This dissertation consists of two chapters in asset pricing. The first chapter studies the segmentation between stock and corporate bond markets. I investigate how active mutual fund and ETF investors bridge this segmentation by facilitating information transmission across the two markets. I show that active investors have within-market informational advantages: changes in active holdings and cross-asset holdings predict future returns, whereas passive flows do not. Across markets, active investors enhance information efficiency by accelerating the incorporation of stock-market information into bond returns, as reflected in the weakened predictability of future bond returns from past stock returns. As complementary evidence, a higher active ratio in ownership and a higher active ratio in cross-asset holdings are associated with stronger return comovement between a firm's stock and bond, reflecting greater integration between the two markets. I identify two channels through which this effect operates: (1) information coordination through cross-asset holdings, which is stronger among investment-grade firms where baseline segmentation is greater and the benefits of information sharing are larger; and (2) mitigation of selling frictions, which is more pronounced following negative news when short-sale constraints impede price discovery. These results highlight the importance of active management in enhancing cross-asset price discovery and market integration. In the second chapter, I study how information and inventory effects jointly determine return predictability from retail and total order flow. I build a model that combines the asymmetric information impact of investors with the inventory effect of market makers to analyze how lagged order flow can forecast future returns. The model illustrates that the difference in predictive power between retail and total order flow can be attributed to the varying informativeness of different investor groups. The focus of this chapter is to empirically test how market makers' varying inventory capacity affects this predictive power. While previous literature has theoretically demonstrated that the predictive power of past returns is positive and increases with a market maker's risk aversion, such a monotonic relationship requires specific model parameter constraints and lacks empirical support. My framework suggests that when predictability remains positive, the magnitude increases when the market maker has lower risk-bearing capacity, but this monotonic relationship is only within a certain range. Specifically, when the market maker is extremely unwilling to provide liquidity, return predictability can turn negative, as the price impact channel dominates. I empirically test this theoretical prediction using data from stocks in the banking sector and the results align with the model. The rationale is that these stocks exhibit the strongest positive correlation with the market maker's business, and therefore they have the lowest inventory capacity for these stocks. This finding is supported by the observation that negative predictability becomes more pronounced in times of higher market volatility or for stocks with lower liquidity.
