Results 231 to 240 of about 141,957 (262)

Forecasting value at risk and conditional value at risk using option market data

Journal of Forecasting, 2020
AbstractWe forecast monthly value at risk (VaR) and conditional value at risk (CVaR) using option market data and four different econometric techniques. Independent from the econometric approach used, all models produce quick to estimate forward‐looking risk measures that do not depend from the amount of historical data used and that, through the ...
Annalisa Molino, Carlo Sala
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Vom Value at Risk zum Conditional Value at Risk

2003
In diesem hinfuhrenden Abschnitt werden mehr oder weniger zufallig ausgewahlte Zitate von Beschreibungen bzw. Definitionen des Value at Risk aufgefuhrt. Sie stellen keine Voraussetzungen fur die nachfolgenden Ausfuhrungen dar, sie mogen vielmehr die Vielfalt der Aspekte und deren Breite verdeutlichen.
Werner Dinkelbach, Andreas Kleine
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Conditional value‐at‐risk beyond finance: a survey

International Transactions in Operational Research, 2019
AbstractA large number of problems involve making decisions in an uncertain environment and, hence, with unknown outcomes. Optimization models aimed at controlling the trade‐off between risk and return in finance have been widely studied since the seminal work by Markowitz in 1952.
Filippi, C., Guastaroba, G., Speranza, M. G.   +2 more
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Asymptotic representations for importance-sampling estimators of value-at-risk and conditional value-at-risk

Operations Research Letters, 2010
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Lihua Sun, L. Jeff Hong
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Efficient portfolio optimization with Conditional Value at Risk

Proceedings of the International Multiconference on Computer Science and Information Technology, 2010
The portfolio optimization problem is modeled as a mean-risk bicriteria optimization problem where the expected return is maximized and some (scalar) risk measure is minimized. In the original Markowitz model the risk is measured by the variance while several polyhedral risk measures have been introduced leading to Linear Programming (LP) computable ...
Wlodzimierz Ogryczak, Tomasz Sliwinski
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Nonlinear prediction of conditional percentiles for value-at-risk

Proceedings of the IEEE/IAFE 1999 Conference on Computational Intelligence for Financial Engineering (CIFEr) (IEEE Cat. No.99TH8408), 2003
We propose, implement and evaluate an approach to predicting conditional distribution tail percentiles, which corresponds to value-at-risk (VaR) when applied to financial asset return series. Our approach differs from current methods for measuring VaR in two basic ways. Firstly, while the standard variance-covariance framework assumes that asset return
Isaac J. Chang, Andreas S. Weigend
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Value-at-Risk and Conditional Value-at-Risk in Optimization Under Uncertainty

2018
This work is related to the use of various risk measures in the context of robust- and reliability-based optimization. We start from the definition of risk measure and its formal setting, and then, we show how different risk functional definitions can lead to different approaches to the problem of optimization under uncertainty.
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Conditional value-at-risk: optimization algorithms and applications

Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520), 2002
This article has outlined a new approach for the simultaneous calculation of value-at-risk (VaR) and optimization of conditional VaR (CVaR) for a broad class of problems. We have shown that CVaR can be efficiently minimized using LP techniques. Our numerical experiments show that CVaR optimal portfolios are near optimal in VaR terms, i.e., VaR cannot ...
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Multitrend Conditional Value at Risk for Portfolio Optimization

IEEE Transactions on Neural Networks and Learning Systems
Trend representation has been attracting more and more attention recently in portfolio optimization (PO) via machine learning methods. It adopts concepts and phenomena from the field of empirical and behavioral finance when little prior knowledge is obtained or strict statistical assumptions cannot be guaranteed.
Zhao-Rong Lai, Cheng Li 0018, Xiaotian Wu, Quanlong Guan, Liangda Fang   +4 more
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A general framework of importance sampling for value-at-risk and conditional value-at-risk

Proceedings of the 2009 Winter Simulation Conference (WSC), 2009
Lihua Sun, L. Jeff Hong
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