Modeling futures market risk simultaneously influenced by macro low-frequency information and daily risk factors is a valuable challenge. We propose a new general framework for it based on the flexible GARCH-MIDAS model. It uses a skewed t distribution to describe the asymmetry of long and short...

I exploit deep learning techniques trained on a set of common accounting items and constructed to mimic features of the human brain to predict future earnings. I show that this model offers incremental explanatory power in predicting future earnings and in estimating the associated implied cost...

We study the impact of government-led incentive systems by examining a staggered reform in the Chinese state-owned enterprise (SOE) performance evaluation policy. To improve capital allocative efficiency, in 2010, regulators switched from using return on equity (ROE) to economic value added...