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Multivariate GARCH models and Black-Litterman approach for tracking error constrained portfolios: an empirical analysis

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  • Giulio PALOMBA

    ([n.a.])

Abstract

In a typical tactical asset allocation set up managers generally make their investment decisions by inserting private information in an optimisation mechanism used to beat a benchmark portfolio; in this context the sole approach a' la Markowitz (1959) does not use all the available information about expected excess return and especially it does not take two main factors into account: first, asset returns often show changes in volatility, and second, the manager's private information plays no role in the optimisation process. This paper provides an empirical work for large scale tactical asset allocation strategy in which a multivariate GARCH estimation is used in portfolio optimisation, given a tracking error constraint (Jorion, 2003). Moreover, the use of Black and Litterman (1991, 1992) approach allows for the possibility to tactically manage the selected portfolio through a very short time, combining informations taken from the time varying volatility model with some personal "view" about asset returns.

Suggested Citation

  • Giulio PALOMBA, 2006. "Multivariate GARCH models and Black-Litterman approach for tracking error constrained portfolios: an empirical analysis," Working Papers 267, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
  • Handle: RePEc:anc:wpaper:267
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    References listed on IDEAS

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    1. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    2. Doron Avramov, 2004. "Stock Return Predictability and Asset Pricing Models," Review of Financial Studies, Society for Financial Studies, vol. 17(3), pages 699-738.
    3. Roy van der Weide, 2002. "GO-GARCH: a multivariate generalized orthogonal GARCH model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 549-564.
    4. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
    5. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    6. Wei Shi & Scott H. Irwin, 2005. "Optimal Hedging with a Subjective View: An Empirical Bayesian Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 918-930.
    7. Pedro N. Rodríguez, & Simón Sosvilla-Rivero, 2006. "Forecasting Stock Price Changes: Is it Possible?," Working Papers 2006-22, FEDEA.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1684, August.
    10. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    11. Monica Billio & Massimiliano Caporin & Michele Gobbo, 2006. "Flexible Dynamic Conditional Correlation multivariate GARCH models for asset allocation," Applied Financial Economics Letters, Taylor and Francis Journals, vol. 2(2), pages 123-130, March.
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    Cited by:

    1. Ugo FRATESI, 2010. "The National and International Effects;of Regional Policy Choices: Agglomeration Economies, Peripherality and Territorial Characteristics," Working Papers 344, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    2. Fabio FIORILLO & Agnese SACCHI, 2010. "I Want to Free-ride. An Opportunistic View on Decentralization Versus Centralization Problem," Working Papers 346, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.

    More about this item

    Keywords

    Black and Litterman approach; multivariate GARCH models; tactical asset allocation;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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