Correspondence: Jérôme Teïletche, University of Paris–Dauphine, CEREG, Place du Maréchal de Lattre de Tassigny, 75775 Paris Cedex 16, France. Tel: +33 1 44 05 4257; E-mail: jerome.teiletche@dauphine.fr

¹is a PhD student in the Department of Economics at the Massachusetts Institute of Technology. He has previously acted as a consultant for investment banks and IT companies in the US and Europe.

²is a senior quantitative analyst for SGAM AI, alternative investment company of Société Générale group, and Associated Professor of Finance at Paris-Dauphine University. He holds a PhD in Economics and has widely published in professional and academic journals, including Journal of Empirical Finance and Journal of Alternative Investments. Prior to joining SGAM AI, he was previously Senior Quantitative Analyst at IXIS CIB in charge of stock, credit and hedge funds and an economist at the French Ministry of Finance.

Received 2 August 2007; Revised 2 August 2007.

Abstract

Alternative assets are gaining increasing importance in investors' portfolios. One of their defining characteristic is their poor liquidity, which often translates into an inherent smoothing process of the returns. For asset allocation purposes, this feature has to be seriously addressed as it leads to a severe underestimation of the variance of returns and their correlation with other (standard) assets. In this paper, in order to deal with practical issues, we extend previous researches that model the smoothing process as a moving-average one in several directions: (i) we propose a correction for the case of numerous illiquid assets; (ii) we investigate the implications of the standard practice of fitting autoregressive models in place of moving-average models for the correction of the returns variance; and (iii) we provide a generalisation to the case where the returns process is jointly governed by smoothing and true (economically) time-dependent behaviour. All the theoretical results are illustrated empirically with applications to US real estate and venture capital indexes.