We propose an actor-critic reinforcement learning (RL) algorithm for the optimal execution problem. We consider the celebrated Almgren-Chriss model in continuous time and formulate a relaxed stochastic control problem for execution under an entropy regularized mean-quadratic variation objective....

We propose a novel methodology for modeling and forecasting multivariate realized volatilities using graph neural networks. This approach extends the work of Zhang et al. [2022] (Graph-based methods for forecasting realized covariances) and explicitly incorporates the spillover effects from...

Renewable energy has been a worldwide interest due to a growing energy demand as well as a mounting concern over the hostile impacts from traditional fuels. One of a direction for future renewable energy is the use of biofuel. In this research, we initially apply the K-means algorithm to...

A significant part of highway and street congestion is produced by work zones. Depending on the type of construction and/or rehabilitation activity, street capacity could be significantly decreased, or the street could be completely closed. The work zone generates traffic delays in the street...

World cultural heritage (WHS) is of great significance to promoting the sustainable development of cities, and history culture is very important to achieve the goal of sustainable development. The purpose of this paper is to construct a cultural heritage evaluation system and to explore and...