Abstract
The Merton’s framework is used for finding the solution of a portfolio problem. Then the quantities in this solution are estimated via a cointegrated vector autoregressive model for the mean part and a multivariate Garch for the volatility part. Finally a thousand is simulated by using the estimation before in a Euler scheme for the prices.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Allais M (1953) Le comportement de l'homme rationnel devant le risque: critique des postulats et axiomes de l'école Américaine. Econometrica 21:503–546
Bauwens L, Laurent S, Rombouts J (2004) Multivariate GARCH models: a survey. J Appl Econ 21:79–109
Bollerslev T, Engle RF, Nelson DB (1994) ARCH model, handbook of econometrics, vol IV. Elsevier Science, Amsterdam, pp 2959–3038
Brandt MW, Goyal A, Santa-Clara P, Stroud JR (2005) A simulation approach to dynamic portfolio choice with an application to learn about return predictability. Rev Financ Stud 18(3):831
Campbell JY, Chan YL, Viceira LM (2003) A multivariate model of strategic asset allocation. J Financ Econ 67(1):41–80
Campbella JY, Chacko G, Rodriguez J, Viceira LM (2004) Strategic asset allocation in a continuous-time VAR model. J Econ Dyn Control 28:2195–2214
Datastream Global Equity Indices (2008) User guide, issue 5. Thomson Reuters Ltd, Toronto
Duffie D (2001) Dynamic asset pricing theory. Princeton University Press, Princeton
Ellsberg D (1961) Risk, ambiguity, and the savage axioms. Quarterly J Econ 75(4):643–669
Engle R, Kroner K (1995) Multivariate simultaneous generalized ARCH. Econom Theory 11(1):122–150
Engle RF, Shephard N, Sheppard K (2008) Fitting vast dimensional time-varying covariance models, discussion paper series. University of Oxford, Oxford
Francq C, Zakoian JM (2010) GARCH models. Wiley, New York, pp 223–227
Hamilton JD (1994) Time series analysis. Princeton University Press, Princeton
Johansen S (1995) Likelihood-based inference in cointegrated vector autoregressive models. Oxford University Press, Oxford
Johansen S, Juselius K (1990) Maximum likelihood estimation and inference on cointegration with applications to the demand for money. Oxf Bull Econ Stat 52:169–210
Kloeden PE, Platen E (1992) Numerical solution of stochastic differential equation through computer experiments. Springer, New York
Lutkepohl H (2007) New introduction to multiple time series analysis. Springer, Berlin
Merton R (1973) An intertemporal capital asset pricing model. Econometrica 41(5):867–887
Milstein GN, Tretyakov MV (2004) Stochastic numerics for mathematical physics. Springer, Berlin
Oskendal B (2010) Stochastic differential equations. Springer, Berlin
Pojarliev M, Polasek W (2001) Applying multivariate time series forecasts for active porfolio management. Financ Mark Portf Manag 15(2):201
von Neumann J, Morgenstern O (1944) Theory of Games and Economic Behavior. Princeton University Press
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Pierini, A. Merton’s Portfolio Estimation with CVAR-MGarch: An Application to the Italian Stock Market. J Indian Soc Probab Stat 19, 153–168 (2018). https://doi.org/10.1007/s41096-018-0038-z
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41096-018-0038-z