Linear Predictability vs. Bull and Bear Market Models in Strategic Asset Allocation Decisions: Evidence from UK Data

Most papers in the portfolio choice literature have examined linear predictability frameworks based on the idea that simple but flexible Vector Autoregressive (VAR) models can be expanded to produce portfolio allocations that hedge against the bull and bear dynamics typical of financial markets through careful selection of predictor variables that capture business cycles and market sentiment. Yet, a distinct literature exists that shows that nonlinear econometric frameworks, such as Markov switching, are also natural tools to compute optimal portfolios arising from the existence of good and bad market states. This paper examines whether and how simple VARs can produce portfolio rules similar to those obtained under a simple Markov switching, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock-bond strategic asset allocation problem for U.K. data, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those of nonlinear models. We conclude that most VARs cannot produce portfolio rules, hedging demands, or (net of transaction costs) out-of-sample performances that approximate those obtained from equally simple nonlinear frameworks

Markov-Switching Structural Vector Autoregressions: Theory and Application

This paper develops a new and easily implementable necessary and sufficient condition for the exact identification of a Markov-switching structural vector autoregression (SVAR) model. The theorem applies to models with both linear and some nonlinear restrictions on the structural parameters. We also derive efficient MCMC algorithms to implement sign and long-run restrictions in Markov-switching SVARs. Using our methods, four well-known identification schemes are used to study whether monetary policy has changed in the euro area since the introduction of the European Monetary Union. We find that models restricted to only time-varying shock variances dominate the other models. We find a persistent post-1993 regime that is associated with low volatility of shocks to output, prices, and interest rates. Finally, the output effects of monetary policy shocks are small and uncertain across regimes and models. These results are robust to the four identification schemes studied in this paper

Corresponding author. 49-203-3792969; 49- 203-3793665. E-mail addresses: [email protected] Hinzke), [email protected] Nowak). Journal Magnetism Magnetic Materials (2000) 365}372

For investigations thermally activated magnetization reversal systems of classical magnetic moments numerical methods desirable. present numerical studies which base time quanti"ed Monte Carlo methods where long-range dipole}dipole interaction calculated fast Fourier transformation. example, study models ferromagnetic nanowires comparing numerical results characteristic time reversal process also with numerical data from Langevin dynamics simulations where fast Fourier transformation method well established. Depending system geometry di!erent reversal mechanism occur coherent rotation, nucleation, curling. 2000 Elsevier Science B.V. rights reserved. PACS: 75.10.Hk; 75.40.Mg; 75.40.Gb Keywords: Classical spin models; Numerical simulation studies; Thermal activation; Magnetization reversal; Nanostructure