Recursive `thick´ modeling of excess returns and portfolio allocation

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Recursive `thick´ modeling of excess returns and portfolio allocation

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Carlo A. Favero
Marco Aiolfi
Giorgio Primiceri

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Abstract

This paper explores the extent to which predictability of asset returns could be exploited for dynamic portfolio allocation among several (seven) assets taking model uncertainty explicitly into account.We consider model uncertainty when solving the problem of a representative fund manager who allocates funds between stock and bonds in three geographical areas: Europe, USA and Japan. We consider explicitly model uncertainty by implementing ´thick modelling´ to derive the average portfolio allocation generated by the recursively selected top fifty per cent of models in term of adjusted R-squared The portfolio allocation based on this strategy leads to systematic over-performance with respect to optimal portfolio allocation among several assets is based on the predictions of the best model as selected by the adjusted R-squared . Such over performance is mainly attributable to a reduction in the volatility of the returns on the selected portfolios. Thick modelling leads also to systematic replication, but not to over-performance, of a typical benchmark\ portfolio for our asset allocation problem.

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Paper provided by IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University in its series Working Papers with number 197.

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Handle: RePEc:igi:igierp:197

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This paper has been announced in the following NEP Reports:

NEP-ALL-2002-05-14 (All new papers)

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Rosario Dell'Aquila & Elvezio Ronchetti, 2004. "Stock and Bond Return Predictability : The Discrimination Power of Model Selection Criteria," Cahiers du DÃ©partement d'EconomÃ©trie 2004.05, Département d'Econométrie, Université de Genève. [Downloadable!]
Marco Aiolfi & Carlo Ambrogio Favero, . "Model Uncertainty, Thick Modelling and the predictability of Stock Returns," Working Papers 221, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University. [Downloadable!]
Other versions:
- Aiolfi, Marco & Favero, Carlo A, 2003. "Model Uncertainty, Thick Modelling and the Predictability of Stock Returns," CEPR Discussion Papers 3997, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
M. Hashem Pesaran & Christoph Schleicher & Paolo Zaffaroni, 2008. "Model Averaging in Risk Management with an Application to Futures Markets," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
Other versions:
- Pesaran, M.H. & Schleicher, C. & Zaffaroni, P., 2008. "Model Averaging in Risk Management with an Application to Futures Markets," Cambridge Working Papers in Economics 0808, Faculty of Economics, University of Cambridge. [Downloadable!]
- Pesaran, M. Hashem & Schleicher, Christoph & Zaffaroni, Paolo, 2009. "Model averaging in risk management with an application to futures markets," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 280-305, March. [Downloadable!] (restricted)
Hashem Pesaran & Paolo Zaffaroni & Banca d'Italia), 2004. "Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management," Money Macro and Finance (MMF) Research Group Conference 2004 101, Money Macro and Finance Research Group. [Downloadable!]
Other versions:
- M. Hashem Pesaran & Paolo Zaffaroni, 2004. "Model Averaging and Value-at-Risk based Evaluation of Large Multi Asset Volatility Models for Risk Management," IEPR Working Papers 04.3, Institute of Economic Policy Research (IEPR). [Downloadable!]
- Pesaran, M Hashem & Zaffaroni, Paolo, 2005. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi-Asset Volatility Models for Risk Management," CEPR Discussion Papers 5279, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
- M. Hashem Pesaran & Paolo Zaffaroni, 2004. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi Asset Volatility Models for Risk Management," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]

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