On the use of conditional expectation in portfolio selection problems

Sergio Ortobelli, Noureddine Kouaissah and Tomáš Tichý ()
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Sergio Ortobelli: University of Bergamo
Noureddine Kouaissah: University of Bergamo
Tomáš Tichý: Technical University Ostrava

Annals of Operations Research, 2019, vol. 274, issue 1, No 23, 530 pages

Abstract: Abstract In this paper, we examine the use of conditional expectation, either to reduce the dimensionality of large-scale portfolio problems or to propose alternative reward–risk performance measures. In particular, we focus on two financial problems. In the first part, we discuss and examine correlation measures (based on a conditional expectation) used to approximate the returns in large-scale portfolio problems. Then, we compare the impact of alternative return approximation methodologies on the ex-post wealth of a classic portfolio strategy. In this context, we show that correlation measures that use the conditional expectation perform better than the classic measures do. Moreover, the correlation measure typically used for returns in the domain of attraction of a stable law works better than the classic Pearson correlation does. In the second part, we propose new performance measures based on a conditional expectation that take into account the heavy tails of the return distributions. Then, we examine portfolio strategies based on optimizing the proposed performance measures. In particular, we compare the ex-post wealth obtained from applying the portfolio strategies, which use alternative performance measures based on a conditional expectation. In doing so, we propose an alternative use of conditional expectation in various portfolio problems.

Keywords: Conditional expectation; Large-scale portfolio selection; Performance measures; Return approximation; Heavy tailed distribution (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (8)

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DOI: 10.1007/s10479-018-2890-3

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