• Identifying the relative importance of stock characteristics in the UK market

      French, D.; Wu, Yuliang; Li, Y. (2016-03)
      There is no consensus in the literature as to which stock characteristic best explains returns. In this study, we employ a novel econometric approach better suited than the traditional characteristic sorting method to answer this question for the UK market. We evaluate the relative explanatory power of market, size, momentum, volatility, liquidity and book-to-market factors in a semiparametric characteristic-based factor model which does not require constructing characteristic portfolios. We find that momentum is the most important factor and liquidity is the least important based on their relative contribution to the fit of the model and the proportion of sample months for which factor returns are significant. Our evidence supports the view that irrational investor behaviour may drive stock returns.
    • Liquidity skewness in the London Stock Exchange

      Hsieh, T-H.; Li, Y.; McKillop, D.G.; Wu, Yuliang (2018-03)
      We study liquidity on the London Stock Exchange. We find that the average bid-ask spread declines, but that the skewness of the spread increases. These results are robust to firm size, trading volume and price level. Our findings hold when the bid-ask spread is estimated utilising high frequency data. We find that the bid-ask spread prior to earnings announcements dates is significantly higher than that of post earnings announcements, suggesting that asymmetric information has driven the increase in liquidity skewness. We also find that the effect of earnings announcements is more pronounced in the 2007 global financial crisis, consistent with the notion that extreme market downturns amplify asymmetric information. Our overall evidence also implies that increased competition and transparent trading environments limit market makers' abilities to cross-subsidize bid-ask spreads between periods of high and low levels of asymmetric information.
    • To Disclose or To Falsify: The Effects of Cognitive Trust and Affective Trust on Customer Cooperation in Contact Tracing

      Chen, S.J.; Waseem, Donia; Xia, R.Z.; Tran, K.T.; Li, Y.; Yao, J. (2021-04)
      Contact tracing involves collecting people’s information to track the spread of COVID-19 and to warn people who have been in the proximity of infected individuals. This measure is important to public health and safety during the pandemic. However, customers’ concerns about the violation of their privacy might inhibit their cooperation in the contact tracing process, which poses a risk to public safety. This research investigates how to facilitate customers’ cooperative behavior in contact tracing based on cognitive trust and affective trust. The findings show that cognitive trust increases people’s willingness to disclose information and reduces their willingness to falsify it, whereas affective trust increases the willingness for both disclosure and falsification. This research contributes to the literature on customer data privacy by illuminating how cognitive and affective trust distinctly influence cooperative behavior, which has important implications for hospitality businesses.