The relative importance of competition to contagion:evidence from the digital currency market

How does the valuation change of an industry leader influence its competitors?Does it induce a competitive effect or a contagion effect?What are the driving forces of such influences?We attempted to answer these questions within digital currency markets.We found that both close and distant competitors against an industry leader experience high competitive effects,while moderate competitors experience high contagion effects.Next,we empirically demonstrated how this Ushaped pattern reduces to a linear relationship depending on the industry concentration.Lastly,we identified eight distinct information categories from a social media platform of the industry leader and compared the influence of the eight information categories on the industry leader’s competitors.Our analysis suggests that the relative importance of the competitive effect to the contagion effect in the industry depends on the category of the information.

Margin trading, short selling, and bond yield spread

Using a quasi-natural experiment, this study examines the effects of margin trading and short selling on bond yield spread in China. It finds that both margin trading and short selling can reduce bond yield spread. Additionally, it finds that margin trading lowers firms' debt ratios and increases their credit ratings, which explains the reduced spread. In other words, margin trading can impact investors' decisions by revealing positive information about a firm.Another finding is that short selling lowers the bond yield spread by decreasing earnings management, suggesting that short selling has an impact on investors' decisions through its effect on corporate governance. Our results suggest that margin trading transmits positive information and short selling impacts firms' policies. These results provide support for future regulations of margin trading and short selling.

Major government customer and management earnings forecasts

This paper examines whether customer base composition in the US,that is,whether a firm's major customers are government entities or publicly traded companies,affects the properties of its management earnings forecasts(MEFs).Using a sample of 1,168 MEFs from 1998 to 2014,we find that firms whose major customers are government entities(i.e.,govemment suppliers)issue more precise and more accurate MEFs than firms whose major customers are public companies(i.e.,corporate suppliers).Moreover,when managers disclose negative information to the market,earnings forecasts issued by government suppliers have greater price impact than those issued by corporate suppliers.Collectively,our empirical results suggest that having major govemment customers has a positive impact on the quality of MEFs.

Toward energy finance market transition:Does China's oil futures shake up global spots market?

China is breaking through the petrodollar system,establishing RMB-dominating crude oil futures market.The country is achieving a milestone in its transition to energy finance market internationalization.This study explores the price leadership of China's crude oil futures and identifies its price co-movement to uncover whether it truly shakes up the global oil spots market.First,we find that for oil spots under different gravities,China's oil futures is only a net price information receiver from light-,medium-,and heavy-gravity oil spots,but it has a relatively stronger price co-movement with these three spots.Second,for oil spots under different sulfur contents,China's oil futures still has weak price leadership in sweet,neutral,and sour oil spots,but it has strong co-movement with them.Third,for oil spots under different geographical origins,China's oil futures shows price leadership in East Asian and Australian oil spots at the medium-and longrun time scales and strong price co-movement with East Asian,Middle Eastern,Latin American and Australian oil spots.China's oil futures may not have good price leadership in global spots market,but it features favorable price co-movement.

Learning from Neighbors and Differentiating Export Quality

This paper explores how learning from neighboring firms affects new exporters' product quality. It builds a Bayesian learning model to study how new exporters revise their prior beliefs about foreign customers' preferences for product quality from neighboring pioneering exporters. The model shows that a new exporter improves its product quality when it receives a positive quality-preference signal from its neighbors. The learning process of a firm depends on the number of neighbors, the level and heterogeneity of their export quality, and its own prior knowledge of the market. Highly disaggregated firm–product–country level transaction data provide robust evidence for this. The results also suggest that the impact of neighboring signals on a new exporter's quality can be channeled through the importation of high-quality intermediate inputs and more fixed investment. Learning effects are heterogeneous across firms and learning can influence other aspects of export performance.