Negative Binomial Panel Research Articles

Which past returns affect trading volume?

Anecdotal evidence suggests and recent theoretical models argue that past stock returns affect subsequent stock trading volume. We study 3,000 individual investors over a 51 month period to test this apparent link between past returns and volume using several different panel regression models (linear panel regressions, negative binomial panel regressions, Tobit panel regressions). We find that both past market returns as well as past portfolio returns affect trading activity of individual investors (as measured by stock portfolio turnover, the number of stock transactions, and the propensity to trade stocks in a given month). After high portfolio returns, investors buy high risk stocks and reduce the number of stocks in their portfolio. High past market returns do not lead to higher risk taking or underdiversification. We argue that the only explanations for our findings are overconfidence theories based on biased self-attribution and differences of opinion explanations for high levels of trading activity.

User pays

In China, a growing number of Q&A platforms begin to provide paid knowledge services. Trust is a critical factor in user online payment decision, and it also applies to online paid Q&A context where questioners and knowledge contributors are strangers. However, what factors contribute to trust-building and can drive payment decision of questioners remain unknown. In this paper, we explore this question from the perspective of knowledge contributor characteristics and their reputation on the paid Q&A platform, and examine how price moderates the relationship between trust and payment decision. We use negative binomial panel regression model to analyze the data crawled from Zhihu.com and find that knowledge contributors’ reputation and two trustworthiness attributes (ability and integrity) positively influence user payment decision, but benevolence is not influential. Besides, price positively moderates the relationship between user trust and payment decision. Corresponding suggestions are put forward, and theoretical and managerial implications are discussed.