Almost Stochastic Dominance and stocks for the long run

Levy, Moshe

doi:10.1016/j.ejor.2007.12.017

Cited by 37 publications

(15 citation statements)

References 45 publications

(46 reference statements)

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“…However, the relaxation of this assumption is conditional: The area of violation (i.e. the area where the cumulative probability distribution of B is above that of A) must be very small compared with the total area of the two distributions (Basu et al 2011;Levy 2009Levy , 2012. The SD decision-making criteria consider both risk and potential outcomes with the cumulative distribution function.…”

Section: Stochastic Dominance Decision-making Criteriamentioning

confidence: 99%

“…SD is the most general approach to decision-making under uncertain circumstances (Levy 2009). Additionally, SD can be employed irrespective of whether the distributions of the choices under consideration are normally distributed or not (Basu et al 2011;Levy 2009). First-degree stochastic dominance (FSD) assumes that the utility function of the decision-maker U(x) increases with x, U'(x)>0.…”

Section: Stochastic Dominance Decision-making Criteriamentioning

confidence: 99%

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Life cycle versus balanced funds: An emerging market perspective

Louw

Schalkwyk

Reyers

2017

SAJEMS

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Background: Inadequate retirement savings is an international challenge. Additionally, individuals are not cognisant of how asset allocation choices ultimately impact retirement savings. Life cycle and balanced funds are popular asset allocation strategies to save towards retirement. However, recent research is questioning the efficacy of life cycle funds that switch to lower risk asset classes as retirement approaches.Aim: The purpose of this study is to compare the performance of life cycle funds with balanced funds to determine whether either dominates the other. The study compares balanced and life cycle funds with similar starting asset allocations as well as those where the starting asset allocations differ.Setting: The study has a South African focus and constructs funds using historical data for the main local asset classes; that is, equity, fixed income and cash, as well as a proxy for foreign equity covering the period 1986–2013.Method: The study makes use of Monte Carlo simulations and bootstrap with replacement, and compares the simulated outcomes using stochastic dominance as decision-making criteria.Results: The results indicate that life cycle funds fail to dominate balanced funds by first-order or almost stochastic dominance when funds have a similar starting asset allocation. It is noteworthy that there are instances where the opposite is true, that is, balanced funds dominate life cycle funds. These results highlight that while the life cycle funds provide more downside protection, they significantly suppress the upside potential compared to balanced funds. When the starting asset allocations of the balanced and life cycle funds differ, the stochastic dominance results are inconsistent as to the efficacy of the life cycle fund strategies considered.Conclusion: The study shows that whether one fund is likely to dominate the other is strongly dependent on the underlying asset allocation strategies of the funds. Additionally, the length of the glide path and the risk and return characteristics of the investable universe are also likely to influence the findings.

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Section: Stochastic Dominance Decision-making Criteriamentioning

confidence: 99%

Section: Stochastic Dominance Decision-making Criteriamentioning

confidence: 99%

Life cycle versus balanced funds: An emerging market perspective

Louw

Schalkwyk

Reyers

2017

SAJEMS

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“…9 [1] and [27] provide two alternative formulations of ASSD. Here we employ Levy's [27] formulation, which is more straightforward.…”

Section: Afsd Algorithmmentioning

confidence: 99%

“…Here we employ Levy's [27] formulation, which is more straightforward. Levy [27] employs integration by parts and the fact that u(x) is concave to prove that if…”

Section: Afsd Algorithmmentioning

confidence: 99%

Almost Stochastic Dominance and Efficient Investment Sets

Levy¹

2012

AJOR

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A major drawback of Mean-Variance and Stochastic Dominance investment criteria is that they may fail to determine dominance even in situations when all "reasonable" decision-makers would clearly prefer one alternative over another. Levy and Leshno [1] suggest Almost Stochastic Dominance (ASD) as a remedy. This paper develops algorithms for deriving the ASD efficient sets. Empirical application reveals that the improvement to the efficient sets implied by ASD is substantial (64% reduction for FSD). Direct expected utility maximization shows that investment portfolios excluded from the ASD efficient set would not have been chosen by any investors with reasonable preferences.

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“…Another drawback of the basic theory of SD is nicely illustrated by a stylised example from Levy (2009) -try to use SD criteria to rank two prospects, one of which pays out $0.5 with a probability of 0.01 and $1 million with a probability of 0.99, and the other of which pays out $1 for sure. While it would seem that virtually any investor would prefer the former, SD cannot be established.…”

Section: Introductionmentioning

confidence: 99%

Spaces for Agreement: A Theory of Time-Stochastic Dominance

Dietz

Matei

2013

SSRN Journal

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Many investments involve both a long time-horizon and risky returns. Making investment decisions thus requires assumptions about time and risk preferences. Such assumptions are frequently contested, particularly in the public sector, and there is no immediate prospect of universal agreement. Motivated by these observations, we develop a theory and method of finding 'spaces for agreement'. These are combinations of classes of discount and utility function, for which one investment dominates another (or 'almost' does so), so that all decision-makers whose preferences can be represented by such combinations would agree on the option to be chosen. The theory is built on combining the insights of stochastic dominance on the one hand, and time dominance on the other, thus offering a nonparametric approach to inter-temporal, risky choice. We go on to apply the theory to the controversy over climate policy evaluation and show with the help of a popular simulation model that, in fact, even tough carbon emissions targets would be chosen by almost everyone, barring those with arguably 'extreme' preferences.

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Almost Stochastic Dominance and stocks for the long run

Cited by 37 publications

References 45 publications

Life cycle versus balanced funds: An emerging market perspective

Life cycle versus balanced funds: An emerging market perspective

Almost Stochastic Dominance and Efficient Investment Sets

Spaces for Agreement: A Theory of Time-Stochastic Dominance

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