Portfolio selection with qualitative input

Anant Chiarawongse, Seksan Kiatsupaibul, Sunti Tirapat and Benjamin Van Roy

Journal of Banking & Finance, 2012, vol. 36, issue 2, 489-496

Abstract: We formulate a mean–variance portfolio selection problem that accommodates qualitative input about expected returns and provide an algorithm that solves the problem. This model and algorithm can be used, for example, when a portfolio manager determines that one industry will benefit more from a regulatory change than another but is unable to quantify the degree of difference. Qualitative views are expressed in terms of linear inequalities among expected returns. Our formulation builds on the Black–Litterman model for portfolio selection. The algorithm makes use of an adaptation of the hit-and-run method for Markov chain Monte Carlo simulation. We also present computational results that illustrate advantages of our approach over alternative heuristic methods for incorporating qualitative input.

Keywords: Portfolio selection; Bayesian inference; Markov chain Monte Carlo; Black-Litterman model; Hit-and-run algorithm (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:36:y:2012:i:2:p:489-496

DOI: 10.1016/j.jbankfin.2011.08.005

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