Results 81 to 90 of about 44,115,319 (296)
Optimizing the Conditional Value-at-Risk in Revenue Management
SSRN Electronic Journal, 2013 Many service industries use revenue management to balance demand and capacity. The assumption of risk-neutrality lies at the heart of the classical approaches, which aim at maximizing expected revenue. In this paper, we give a comprehensive overview of the existing approaches, most of which were only recently developed, and discuss the need to take ...
Gönsch, Jochen, Hassler, Michael
openaire +3 more sources
Extreme Value at Risk and Expected Shortfall during Financial Crisis [PDF]
This paper investigates Value at Risk and Expected Shortfall for CAC 40, S&P 500, Wheat and Crude Oil indexes during the 2008 financial crisis. We show an underestimation of the risk of loss for the unconditional VaR models as compared with the ...
D. Dupre +3 more
core
Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots
Advanced Robotics Research, EarlyView.This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou +4 more
wiley +1 more source
Media Statistika, 2019 Stock is the most popular type of financial asset investment. Before buying a stock, an investor must estimate the risks which will be received. Value at Risk (VaR) is one of the methods that can be used to measure the level of risk.
Mutik Dian Prabaning Tyas +2 more
doaj +1 more source
Filtered Extreme Value Theory for Value-At-Risk Estimation [PDF]
Extreme returns in stock returns need to be captured for a successful risk management function to estimate unexpected loss in portfolio. Traditional value-at-risk models based on parametric models are not able to capture the extremes in emerging markets ...
Yilmazer, Sait +2 more
core
Advanced Robotics Research, EarlyView.DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano +3 more
wiley +1 more source
GFC-Robust Risk Management Under the Basel Accord Using Extreme Value Methodologies [PDF]
In McAleer et al. (2010b), a robust risk management strategy to the Global Financial Crisis (GFC) was proposed under the Basel II Accord by selecting a Value-at-Risk (VaR) forecast that combines the forecasts of different VaR models.
Michael McAleer +3 more
core +4 more sources
Minimum capital requirement and portfolio allocation for non-life insurance: a semiparametric model with Conditional Value-at-Risk (CVaR) constraint. [PDF]
Comput Manag Sci, 2023 Staino A +3 more
europepmc +1 more source
Risks, 2018 There has been much discussion in the literature about how central measures of equity risk such as standard deviation fail to account for extreme tail risk of equities.
Robert J. Powell +2 more
doaj +1 more source
Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source