Results 11 to 20 of about 3,170,301 (265)
Deep learning of value at risk through generative neural network models: The case of the Variational auto encoder [PDF]
MethodsX, 2023 We present in this paper a method to compute, using generative neural networks, an estimator of the “Value at Risk” for a financial asset. The method uses a Variational Auto Encoder with an 'energy' (a.k.a. Radon-Sobolev) kernel.
Pierre Brugière, Gabriel Turinici
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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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On multivariate extensions of Value-at-Risk [PDF]
Journal of Multivariate Analysis, 2013 In this paper, we introduce two alternative extensions of the classical univariate Value-at-Risk (VaR) in a multivariate setting. The two proposed multivariate VaR are vector-valued measures with the same dimension as the underlying risk portfolio. The lower-orthant VaR is constructed from level sets of multivariate distribution functions whereas the ...
Areski Cousin, Elena Di Bernadino
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Determining Systemic Risk of Banks, Financial Services, and Insurance Firms of Pakistan
JISR Management and Social Sciences & Economics, 2018 This paper contributes on the literature of systemic risk by investigating the extent of financial distress injected by banks, financial services, and insurance firms in the financial system of Pakistan.
Shumaila Zeb, Abdul Rashid
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Value-at-Risk Versus Non Value-at-Risk Traders [PDF]
SSRN Electronic Journal, 2009 In the paper, I simulate the games with a joint presence of 95% VaR-rule and return-rule groups of agents in the game. Simulations highlighted the level of omniscience, next being the rule, which agents follow at the decision-making, and the third the presence of liquidity agents in the game.
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Procyclicality in tradeable credit risk: Consequences for South Africa
South African Journal of Economic and Management Sciences, 2018 Background: Tradeable credit assets are vulnerable to two varieties of credit risk: default risk (which manifests itself as a binary outcome) and spread risk (which arises as spreads change continuously).
Dirk Visser, Gary W. van Vuuren
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On the global minimization of the value-at-risk [PDF]
Optimization Methods and Software, 2004 21 pages, 1 ...
Jong-Shi Pang, Sven Leyffer
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Tsallis value-at-risk: generalized entropic value-at-risk
Probability in the Engineering and Informational Sciences, 2022 AbstractMotivated by Ahmadi-Javid (Journal of Optimization Theory Applications, 155(3), 2012, 1105–1123) and Ahmadi-Javid and Pichler (Mathematics and Financial Economics, 11, 2017, 527–550), the concept of Tsallis Value-at-Risk (TsVaR) based on Tsallis entropy is introduced in this paper. TsVaR corresponds to the tightest possible upper bound obtained
Zhenfeng Zou, Zichao Xia, Taizhong Hu
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Empirical Issues in Value-at-Risk [PDF]
ASTIN Bulletin, 2001 AbstractFor the purpose of Value-at-Risk (VaR) analysis, a model for the return distribution is important because it describes the potential behavior of a financial security in the future. What is primarily, is the behavior in the tail of the distribution since VaR analysis deals with extreme market situations.
Wielhouwer, J.L., Bams, D.
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Implications of Heavy-Tailed Loss Distributions for Reinsurance and Solvency Capital: Evidence from US and Egyptian Insurance Markets (2020-2023) [PDF]
Maǧallaẗ Al-Buḥūṯ Al-TiǧāriyyaẗThis study aims to compare the performance of heavy-tailed probability distributions in modelingextreme insurance losses, with a focus on their implications for risk capital assessment and reinsurance pricing.
محمود فخرى محمد حماد
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