Covariate balance contributes to improve estimation accuracy for causal inference. This paper achieves optimal covariate balance for continuous treatment by minimizing the distributional difference between the covariates and a specified weighted covariates, which is very different from the...

Stock market prediction provides the decision-making ability to the different stockholders for their investments. Recently, stock technical indicators (STI) emerged as a vital analysis tool for predicting high-dimensional stock data in various studies. However, the prediction performance and...

Covariate balance is frequently-used to identify the balance weights or nuisance parameters for causal inference due to being less likely to produce extreme weights and being more robust. Based on bias decomposition, this paper proposes a covariate balance method for continuous treatment via the...