Results 91 to 100 of about 46,518,871 (255)
Hedging Risks in the Loss-Averse Newsvendor Problem with Backlogging
Mathematics, 2019 This paper studies the optimal order decisions for the loss-averse newsvendor problem with backordering and contributes to the risk hedging issue in the newsvendor model.
Xiaoqing Liu +2 more
doaj +1 more source
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
Crisis, Value at Risk, and Conditional Extreme Value Theory via Garch-Jump Model
, 2010 This study develops a new conditional extreme value theory-based model (EVT) combined with the GARCH-Jump model to forecast extreme risks. This paper utilizes the GARCH-Jump model to asymmetrically feed back the past realization of jump innovation to the
Ze-To, S.
core
On a Multivariate Extension for Copula-Based Conditional Value at Risk
Journal of Statistical Theory and Applications (JSTA)Copula-based Conditional Value at Risk ( $$\textrm{CCVaR}$$ ) is a real-valued tail risk measure for multivariate random vectors defined through conditioning on a copula level set.
Andres Mauricio Molina Barreto
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
Monte Carlo estimation of value-at-risk, conditional value-at-risk and their sensitivities
, 2011 Value-at-risk and conditional value at risk are two widely used risk measures, employed in the financial industry for risk management purposes. This tutorial discusses Monte Carlo methods for estimating value-at-risk, conditional value-at-risk and their ...
Liu, Guangwu +3 more
core +1 more source
Advanced Robotics Research, EarlyView.This review brings together 20 publications describing 11 robotic system families developed for instrument handling, sterile‐package opening, supply delivery, and operating room logistics. Perception is becoming more capable through deep learning and language‐guided control, but autonomy remains limited, evidence is largely laboratory‐based, and no ...
Eugenia Mawuenya Akpo +4 more
wiley +1 more source
BarekengThis study aims to estimate Conditional Value at Risk (CVaR) for insurance company stock portfolios using a machine learning approach to improve the accuracy of financial risk measurement under extreme market conditions.
Purwanto Purwanto, Agna Olivia
doaj +1 more source
Advanced Science, EarlyView.The adipocyte MKK3–p38β axis emerges as an adaptive stress‐response pathway during obesity. Human visceral adipose tissue analyses, adipocyte‐specific mouse models, and primary adipocytes show that the MKK3–p38β axis supports insulin responsiveness by restraining p70S6K‐dependent inhibitory IRS1 feedback and preserving AKT–GLUT4 signaling. This pathway
Edgar Bernardo +20 more
wiley +1 more source
Crisis, Value at Risk and Conditional Extreme Value Theory via the NIG + Jump Model
, 2012 This study develops a new conditional extreme value theory-based model (EVT) combined with the NIG + Jump model to forecast extreme risks. This paper utilizes the NIG + Jump model to asymmetrically feedback the past realization of jump innovation to the ...
Ze-To, S.
core +1 more source