Risk Management under Omega Measure

Metel, Michael R.; Pirvu, Traian A.; Wong, Julian

doi:10.3390/risks5020027

Cited by 9 publications

(11 citation statements)

References 13 publications

(14 reference statements)

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“…is the absolute semideviation (from the mean). Its use as a risk measure is examined in [13]. [1] introduced the Omega ratio with benchmark t as…”

Section: Omega Ratios and Stochastic Dominancementioning

confidence: 99%

“…Theorem 4.3 in [2] provides an integral condition for (1+γ cv , 1+γ cx )-SD. In particular, for γ cv = 0, (13) and…”

Section: Omega Ratios and Combined Concave And Convex Stochastic Domimentioning

confidence: 99%

“…[8] introduce a linear programming algorithm to find an optimal portfolio maximizing the Omega ratio. [9] and [10] also discuss portfolio optimization problems using Omega ratio as a performance measure. In [9] it is shown that for some benchmarks this is an ill-posed problem in their setting, as the optimal Omega ratio may be infinite.…”

Section: Introductionmentioning

confidence: 99%

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On Consistency of the Omega Ratio with Stochastic Dominance Rules

Klar

Müller

2018

Innovations in Insurance, Risk- And Asset Management

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Omega ratios have been introduced in [1] as a performance measure to compare the performance of different investment opportunities. It does not have some of the drawbacks of the famous Sharpe ratio. In particular, it is consistent with first order stochastic dominance. Omega ratios also have an interesting relation to expectiles, which found increasing interest recently as risk measures. There is some confusion in the literature about consistency with respect to second order stochastic dominance. In this paper, we clarify this and extend it to a consistency result with respect to stochastic dominance of order 1 + γ recently introduced in [2] and generalizing the classical concepts of stochastic dominance of first and second order. Several examples illustrate the usefulness of this result. Finally, some consistency results for even more general stochastic dominance rules are shown, including the concept of -almost stochastic dominance introduced in [3].

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“…is the absolute semideviation (from the mean). Its use as a risk measure is examined in [13]. [1] introduced the Omega ratio with benchmark t as…”

Section: Omega Ratios and Stochastic Dominancementioning

confidence: 99%

“…Theorem 4.3 in [2] provides an integral condition for (1+γ cv , 1+γ cx )-SD. In particular, for γ cv = 0, (13) and…”

Section: Omega Ratios and Combined Concave And Convex Stochastic Domimentioning

confidence: 99%

See 1 more Smart Citation

On Consistency of the Omega Ratio with Stochastic Dominance Rules

Klar

Müller

2018

Innovations in Insurance, Risk- And Asset Management

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“…Normal, Log-normal, Student-t and Generalized Pareto distributions. Metel et al (2017) is an illuminating paper as it is the first to notice the correspondence between Sharpe and Omega ratio under jointly elliptic distributions of returns. Compared to our work, their proof is more convoluted and does not emphasize the important fact that elliptic distributions satisfy some symmetry properties that validates the proof.…”

Section: Related Workmentioning

confidence: 99%

Omega and Sharpe Ratio

2019

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“…In her paper on predicting prices for high profile tech stocks, Nguyet Nguyen (Nguyen (2017)) applies the Hidden Markov Model (HMM) to forecast stock prices and develop an HMM-based trading strategy. Michael R. Metel, Traian A. Pirvu and Julian Wong (Metel et al (2017)) investigate the Omega Measure and it's use for assessing portfolio performance, as well as similarities and differences with the Sharpe Ratio when determining the optimal portfolio for different return classes. Finally, Nick Costanzino and I (Cohen and Costanzino (2017)) look at incorporating stochastic recovery into the Black-Cox model of bond pricing, with application to credit default swaps.…”

Section: Overviewmentioning

confidence: 99%

Editorial: A Celebration of the Ties That Bind Us: Connections between Actuarial Science and Mathematical Finance

Cohen¹

2018

Risks

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Abstract:In the nearly thirty years since Hans Buhlmann (Buhlmann (1987)) set out the notion of the Actuary of the Third Kind, the connection between Actuarial Science (AS) and Mathematical Finance (MF) has been continually reinforced. As siblings in the family of Risk Management techniques, practitioners in both fields have learned a great deal from each other. The collection of articles in this volume are contributed by scholars who are not only experts in areas of AS and MF, but also those who present diverse perspectives from both industry and academia. Topics from multiple areas, such as Stochastic Modeling, Credit Risk, Monte Carlo Simulation, and Pension Valuation, among others, that were maybe thought to be the domain of one type of risk manager are shown time and again to have deep value to other areas of risk management as well. The articles in this collection, in my opinion, contribute techniques, ideas, and overviews of tools that specialists in both AS and MF will find useful and interesting to implement in their work. It is also my hope that this collection will inspire future collaboration between those who seek an interdisciplinary approach to risk management.

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Risk Management under Omega Measure

Cited by 9 publications

References 13 publications

On Consistency of the Omega Ratio with Stochastic Dominance Rules

On Consistency of the Omega Ratio with Stochastic Dominance Rules

Omega and Sharpe Ratio

Editorial: A Celebration of the Ties That Bind Us: Connections between Actuarial Science and Mathematical Finance

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