Results 1 to 10 of about 148,735 (300)
Dependent conditional value-at-risk for aggregate risk models [PDF]
Heliyon, 2021 Risk measure forecast and model have been developed in order to not only provide better forecast but also preserve its (empirical) property especially coherent property. Whilst the widely used risk measure of Value-at-Risk (VaR) has shown its performance
Bony Parulian Josaphat, Khreshna Syuhada
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Optimization with Multivariate Conditional Value-at-Risk Constraints [PDF]
Operations Research, 2013 For many decision-making problems under uncertainty, it is crucial to develop risk-averse models and specify the decision makers' risk preferences based on multiple stochastic performance measures (or criteria). Incorporating such multivariate preference rules into optimization models is a fairly recent research area.
Nilay Noyan, Gábor Rudolf
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Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics [PDF]
Operations Research, 2012 We discuss linear regression approaches to the estimation of law-invariant conditional risk measures. Two estimation procedures are considered and compared; one is based on residual analysis of the standard least-squares method, and the other is in the spirit of the M-estimation approach used in robust statistics.
So Yeon Chun +2 more
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Maximum Varma Entropy Distribution with Conditional Value at Risk Constraints [PDF]
Entropy, 2020 It is well known that Markowitz’s mean-variance model is the pioneer portfolio selection model. The mean-variance model assumes that the probability density distribution of returns is normal. However, empirical observations on financial markets show that
Chang Liu, Chuo Chang, Zhe Chang
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Vector-valued multivariate conditional value-at-risk
Operations Research Letters, 2018 In this study, we propose a new definition of multivariate conditional value-at-risk (MCVaR) as a set of vectors for discrete probability spaces. We explore the properties of the vector-valued MCVaR (VMCVaR) and show the advantages of VMCVaR over the existing definitions given for continuous random variables when adapted to the discrete case.
Simge Küçükyavuz
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Equity Portfolio Optimization Using Mean-CVaR Method Considering Symmetric and Asymmetric Autoregressive Conditional Heteroscedasticity [PDF]
تحقیقات مالی, 2020 Objective: Risk management is one of the most important areas of study in finance, and its vital role in the field has attracted the attention of managers and investors in in various sectors of the industry.
Reza Raei +2 more
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Energy risk measurement and hedging analysis by nonparametric conditional value at risk model
Frontiers in Energy Research, 2022 The accurate measurement and management of energy risk have become important issues of the economic development and energy security for all countries. The existing literature generally adopts the Value at Risk (VaR).
Ling Li, Guopeng Hu
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Individual Investors’ Attention to Left Tail Risk [PDF]
Journal of Asset Management and Financing, 2020 Objective: Left tail risk shows the probability of the occurrence of undesirable events. Investors who undergo the left tail risk are likely to experience considerable negative returns since the left tail risk oftentimes continues to the next period ...
Mahshid Shahrzadi, Daryoosh Forooghi
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Does the COVID-19 pandemic matter for market risks across sectors in Vietnam?
Heliyon, 2021 Vietnam has been considered one of the few countries that put the COVID-19 pandemic under control and successfully achieved solid economic growth in 2020. However, the national economy has been hit hard by the pandemic in 2021.
Chi Minh Ho +3 more
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Mean-standard deviation-conditional value-at-risk portfolio optimization [PDF]
Mathematics and Modeling in Finance, 2023 The use of variance as a risk measure is limited by its non-coherentnature. On the other hand, standard deviation has been demonstrated as acoherent and effective measure of market volatility. This paper suggests theuse of standard deviation in portfolio
Maziar Salahi +2 more
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