Markov-switching asset allocation: Do profitable strategies exist?

This article proposes a straightforward Markov-switching asset allocation model, which reduces the market exposure to periods of high volatility. The main purpose of the study is to examine the performance of a regime-based asset allocation strategy under realistic assumptions, compared to a buy-and-hold strategy. An empirical study, utilizing daily return series of major equity indices in the United States, Japan and Germany over the past 40 years, investigates the performance of the model. In an out-of-sample context, the strategy proves profitable after taking transaction costs into account. For the regional markets under consideration, the volatility reduces on average by 41 per cent. In addition, annualized excess returns attain 18.5 to 201.6 basis points.

[1]  R. Quandt A New Approach to Estimating Switching Regressions , 1972 .

[2]  R. Quandt The Estimation of the Parameters of a Linear Regression System Obeying Two Separate Regimes , 1958 .

[3]  Rob Bauer,et al.  Asset Allocation in Stable and Unstable Times , 2004 .

[4]  Eric Moulines,et al.  Inference in hidden Markov models , 2010, Springer series in statistics.

[5]  Martin K. Hess Timing and diversification: A state-dependent asset allocation approach , 2006 .

[6]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[7]  Brian D. Singer,et al.  Determinants of Portfolio Performance II: An Update , 1991 .

[8]  L. Baum,et al.  A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains , 1970 .

[9]  Jan Bulla,et al.  Stylized facts of financial time series and hidden semi-Markov models , 2006, Comput. Stat. Data Anal..

[10]  Antonello Maruotti,et al.  A semiparametric approach to hidden Markov models under longitudinal observations , 2009, Stat. Comput..

[11]  Jan Bulla,et al.  Computational issues in parameter estimation for stationary hidden Markov models , 2008, Comput. Stat..

[12]  Eric Moulines,et al.  Inference in Hidden Markov Models (Springer Series in Statistics) , 2005 .

[13]  Manuel Ammann,et al.  The Effect of Market Regimes on Style Allocation , 2006 .

[14]  S. Goldfeld,et al.  A Markov model for switching regressions , 1973 .

[15]  T. Rydén,et al.  Stylized Facts of Daily Return Series and the Hidden Markov Model , 1998 .

[16]  Mark M. Carhart On Persistence in Mutual Fund Performance , 1997 .

[17]  Jan Bulla,et al.  Hidden Markov models with t components. Increased persistence and other aspects , 2011 .

[18]  Van Nostrand,et al.  Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm , 1967 .

[19]  W. Zucchini,et al.  Hidden Markov Models for Time Series: An Introduction Using R , 2009 .

[20]  Richard O. Michaud The Markowitz Optimization Enigma: Is 'Optimized' Optimal? , 1989 .

[21]  Andrew Ang,et al.  How Regimes Affect Asset Allocation , 2006 .

[22]  Birger Nilsson,et al.  Dynamic Portfolio Selection: The Relevance of Switching Regimes and Investment Horizon , 2002 .

[23]  G. Schwert Why Does Stock Market Volatility Change Over Time? , 1988 .

[24]  Jedrzej Bialkowski,et al.  Modelling Returns on Stock Indices for Western and Central European Stock Exchanges - a Markov Switching Approach , 2004 .

[25]  Keith H. Black International Asset Allocation with Regime Shifts , 2003 .

[26]  S. Satchell,et al.  Why do regime‐switching models forecast so badly? , 1999 .

[27]  L. Baum,et al.  Statistical Inference for Probabilistic Functions of Finite State Markov Chains , 1966 .

[28]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[29]  Massimo Guidolin,et al.  Economic Implications of Bull and Bear Regimes in UK Stock and Bond Returns , 2005 .

[30]  Thomas Linne A Markov Switching Model of Stock Returns: An Application to the Emerging Markets in Central and Eastern Europe , 2002 .

[31]  James D. Hamilton A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle , 1989 .