Forecasting Hedge Funds Volatility: A Markov Regime-Switching Approach

45 Pages Posted: 28 Feb 2011

Date Written: February 2011

Abstract

The article focuses on forecasting idiosyncratic hedge fund return volatility using a non-linear Markov switching GARCH (MS-GARCH) framework in which the conditional mean and volatility of systematic and idiosyncratic hedge fund return components may exhibit dynamic Markov switching behaviour. The article compares the out-of-sample and multi-step ahead forecasting performance of two competing conditional volatility specifications: GARCH(1,1) and MS-GARCH(1,1). The work employs data collected on 12 global hedge fund indices over January 1990 - October 2010 and produce volatility forecasts for the January 1999 - October 2010 period. The forecasting precision measure employed evidences superior forecasting performance of the MS volatility model for most hedge fund indices considered. The forecast encompassing robustness test results provide evidence that the MS-GARCH volatility forecasts significantly encompass the GARCH volatility forecasts for most Event-Driven and Relative Value hedge fund indices, whereas forecast encompassing is less significant for some Equity Hedge and Emerging Markets hedge fund indices.

Keywords: hedge fund indices, idiosyncratic return, Markov switching model, volatility forecasting

JEL Classification: G11, G17, G23

Suggested Citation

Blazsek, Szabolcs and Downarowicz, Anna, Forecasting Hedge Funds Volatility: A Markov Regime-Switching Approach (February 2011). Available at SSRN: https://ssrn.com/abstract=1768864 or http://dx.doi.org/10.2139/ssrn.1768864

Szabolcs Blazsek

affiliation not provided to SSRN ( email )

No contact information is available for Anna Downarowicz

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