Kin Keung Lai

TL;DR: In this paper, the authors explored the effect of macroeconomic variables on improving the predictive accuracy of corporate bankruptcy prediction with neural networks models based on data from USA firms, and found that neural network models incorporating macroeconomic factors can made a slight improvement on predictive accuracy with comparison to models without the macroeconomic information.

TL;DR: Wang et al. as discussed by the authors examined the threshold effects of financial developments on energy supply structures for 17 energy supply provinces in China observed over 2000-2014, using a non-linear Panel Smooth Transition Regression (PSTR) model.

TL;DR: A new class of generalized convex function is introduced, namely, α-pseudo-univex function, by combining the concepts of pseudo- univex and α-invex functions, and establishes some relationships between vector variational-like inequality problems and vector optimization problems under the assumptions of α- Pseudo-Univex functions.

TL;DR: In this paper, a non-convex optimization problem with some constraints is formulated for portfolio liquidation, and a genetic algorithm is developed to obtain the optimal solution for the above problem, and also illustrate the efficiency of the algorithm.