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Asset allocation in a Bayesian copula-GARCH framework: An application to the ‘passive funds versus active funds’ problem

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  • Long Kang

    (Quantitative Risk Management, The Options Clearing Corporation, One North Wacker Drive)

Abstract

We solve a one-period asset allocation problem with a Bayesian copula-Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. Investors invest among risk-free assets, a passive fund and an active fund, and maximize their expected utility. Posterior distributions of model parameters are drawn by the ‘Metropolis-within-Gibbs’ algorithm. Our results show significant percentage of holdings in active funds with different levels of risk aversion. With low risk aversion, Bayesian models yield similar portfolio weights and returns with non-Bayesian models. As risk aversion increases, however, Bayesian models imply more conservative weights in active funds and lead to significantly lower volatility of realized out-of-sample returns and utilities.

Suggested Citation

  • Long Kang, 2011. "Asset allocation in a Bayesian copula-GARCH framework: An application to the ‘passive funds versus active funds’ problem," Journal of Asset Management, Palgrave Macmillan, vol. 12(1), pages 45-66, April.
    • Handle: RePEc:pal:assmgt:v:12:y:2011:i:1:d:10.1057_jam.2010.6
    DOI: 10.1057/jam.2010.6
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    References listed on IDEAS

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    Cited by:

    1. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2016. "A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 814-829.
    2. Yanwei Zhang & Vanja Dukic, 2013. "Predicting Multivariate Insurance Loss Payments Under the Bayesian Copula Framework," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(4), pages 891-919, December.
    3. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.

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