publication . Preprint . 2006

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

Giulio PALOMBA;
Open Access
  • Published: 01 Sep 2006
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 i...
Subjects
free text keywords: Black and Litterman approach, multivariate GARCH models, tactical asset allocation, jel:C32, jel:C53, jel:G11
28 references, page 1 of 2

Aiolfi M. and Favero C.A. (2005), “Model uncertainty, thick modelling and the predictability of stock returns”, Journal of Forecasting 24(4), pp. 233-254.

Alexander C. and Chibumba A.M. (1996), “Multivariate orthogonal factor GARCH”, Discussion Paper in Mathematics, University of Sussex.

Avramov D. (2002), “Stock return predictability and model uncertainty”, Journal of Financial Economics 64, pp. 423-458.

Avramov D. (2004), “Stock return predictability and asset pricing models”, Review of Financial Studies 17, pp. 699-738.

Bevan A. and Winkelmann K. (1998), “Using the Black-Litterman global asset allocation model: three years of practical experience”, Fixed Income Research, Goldman Sachs & Co.

Billio M., Caporin M. and Gobbo M. (2003), “Block dynamic conditional correlation multivariate GARCH models”, GRETA working paper n. 03.03.

Billio M., Caporin M. and Gobbo M. (2006), “Flexible Dynamic Conditional Correlation multivariate GARCH models for asset allocation”, Applied Financial Economics Letters 2, pp. 123-130.

Black F. and Litterman R. (1991), “Asset allocation: combining investors views with market equilibrium”, Journal of Fixed Income, september, pp. 7-18.

Black F. and Litterman R. (1992), “Global portfolio optimization”, Financial Analysts Journal 48(5), pp. 28-43.

Bollerslev T. (1986), “Generalized autoregressive conditional heteroskedasticity”, Journal of Econometrics 31, pp. 307-327. [OpenAIRE]

Bollerslev T. (1990), “Modelling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH approach”, Review of Economics and Statistics 72, pp. 498-505. [OpenAIRE]

Bollerslev T., Engle R.F. and Nelson D.B. (1994), ARCH models, in R.F. Engle & D.L. McFadden (eds.), Handbook of Econometrics, vol. IV, Elsevier, North Holland.

Bollerslev T., Engle R.F. and Wooldridge J.M. (1988), “A capital asset pricing model with time varying covariances”, Journal of Political Economy 96, pp. 116-131. [OpenAIRE]

Corvala´n A. (2005), “Mixed tactical asset allocation”, Working paper n. 323, Banco Central de Chile.

Ding Z.X., Engle R.F. and Granger C.W.J. (1993), “A long memory property of stock markets returns and a new model”, Journal of Empirical Finance 1, pp. 83-106.

28 references, page 1 of 2
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 i...
Subjects
free text keywords: Black and Litterman approach, multivariate GARCH models, tactical asset allocation, jel:C32, jel:C53, jel:G11
28 references, page 1 of 2

Aiolfi M. and Favero C.A. (2005), “Model uncertainty, thick modelling and the predictability of stock returns”, Journal of Forecasting 24(4), pp. 233-254.

Alexander C. and Chibumba A.M. (1996), “Multivariate orthogonal factor GARCH”, Discussion Paper in Mathematics, University of Sussex.

Avramov D. (2002), “Stock return predictability and model uncertainty”, Journal of Financial Economics 64, pp. 423-458.

Avramov D. (2004), “Stock return predictability and asset pricing models”, Review of Financial Studies 17, pp. 699-738.

Bevan A. and Winkelmann K. (1998), “Using the Black-Litterman global asset allocation model: three years of practical experience”, Fixed Income Research, Goldman Sachs & Co.

Billio M., Caporin M. and Gobbo M. (2003), “Block dynamic conditional correlation multivariate GARCH models”, GRETA working paper n. 03.03.

Billio M., Caporin M. and Gobbo M. (2006), “Flexible Dynamic Conditional Correlation multivariate GARCH models for asset allocation”, Applied Financial Economics Letters 2, pp. 123-130.

Black F. and Litterman R. (1991), “Asset allocation: combining investors views with market equilibrium”, Journal of Fixed Income, september, pp. 7-18.

Black F. and Litterman R. (1992), “Global portfolio optimization”, Financial Analysts Journal 48(5), pp. 28-43.

Bollerslev T. (1986), “Generalized autoregressive conditional heteroskedasticity”, Journal of Econometrics 31, pp. 307-327. [OpenAIRE]

Bollerslev T. (1990), “Modelling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH approach”, Review of Economics and Statistics 72, pp. 498-505. [OpenAIRE]

Bollerslev T., Engle R.F. and Nelson D.B. (1994), ARCH models, in R.F. Engle & D.L. McFadden (eds.), Handbook of Econometrics, vol. IV, Elsevier, North Holland.

Bollerslev T., Engle R.F. and Wooldridge J.M. (1988), “A capital asset pricing model with time varying covariances”, Journal of Political Economy 96, pp. 116-131. [OpenAIRE]

Corvala´n A. (2005), “Mixed tactical asset allocation”, Working paper n. 323, Banco Central de Chile.

Ding Z.X., Engle R.F. and Granger C.W.J. (1993), “A long memory property of stock markets returns and a new model”, Journal of Empirical Finance 1, pp. 83-106.

28 references, page 1 of 2
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue