Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10419/4304
Title: Multifractality and long-range dependence of asset returns: The scaling behaviour of the Markov-switching multifractal model with lognormal volatility components
Keywords: C22
G12
C22
ddc:330
Markov-switching multifractal
Scaling
Return volatility
Kapitalertrag
Volatilität
Finanzmarkt
Markovscher Prozess
Statistische Verteilung
Theorie
Issue Date: 16-Oct-2013
Publisher: Kiel Institute for the World Economy (IfW) Kiel
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.
URI: http://koha.mediu.edu.my:8181/xmlui/handle/10419/4304
Other Identifiers: http://hdl.handle.net/10419/4304
ppn:568787374
Appears in Collections:EconStor

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