, Emrah Ismail & Gunay, Samet & Dibooglu, Sel & Yıldırım, Durmuş Çağrı, 2023. "The impact of expected and unexpected events on Bitcoin price development: Introduction of futures market and COVID-19," Finance Research Letters, Elsevier, vol. 54(C).

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    More about this item

    Keywords

    Conditional variance; Foreign exchange; GARCH; Spurious long memory; Value-at-Risk;
    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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