Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/10419/3979
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dc.creatorLiu, Ruipeng-
dc.creatorDi Matteo, Tiziana-
dc.creatorLux, Thomas-
dc.date2007-
dc.date.accessioned2013-10-16T06:21:30Z-
dc.date.available2013-10-16T06:21:30Z-
dc.date.issued2013-10-16-
dc.identifierhttp://hdl.handle.net/10419/3979-
dc.identifierppn:52714956X-
dc.identifierRePEc:zbw:cauewp:5534-
dc.identifier.urihttp://koha.mediu.edu.my:8181/xmlui/handle/10419/3979-
dc.descriptionIn this paper, we consider daily financial data of a collection of different stock market indices, exchange rates, and interest rates, and we analyze their multi-scaling properties by estimating a simple specification of the Markov- switching multifractal model (MSM). In order to see how well the estimated models capture the temporal dependence of the data, we estimate and compare the scaling exponents H(q) (for q = 1; 2) for both empirical data and simulated data of the estimated MSM models. In most cases the multifractal model appears to generate `apparent' long memory in agreement with the empirical scaling laws.-
dc.languageeng-
dc.publisherInstitut für Volkswirtschaftslehre, Kiel-
dc.relationEconomics working paper / Christian-Albrechts-Universität Kiel, Department of Economics 2007,06-
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.subjectddc:330-
dc.subjectScaling-
dc.subjectGeneralized Hurst exponent-
dc.subjectMultifractal model-
dc.subjectGMM estimation-
dc.titleTrue and Apparent Scaling: The Proximity of the Markov- Switching Multifractal Model to Long-Range Dependence-
dc.typedoc-type:workingPaper-
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