This paper proposes asymmetric GARCH-Jump models that synthesize autoregressive jump intensities and volatility feedback in the jump component. Our results indicate that these models provide a better fit for the dynamics of the equity returns in the US and emerging Asian markets, irrespective whether the volatility feedback is generated through a common GARCH multiplier or a separate measure of volatility in the jump intensity function. We also find that they can capture several distinguishing features of the return dynamics in emerging markets, such as, more volatility persistence, less leverage effects, fatter tails, and greater contribution and variability of the jump component.

IPO auctions, which provide an impartial way of determining IPO pricing and share allocations, offer a natural setting for examining whether institutional investors possess private information, and for measuring how valuable their information is. Analyzing detailed bidding data from Taiwan’s discriminatory (pay-as-bid) auctions, we find that, relative to retail investors, institutional investors tend to bid higher in auctions when IPO shares are more valuable, and that underpricing is larger in auctions with relatively higher institutional bids. These results imply that institutional investors are better informed about IPO value, and that they obtain higher information rents when they bid higher relative to retail investors. We estimate the value of institutional investors’ private information to be worth about 8.68% of return, which is the extra rate of return they command on their informational advantages over retail investors.