Kiel Working Papers, Kiel Institute for World Economics
No 1737:
A Markov-switching Multifractal Approach to Forecasting Realized Volatility
Thomas Lux, Leonardo Morales-Arias and Cristina Sattarhoff
Abstract: The volatility specification of the Markov-switching
Multifractal (MSM) model is proposed as an alternative mechanism for
realized volatility (RV). We estimate the RV-MSM model via Generalized
Method of Moments and perform forecasting by means of best linear forecasts
derived via the Levinson-Durbin algorithm. The out-of-sample performance of
the RV-MSM is compared against other popular time series specfications
usually employed to model the dynamics of RV as well as other standard
volatility models of asset returns. An intra-day data set for five major
international stock market indices is used to evaluate the various models
out-of-sample. We find that the RV-MSM seems to improve upon forecasts of
its baseline MSM counterparts and many other volatility models in terms of
mean squared errors (MSE). While the more conventional RV-ARFIMA model
comes out as the most successful model (in terms of the number of cases in
which it has the best forecasts for all combinations of forecast horizons
and criteria), the new RV-MSM model seems often very close in its
performance and in a non-negligible number of cases even dominates over the
RV-ARFIMA model
Keywords: Realized volatility, multiplicative volatility models, long memory, international volatility forecasting; (follow links to similar papers)
JEL-Codes: C20,; G12; (follow links to similar papers)
48 pages, October 2011
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