Using a momentum threshold autoregression model, we find evidence showing that there is an asymmetrical mean reversion behavior in return on equity (ROE). Results show that the speed of adjustment of ROE towards the long-term mean is slower in the ROE increasing regimes than in the ROE decreasing regimes. Additional results indicate that investor earnings optimism is significantly related to change in abnormal ROE. These results are consistent with predictions from catering theory.

Traditional data sources do not have institutional holding data on a daily basis. Because of this, most prior empirical studies of institutional herding have focused on quarterly or annual data. The problem, however, with using quarterly or annual data on institutional holdings is that these data may not reveal institutional herding if it occurs over a shorter time interval. For this study, we make use of data from the Taiwan Stock Exchange (TSE). Unlike traditional data sources, the TSE provides daily institutional holdings information. The use of this detailed data allows us to make more interesting analysis and inferences. In this study, we examine the relationship between institutional ownership changes and returns localized around analysts’ earnings forecast release events. Analysis of institutional ownership and return data around the earnings release event allows us to investigate institutional herding and feedback behavior in a different level. Our major results are as follows: (1) there exists a relation between company specific attributes and institutional herding, (2) observed changes in institutional ownership and contemporaneous return are mainly the results of inter-day price impact of herding, (3) institutional investors show evidence of being informed traders in buying but not selling.

This paper compares the empirical performances of statistical projection models with those of the Black–Scholes (adapted to account for skew) and the GARCH option pricing models. Empirical analysis on S&P500 index options shows that the out-of-sample pricing and projected trading performances of the semi-parametric and nonparametric projection models are substantially better than more traditional models. Results further indicate that econometric models based on nonlinear projections of observable inputs perform better than models based on OLS projections, consistent with the notion that the true unobservable option pricing model is inherently a nonlinear function of its inputs. The econometric option models presented in this paper should prove useful and complement mainstream mathematical modeling methods in both research and practice.

This paper empirically analyzes bidding behavior and information asymmetries of stock auctions using a discriminatory auction model framework. Analyzing stock auctions using auction theory is important because it provides a logical framework for explaining observable behaviors and a solid foundation for empirical testing. Because of limited availability of stock auction data, existing empirical research based on auction theory focus mainly on treasury auctions. Away from the treasury markets, however, there is a significant paucity of literature on this subject. In this study, we make use of a detailed stock auction data set from the Taiwan Stock Exchange to empirically examine the behaviors of the Taiwan stock auction market within the framework of the auction theory. Our results show that the level of competition, the dispersion of opinion among bidders, and the bidder’s risk aversion are significant in determining auction prices. Results also show that if the offering prices are set equal to the average offering prices, the first-day post-initial public offering abnormal return will be equal to zero. Additionally, we find institutional bidders possess superior bidding skills compared to small bidders and that underwriter’s characteristics influence the bidding results.

Results of research on whether changes in earnings can predict future stock returns are inconclusive. We add to this debate by using long-term data from 1871 to 2004 to examine the predictive power of changes in earnings in periods of intrinsic bubbles and in periods absent intrinsic bubbles. Our results show that accounting for bubbles is important in whether changes in earnings can predict future stock returns. In periods of no bubble, we find that changes in earnings Granger-cause future returns, whereas in periods of bubble, this Granger causality from changes in earnings to future returns cannot be found. We conclude that changes in earnings can predict future stock returns, but only in periods absent bubbles.

Private equity placement data allow us to determine whether sophisticated investors can uncover the true value of firms. This can be done by defining sophisticated investors as those who meet the stringent participation requirements of the private equity market. Our results show private equity issuing firms overstate their earnings in the quarter preceding private equity placement announcements and that sophisticated investors do not ask for a fair discount when purchasing the shares of the private issuing firms. We also find evidence showing that the reversal of the effects of pre-issue earnings management is a significant determinant of the long-term performance of private issues. Results further show that post-issue stock performance and operating performance of firms using “aggressive” earnings management significantly underperform those using more “conservative” earnings management.