Evaluating Fund Performance by Compromise Programming with Linear‐Quadratic Composite Metric: An Actual Case on The CaixaBank in Spain

Abstract

This paper proposes an additive measure on the basis of compromise programming to evaluate fund performance from multiple criteria, of which the most usual are profitability and risk. This proposal is motivated by the fact that compromise programming is a sound decision support model to obtain scores of alternatives by minimizing weighted distances to an ideal point, the weights reflecting the investor's preferences for the criteria. To define the distance objective function, the linear-quadratic composite metric is used, which combines advantages of linear and non-linear objective functions. A critical advantage of compromise programming for fund performance evaluation is that the model can be extended to more than two financial criteria while other measures currently used (either ratio-based or leverage-based measures) only consider two criteria, say, profitability and risk. In the application, three investor's profiles are defined, which involve different weighting systems and lead to different fund rankings. These rankings are compared with domination relationships, the latter formulating if a fund is dominated or non-dominated by convex combinations of other funds. Numerical tables are provided with data, computational process and results, which are analysed.

Characterizing compromise solutions for investors with uncertain risk preferences

“…As a result, the utility of the Ballestero's bounding theorem roots in the possibility to precisely delimit the efficient set of portfolios according to the particular bias for risk of an investor. This theorem has been recently used in portfolio selection research (Ballestero and Pla-Santamaria, 2004;Ballestero, 2007;Bravo et al, 2012). Next we characterize this theorem to the selection of the best portfolio according to particular preferences.…”

“…Subsequent works have followed two separated ways. On the one hand, some of them have successfully applied this theorem for selecting portfolios for mutual funds (Ballestero and Pla-Santamaria, 2004) and for eliciting balanced solutions by using an additive linear-quadratic composite metric (Ballestero, 2007;Bravo et al, 2012). On the other hand, a number of related works have recently mentioned Ballestero's theorem as an important contribution to portfolio selection (Ehrgott et al, 2004;Steuer et al, 2007;Xidonas et al, 2012).…”

The Determinants of the Performance of Precious Metal Mutual Funds

“…Consequently, a reliable and rigorous method for evaluating and rating the performance of managed funds is now urgently needed (Chen and Lin 2006). Two main research streams on mutual fund performance appraisal are identified in the literature: the first stream includes methods based on Capital Asset Pricing Model (CAPM) and utility theory, and the second stream involves operation research methods such as data envelopment analysis (DEA) (Bravo et al 2012).…”

“…Moreover, Jensen's α may be used to measure the difference between the actual and the expected return of a fund. An approach based on utility theory using compromise programming has been proposed by Bravo et al (2012).…”

Data-Driven Decision-Making and Its Application to the Corporate Cash Management Problem

“…Within a single objective framework, one suitable method to solve this problem is dynamic programming, which was initially proposed by Eppen and Fama (1969) and Neave (1970), and more recently followed by Penttinen (1991), Chen and Simchi-Levi (2009), and Melo and Bilich (2013). On the other hand, compromise programming (CP) and goal programming (GP) (Zeleny, 1982;Yu, 2013;Ballestero and Romero, 1998;Ballestero and Pla-Santamaria, 2004;Bravo, Ballestero, and Pla-Santamaria, 2012;Pla-Santamaria and Bravo, 2013) are possible approaches to deal with multiple objectives. When the CMP is formulated as a linear/quadratic program, we can benefit from state-of-the-art mathematical programming solvers to obtain optimal solutions.…”