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Multifractality and long-range dependence of asset returns: The scaling behaviour of the Markov-switching multifractal model with lognormal volatility components

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dc.creator Liu, Ruipeng
dc.creator Di Matteo, Tiziana
dc.creator Lux, Thomas
dc.date 2008
dc.date.accessioned 2013-10-16T06:19:14Z
dc.date.available 2013-10-16T06:19:14Z
dc.date.issued 2013-10-16
dc.identifier http://hdl.handle.net/10419/4311
dc.identifier ppn:570350115
dc.identifier ppn:570350115
dc.identifier RePEc:zbw:cauewp:7371
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/10419/4311
dc.description In this paper we consider daily financial data from various sources (stock market indices, foreign exchange rates and bonds) and analyze their multi-scaling properties by estimating the parameters of a Markov-switching multifractal model (MSM) with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the empirical data, we estimate and compare (generalized) Hurst exponents for both empirical data and simulated MSM models. In general, the Lognormal MSM models generate ?apparent? long memory in good agreement with empirical scaling provided one uses sufficiently many volatility components. In comparison with a Binomial MSM specification [7], results are almost identical. This suggests that a parsimonious discrete specification is flexible enough and the gain from adopting the continuous Lognormal distribution is very limited.
dc.language eng
dc.publisher Institut für Volkswirtschaftslehre, Kiel
dc.relation Economics working paper / Christian-Albrechts-Universität Kiel, Department of Economics 2008,09
dc.rights http://www.econstor.eu/dspace/Nutzungsbedingungen
dc.subject ddc:330
dc.subject Markov-switching multifractal , scaling , return volatility
dc.subject Kapitalertrag
dc.subject Volatilität
dc.subject Finanzmarkt
dc.subject Markovscher Prozess
dc.subject Statistische Verteilung
dc.subject Theorie
dc.title Multifractality and long-range dependence of asset returns: The scaling behaviour of the Markov-switching multifractal model with lognormal volatility components
dc.type doc-type:workingPaper


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