Time-Varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies

Tinbergen Institute Discussion Paper 16-099/III

44 Pages Posted: 22 Nov 2016

See all articles by Nalan Basturk

Nalan Basturk

Maastricht University - Department of Quantitative Economics

Stefano Grassi

University of Kent - Canterbury Campus

Lennart F. Hoogerheide

VU University Amsterdam

H. K. van Dijk

Tinbergen Institute; Econometric Institute

Date Written: October 31, 2016

Abstract

A novel dynamic asset-allocation approach is proposed where portfolios as well as portfolio strategies are updated at every decision period based on their past performance. For modeling, a general class of models is specified that combines a dynamic factor and a vector autoregressive model and includes stochastic volatility, denoted by FAVAR-SV. Next, a Bayesian strategy combination is introduced in order to deal with a set of strategies. Our approach extends the mixture of the experts analysis by allowing the strategic weights to be dependent between strategies as well as over time and to further allow for strategy incompleteness. Our approach results in a combination of different portfolio strategies: a model-based and a residual momentum strategy. The estimation of this modeling and strategy approach can be done using an extended and modified version of the forecast combination methodology of Casarin, Grassi, Ravazzolo and Van Dijk (2016). Given the complexity of the non-linear and non-Gaussian model used a new and efficient filter is introduced based on the MitISEM approach by Hoogerheide, Opschoor and Van Dijk (2013).

Using US industry portfolios between 1926M7 and 2015M6 as data, our empirical results indicate that time-varying combinations of flexible models in the FAVAR-SV class and two momentum strategies lead to better return and risk features than very simple and very complex models. Combinations of two strategies help, in particular, to reduce risk features like volatility and largest loss, which indicates that complete densities provide useful information for risk.

Keywords: nonlinear, non-gaussian state space, filters, density combinations, bayesian modeling, equity momentum

JEL Classification: C11, C15, G11, G17

Suggested Citation

Basturk, Nalan and Grassi, Stefano and Hoogerheide, Lennart F. and van Dijk, Herman K., Time-Varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies (October 31, 2016). Tinbergen Institute Discussion Paper 16-099/III, Available at SSRN: https://ssrn.com/abstract=2871109 or http://dx.doi.org/10.2139/ssrn.2871109

Nalan Basturk (Contact Author)

Maastricht University - Department of Quantitative Economics ( email )

P.O. Box 616
Maastricht, 6200 MD
Netherlands

Stefano Grassi

University of Kent - Canterbury Campus ( email )

Keynes College
Canterbury, Kent CT2 7NP
United Kingdom

Lennart F. Hoogerheide

VU University Amsterdam ( email )

De Boelelaan 1105
Amsterdam, ND North Holland 1081 HV
Netherlands

Herman K. Van Dijk

Tinbergen Institute ( email )

Gustav Mahlerplein 117
Burg. Oudlaan 50
Amsterdam/Rotterdam, 1082 MS
Netherlands
+31104088955 (Phone)
+31104089031 (Fax)

HOME PAGE: http://people.few.eur.nl/hkvandijk/

Econometric Institute ( email )

P.O. Box 1738
3000 DR Rotterdam
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+31 10 4088955 (Phone)
+31 10 4527746 (Fax)

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