Results 71 to 80 of about 44,115,319 (295)
Advanced Robotics Research, EarlyView.Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
CVaR in Measuring Sector's Risk on the Croatian Stock Exchange
Business Systems Research, 2018 Background: In this paper the well-known risk measurement method Conditional Value-at-Risk (CVaR) is applied to the Croatian stock market to estimate the risk for 8 sectors in Croatia.
Aljinović Zdravka, Trgo Andrea
doaj +1 more source
Time-varying conditional Johnson SU density in value-at-risk (VaR) methodology [PDF]
Stylized facts on financial time series data are the volatility of returns that follow non-normal conditions such as leverage effects and heavier tails leading returns to have heavier magnitudes of extreme losses.
Cayton, Peter Julian A., Mapa, Dennis S.
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LLM‐Integrated Human–Robot Interaction System for Microrobots
Advanced Robotics Research, EarlyView.This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley +1 more source
A Method on Solving Multiobjective Conditional Value-at-Risk [PDF]
, 2004 This paper studies Conditional Value-at-Risk (CVaR) with multiple losses. We introduce the concept of α-CVaR for the case of multiple losses under the confidence level vector α. The α-CVaR indicates the conditional expected losses corresponding to the α-VaR. The problem of solving the minimal α-CVaR results in a multiobjective problem (MCVaR). In order
Min Jiang, Qiying Hu, Zhiqing Meng
openaire +1 more source
Inference for conditional value-at-risk of a predictive regression
The Annals of Statistics, 2020 The authors deal with the inference problem of conditional value-at-risk under a linear predictive regression model. Denote by \(Y\) the return of an asset and let \(X = (X_1, \dots, X_k)^{\top}\) be a collection of predictors (market variables or risk factors).
He, Y., Hou, Y., Peng, L., Shen, H.
openaire +5 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
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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
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