Kiel Working Papers, Kiel Institute for World Economics
No 1427:
Multifractality and Long-Range Dependence of Asset Returns: The Scaling Behaviour of the Markov-Switching Multifractal Model with Lognormal Volatility Components
Ruipeng Liu, Tiziana Di Matteo and Thomas Lux
Abstract: 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
Keywords: Markov-switching multifractal, scaling, return volatility; (follow links to similar papers)
JEL-Codes: C22,; G12; (follow links to similar papers)
15 pages, June 2008
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