Počet záznamů: 1  

Modeling and Forecasting Persistent Financial Durations

  1. 1.
    0434201 - ÚTIA 2018 RIV US eng J - Článek v odborném periodiku
    Žikeš, F. - Baruník, Jozef - Shenai, N.
    Modeling and Forecasting Persistent Financial Durations.
    Econometric Reviews. Roč. 36, č. 10 (2017), s. 1081-1110. ISSN 0747-4938. E-ISSN 1532-4168
    Grant CEP: GA ČR GA13-32263S
    GRANT EU: European Commission 612955 - FINMAP
    Institucionální podpora: RVO:67985556
    Klíčová slova: price durations * long memory * multifractal models * realized volatility * Whittle estimation
    Obor OECD: Applied Economics, Econometrics
    Impakt faktor: 1.218, rok: 2017
    http://library.utia.cas.cz/separaty/2014/E/barunik-0434201.pdf

    This paper introduces the Markov-Switching Multifractal Duration (MSMD) model by adapting the MSM stochastic volatility model of Calvet and Fisher (2004) to the duration setting. Although the MSMD process is exponential beta-mixing as we show in the paper, it is capable of generating highly persistent autocorrelation. We study analytically and by simulation how this feature of durations generated by the MSMD process propagates to counts and realized volatility. We employ a quasi-maximum likelihood estimator of the MSMD parameters based on the Whit- tle approximation and establish its strong consistency and asymptotic normality for general MSMD specifications. We show that the Whittle estimation is a computa- tionally simple and fast alternative to maximum likelihood. Finally, we compare the performance of the MSMD model with competing short- and long-memory duration models in an out-of-sample forecasting exercise based on price durations of three major foreign exchange futures contracts.
    Trvalý link: http://hdl.handle.net/11104/0238358

     
     
Počet záznamů: 1  

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