Multistage risk premiums in portfolio optimization

Kopa, Miloš; Petrová, Barbora

doi:10.14736/kyb-2017-6-0992

Cited by 4 publications

(12 citation statements)

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“…The definition of the SSD relationship uses comparisons of either twice cumulative distribution functions (see, e.g., Branda, 2015) or expected utilities (see, e.g., Levy, 2006). Alternatively, it is possible to define the SSD relationship using cumulative quantile functions or conditional value at risk (see Ogryczak and Ruszczyński, 2002; Kopa and Chovanec, 2008). Definition SSD (Kopa and Chovanec, 2008).…”

Section: Portfolio Efficiency: Typesmentioning

confidence: 99%

Measuring the overall efficiency of SRI and conventional mutual funds by a diversification‐consistent DEA model

Bilbao-Terol

Arenas-Parra

Bilbao‐Terol

2021

Int Trans Operational Res

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This paper presents an application of data envelopment analysis (DEA) based approaches to assess the relative financial and nonfinancial efficiency of mutual funds (MFs). Our approach measures corporate sustainability (CS) of the MFs from the rating process carried out by social agencies on the constituent firms. We have modified the raw scores of the firms invested in by the MFs in order to overcome the compensatory effect when the MFs invested in both "good" and "bad" firms. For this purpose, we have used prospect theory in such a manner that the original scores awarded to the firms are modified by applying a value function. Three extensions of Branda's model are formulated. The first model measures financial efficiency, the second model measures CS efficiency and is an output-oriented DEA model, and, the third is a DEA model for measuring overall efficiency of the MFs. In the last step of the proposed methodology, the set of overallefficient MFs is ranked applying technique for order of preference by similarity to ideal solution to the two DEA scores corresponding to the two partial DEA models. The risk and return measures have been chosen so that the proposed models are consistent with the second-order stochastic dominance relation. Therefore, under a finite number of equiprobable scenarios for the rates of return, a set of conditional value at risk for several confidence levels are used as inputs of the models that consider the financial performance. The proposed approach is illustrated with real data on a set of 144 French MFs, 31 marketed as socially responsible investment MFs.

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Section: Portfolio Efficiency: Typesmentioning

confidence: 99%

Measuring the overall efficiency of SRI and conventional mutual funds by a diversification‐consistent DEA model

Bilbao-Terol

Arenas-Parra

Bilbao‐Terol

2021

Int Trans Operational Res

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“…To produce results about the sensitivity of the solution distance with respect to the tree distance, we propose three portfolio models very well known in the literature that discusses stochastic optimization applied to financial problems, see e. g. [2,5,6,19]. The three models are: the maximization of the average value-at-risk (AV@R), the maximization of the expected wealth and the minimization of the difference between the expected wealth and its AV@R. In particular, the third model has recently been studied in [6] and [4].…”

Section: Portfolio Selection Modelsmentioning

confidence: 99%

“…When the stochastic random variable and the optimal decision evolve along a sequence of temporal stages, the framework becomes a multistage stochastic optimization, see [17]. Financial problems require models that very well interface with multistage stochastic optimization because they typically need to find an optimal portfolio allocation in financial assets whose future return is uncertain, see [2,3,5,6,19]. Therefore, the implementation of a multistage stochastic model follows the characterization of the stochastic environment in which the problem is defined.…”

Section: Introductionmentioning

confidence: 99%

Multistage multivariate nested distance: An empirical analysis

Vitali¹

2018

Kybernetika

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“…Moreover, it is well known that multistage stochastic optimization is particularly helpful for addressing portfolio management problems, see Dupačová et al (2002) for an overview of the topic and the recent applications of Vitali et al (2017), Kopa and Petrová (2017), Consigli et al (2018a), Kopa et al (2018), Moriggia et al (2019) and references therein. For this reason, we also formulate and solve a multistage portfolio selection problem.…”

Section: Introductionmentioning

confidence: 99%

“…,Vitali et al (2017),Kopa and Petrová (2017),Consigli et al (2018a, b),Kopa et al (2018),Moriggia et al (2019),Rusý and Kopa (2018), we formulate a multistage portfolio selection problem.…”

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confidence: 99%

Evaluation of scenario reduction algorithms with nested distance

et al. 2020

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Multistage stochastic optimization is used to solve many real-life problems where decisions are taken at multiple times. Such problems need the representation of stochastic processes, which are usually approximated by scenario trees. In this article, we implement seven scenario reduction algorithms: three based on random extraction, named Random, and four based on specific distance measures, named Distance-based. Three of the latter are well known in literature while the fourth is a new approach, namely nodal clustering. We compare all the algorithms in terms of computational cost and information cost. The computational cost is measured by the time needed for the reduction, while the information cost is measured by the nested distance between the original and the reduced tree. Moreover, we also formulate and solve a multistage stochastic portfolio selection problem to measure the distance between the optimal solutions and between the optimal objective values of the original and the reduced tree.

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Multistage risk premiums in portfolio optimization

Abstract: Institute of Mathematics of the Czech Academy of Sciences provides access to digitized documents strictly for personal use. Each copy of any part of this document must contain these Terms of use.

Cited by 4 publications

References 14 publications

Measuring the overall efficiency of SRI and conventional mutual funds by a diversification‐consistent DEA model

Measuring the overall efficiency of SRI and conventional mutual funds by a diversification‐consistent DEA model

Multistage multivariate nested distance: An empirical analysis

Evaluation of scenario reduction algorithms with nested distance

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