Increasingly, consumers depend on social information channels, such as user-posted online reviews, to make purchase decisions. These reviews are assumed to be unbiased reflections of other consumers' experiences with the products or services. While extensively assumed, the literature has not...

We compared the predictive performance of a series of machine learning and traditional methods for monthly CDS spreads, using firms' accounting-based, market-based and macroeconomics variables for a time period of 2006 to 2016. We find that ensemble machine learning methods (Bagging, Gradient...

In this paper, using news reflected in the stock market as a benchmark for the public information of suppliers, we find significant incremental information revelation in the credit default swap market of the customers. The information revelation is more significant during the periods when either...

In this paper, using newly available CDS positions data compiled from DTCC and the supply chain hierarchical position obtained from networking methodology, we examine whether and how investors can use CDS contracts to manage the heightened operational risk due to upstream supply chain...

This paper provides a measurement of framing effects in the stock market by using actual market open trading data, and provide a test of this new firm-special behavioral characteristic. We adopt univariate and bivariate portfolio-level analyses with seminal rational and behavioral factors, to...

We examine the relationship between CDS spreads and annual report readability in this paper. Our results suggest that annual report readability is negatively related to CDS spreads. Furthermore, on the information supply side, the effect of readability on CDS spreads is more concentrated on...