Portfolio Performance Gauging in Discrete Time Using a Luenberger Productivity Indicator

Olivier Brandouy (), Walter Briec, Kristiaan Kerstens and Ignace Van de Woestyne
Additional contact information
Walter Briec: University of Perpignan, LAMPS
Ignace Van de Woestyne: HUB University College Brussels

No 2008-ECO-12, Working Papers from IESEG School of Management

Abstract: This paper proposes a pragmatic, discrete time indicator to gauge the performance of portfolios over time. Integrating the shortage function (Luenberger, 1995) into a Luenberger portfolio productivity indicator (Chambers, 2002), this study estimates the changes in the relative positions of portfolios with respect to the traditional Markowitz mean-variance efficient frontier, as well as the eventual shifts of this frontier over time. Based on the analysis of local changes relative to these mean-variance and higher moment (in casu, mean-variance-skewness) frontiers, this methodology allows to neatly separate between on the one hand performance changes due to portfolio strategies and on the other hand performance changes due to the market evolution. This methodology is empirically illustrated using a mimicking portfolio approach (Fama and French 1996; 1997) using US monthly data from January 1931 to August 2007.

Keywords: shortage function; mean-variance; mean-variance-skewness; efficient portfolios; Luenberger portfolio productivity indicator (search for similar items in EconPapers)
JEL-codes: C43 G11 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2008-10, Revised 2009-10
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Portfolio performance gauging in discrete time using a Luenberger productivity indicator (2010)
Working Paper: Portfolio performance gauging in discrete time using a luenberger productivity indicator (2010)
Working Paper: Portfolio performance gauging in discrete time using a Luenberger productivity indicator (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:ies:wpaper:e200812

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