This paper examines the contribution of closing pressure and predatory trading to the formation of the negative settlement price of NYMEX West Texas Intermediate (WTI) Crude Oil futures on April 20, 2020. We construct a theoretical model and show that the eagerness to close long positions,...

I study voluntary disclosure of oligopoly firms when they learn information from asset prices. By disclosing information, a firm incurs a cost of losing competitive advantage to its rivals but benefits from learning from a more informative asset market. Adding a financial market helps the...

In this paper, we study the latent group structure in cryptocurrencies market by forming a dynamic return inferred network with coin attributions. We develop a dynamic covariate-assisted spectral clustering method to detect the communities in dynamic network framework and prove its uniform...

Cryptocurrencies are becoming an attractive asset class and are the focus of recent quantitative research. The joint dynamics of the cryptocurrency market yields information on network risk. Utilizing the adaptive LASSO approach, we build a dynamic network of cryptocurrencies and model the...

Cryptocurrencies return cross-predictability and technological similarity yield information on risk propagation and market segmentation. To investigate these effects, we build a timevarying network for cryptocurrencies, based on the evolution of return cross-predictability and technological...

This paper examines the limit properties of information criteria (such as AIC, BIC, HQIC) for distinguishing between the unit root model and the various kinds of explosive models. The explosive models include the local-to-unit-root model, the mildly explosive model and the regular explosive...

This paper examines regression-adjusted estimation and inference of unconditional quantile treatment effects (QTEs) under covariate-adaptive randomizations (CARs). Datasets from field experiments usually contain extra baseline covariates in addition to the strata indicators. We propose to...

This paper studies a continuous time dynamic system with a random persistence parameter. The exact discrete time representation is obtained and related to several discrete time random coefficient models currently in the literature. The model distinguishes various forms of unstable and explosive...

Cryptocurrencies return cross-predictability yields information on risk propagation and market segmentation. To explore these effects, we build a dynamic network of cryptocurrencies based on the evolution of return cross-predictability and develop a dynamic covariate-assisted spectral clustering...