Results 151 to 160 of about 12,123 (304)
Characterizing Higher‐Order Ross More Risk Aversion by Comparison of Risk Compensation
International Studies of Economics, EarlyView.ABSTRACT This paper characterizes higher‐order Ross more risk aversion by means of risk compensation rather than the traditional risk premium. Our approach extends the willingness‐to‐accept (WTA) framework of Denuit and Eeckhoudt (2013) to a broader class of risk changes.
Zhen Huang, Guoqiang Tian, Yougong Tian
wiley +1 more source
Journal of Applied Econometrics, EarlyView.ABSTRACT We present four novel tests of equal predictive accuracy and encompassing á Pitarakis (2023, 2025) for factor‐augmented regressions. Factors are estimated using cross‐section averages (CAs) of grouped series and our theoretical findings are empirically relevant: asymptotic normality, robustness to an overspecification of the number of factors,
Alessandro Morico, Ovidijus Stauskas
wiley +1 more source
System for Automating the Database Normalization Process
As data volumes grow rapidly, efficient database management has become critical for organizations. Relational databases play an essential role in ensuring data integrity, enabling complex queries, and supporting various applications, including financial,
Яремко, Соломія +1 more
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Journal of Applied Econometrics, EarlyView.ABSTRACT Double/debiased machine learning (DML) uses for estimating an average treatment effect (ATE) a double‐robust score function that relies on the prediction of nuisance functions, such as the propensity score, which is the probability of treatment assignment given covariates.
Daniele Ballinari, Nora Bearth
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A Joint Test of Unconfoundedness and Common Trends
Journal of Applied Econometrics, EarlyView.ABSTRACT We introduce an overidentification test of two alternative assumptions to identify the average treatment effect on the treated in a two‐period panel data setting: unconfoundedness and common trends. Under unconfoundedness, treatment assignment and post‐treatment outcomes are independent, conditional on control variables and pre‐treatment ...
Martin Huber, Eva‐Maria Oeß
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Foundations of continuous-time recursive utility : differentiability and normalization of certainty equivalents [PDF]
, 2009 This paper relates recursive utility in continuous time to its discrete-time origins and provides a rigorous and intuitive alternative to a heuristic approach presented in [Duffie, Epstein 1992], who formally define recursive utility in continuous time ...
Seifried, Frank Thomas, Kraft, Holger
core
The needle study: Machine learning as a new method for case‐finding in celiac disease
Journal of Pediatric Gastroenterology and Nutrition, EarlyView.Abstract Objectives Despite a well‐defined diagnostic work‐up, uncertainties persist regarding celiac disease (CeD) detection strategies in the general population. Machine learning (ML) algorithms offer promise in aiding medical decision‐making on clinical data.
Chiara Maria Trovato +9 more
wiley +1 more source
Advances in Position‐Momentum Entanglement: A Versatile Tool for Quantum Technologies
Laser &Photonics Reviews, EarlyView.Position–momentum entanglement constitutes a high‐dimensional continuous‐variable resource in quantum optics. Recent advances in its generation, characterization, and control are reviewed, with emphasis on spontaneous parametric down‐conversion and modern measurement techniques.
Satyajeet Patil +6 more
wiley +1 more source
Rigorous Electromagnetic Quasinormal‐Mode Method Made Easy for Users
Laser &Photonics Reviews, EarlyView.We present a method that combines numerical techniques with accurate approximations to enable simple and ultrafast computations of the scattered field based on quasinormal modes expansions. The method is made available in the open‐source package MANlite implemented within COMSOL.
Tong Wu, Philippe Lalanne
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CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel.
Yining Hua +4 more
wiley +1 more source