Optimal Multistage Defined-Benefit Pension Fund Management

Consigli, Giorgio; Moriggia, Vittorio; Benincasa, Elena; Landoni, Giacomo Maria; Petronio, Filomena; Vitali, Sebastiano; Tria, Massimo Di; Skoric, Mario; Uristani, Angelo

doi:10.1007/978-3-319-61320-8_13

Cited by 10 publications

(20 citation statements)

References 18 publications

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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%

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Multistage multivariate nested distance: An empirical analysis

Vitali¹

2018

Kybernetika

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Section: Portfolio Selection Modelsmentioning

confidence: 99%

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%

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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“…Comprehensive collections are in Ziemba and Mulvey (1998) and Zenios and Ziemba (2006), Zenios and Ziemba (2007). More recent developments are in Kopa and Rusỳ (2020) that formulated an ALM model to tackle the consumer loan problem; in Consigli et al (2011), , Consigli and Moriggia (2014), and in Consigli et al (2017) that analysed a Property & Casualty insurance fund; and in other papers that discussed the pension fund from different point of view such as the issuer of the pension fund, see e.g Vitali et al (2017) and Devolder et al (2020), and the individual pension problem, see e.g. Consigli (2007), , Kopa et al (2018) and Consigli et al (2019).…”

Section: Introductionmentioning

confidence: 99%

“…McKendall et al (1994), Davis (2000), Guiso et al (2002), Hardy (2003), Gollier (2008), Broeders et al (2009). Following this path, our aim is to propose an extension of the model proposed in Consigli et al (2017) and in Moriggia et al (2019) to include a relatively new class of investment opportunities, i.e. the investment certificates.…”

Section: Introductionmentioning

confidence: 99%

Pension fund management with investment certificates and stochastic dominance

Vitali

Moriggia

2020

Ann Oper Res

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This paper considers an extension of the common asset universe of a pension fund to investment certificates. Investment certificates are a class of structured products particularly interesting for their special payoff structures and they are acquiring relevancy in the worldwide markets. In fact, some subclasses of certificates offer loss protection and show high liquidity and, thus, they can be very appreciated by pension fund managers. We consider the problem of a pension fund manager who has to implement an Asset and Liability Management model trying to achieve a long-term sustainability. Therefore, we formulate a multi-stage stochastic programming problem adopting a discrete scenario tree and a multi-objective function. We propose a technique to price highly structured products such as investment certificates on a discrete scenario tree. Finally, we solve the investment problem considering some investment certificate types both in term of payoff structure and protection level, and we test whether they are preferred or not to standard hedging contract such as put options. Moreover, we test the inclusion of first-order and second-order stochastic dominance constraints on multiple stages with respect to a benchmark portfolio. Numerical results show that the portfolio composition reacts to the inclusion of the stochastic dominance constraints, and that the optimal portfolio is efficiently able to reach several targets such as liquidity, returns, sponsor’s extraordinary contribution and funding gap.

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Optimal Multistage Defined-Benefit Pension Fund Management

Cited by 10 publications

References 18 publications

Multistage multivariate nested distance: An empirical analysis

Multistage multivariate nested distance: An empirical analysis

Evaluation of scenario reduction algorithms with nested distance

Pension fund management with investment certificates and stochastic dominance

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