0434201 20240103204931.920141106235959.9 84947254896 000408772300001 10.1080/07474938.2014.977057 43 s. P cav_un_epca*02930340747-49383610 (2017)1081-1110Taylor & Francis price durations long memory multifractal models realized volatility Whittle estimation cav_un_auth*0308943 30 Žikeš F. GB K cav_un_auth*0242028 Ekonometrie Department of Econometrics E E Department of Econometrics 40 Baruník Jozef UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0308944 30 Shenai N. GB http://library.utia.cas.cz/separaty/2014/E/barunik-0434201.pdf cav_un_auth*0292677 GA13-32263S GA ČR cav_un_auth*0308905 612955 EC 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. WOS AH 50000 50200 50202 2018 3 4 A hod 4ah 4a 20231122140548.2 RVO:67985556 http://hdl.handle.net/11104/0238358 1 Department of Econometrics UTIA-B 50202 ECONOMICS S 3+4 Article Economics|Mathematics Interdisciplinary Applications|Social Sciences Mathematical Methods|Statistics Probability 2 Article Economics|Mathematics Interdisciplinary Applications|Social Sciences Mathematical Methods|Statistics Probability 2 Article Economics|Mathematics Interdisciplinary Applications|Social Sciences Mathematical Methods|Statistics Probability ECONOMICS|STATISTICS&PROBABILITY|MATHEMATICS.INTERDISCIPLINARYAPPLICATIONS|SOCIALSCIENCES.MATHEMATICALMETHODS 1.622 0.236 11.2 0.00425 1.599 1313 1.797 1.178 55 Q2 80.01 54.5 Q1 Q1 0.95 Q1 61.382 2017 Soubory v repozitáři: barunik-0434201.pdf, barunik-0434201.pdf 84947254896 SCOPUS 000408772300001 WOS cav_un_epca*0293034 Econometric Reviews 0747-4938 1532-4168 Roč. 36 č. 10 2017 1081 1110 Taylor & Francis