The utilization of wind energy, as a booming technology in the field of renewable energies, has been highly regarded around the world. Quantification of uncertainties associated with accurate wind speed forecasts is essential for regulating wind power generation and integration. However, it...

Based on upper echelon theory, we employ machine learning to explore how CEO characteristics influence corporate violations using a large-scale dataset of listed firms in China for the period 2010-2020. Comparing ten machine learning methods, we find that eXtreme Gradient Boosting (XGBoost)...

We develop a dynamic model to simultaneously characterize the liquidity demand and supply in limit order book. The joint dynamics is modelled in a unified Vector Functional AutoRegressive (VFAR) framework. We derive a closed-form maximum likelihood estimator under sieves and establish asymptotic...