Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: http://hdl.handle.net/10419/4311
Autor:innen: 
Liu, Ruipeng
Di Matteo, Tiziana
Lux, Thomas
Datum: 
2008
Schriftenreihe/Nr.: 
Economics Working Paper No. 2008-09
Verlag: 
Kiel University, Department of Economics, Kiel
Zusammenfassung: 
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.
Schlagwörter: 
Markov-switching multifractal
scaling
return volatility
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
877.69 kB





Publikationen in EconStor sind urheberrechtlich geschützt.