This paper proposes the concepts of ESG information flows and a predictable framework of ESG flows based on AR process, and studies how ESG information flows are incorporated into and affect a dynamic portfolio with transaction costs. Two methods, called the ESG factor model and the ESG preference model, are considered to embed ESG information flows into a dynamic mean-variance model. The dynamic optimal portfolio can be expressed as a traditional optimal portfolio without ESG information and a dynamic ESG preference portfolio, and the impact of ESG information on optimal trading is explicitly analyzed. The rich numerical results show that ESG information can improve the out-of-sample performance, and ESG preference portfolio has the best out-of-sample performance including the net returns, Sharpe ratio and cumulative return of portfolios, and contribute to reducing risk and transaction costs. Our dynamic trading strategy provides valuable insights for sustainable investment both in theory and practice.

We construct a stock learning index in China A-share market, which is based on a theoretical model of information and investment choice. The higher the learning index value, the more thoroughly the individual stock is learned. Our study shows that a stock with a high learning index will have a lower expected future return compared to a stock with a low learning index. Additionally, decomposition of predictive power shows that the predictive power of the learning index mainly comes from the persistence of its own predictive power, while the rest cannot be explained by changes in the volume of news (proxy for information flow). Moreover, the learning index can explain many market anomalies in China A-share market.

This paper investigates whether and how high-speed rail (HSR) construction affects local bank performance. Using the difference-in-difference method, we find that the city commercial banks (CCBs) significantly experience an overall decrease in ROA after HSR is introduced in the headquarters city. Mechanism analysis suggests that the HSR-driven city connectivity imposes the local CCBs on the intensified banking competition related to capital flows, and governance improvements associated with information flows. HSR exerts more pronounced impacts under higher financial liberalization. The findings are robust to the endogeneity concerns. We highlight the indispensable role of transport infrastructure in banking development.

We examine the impact of institutional investor networks on firm innovation in China. Employing the unexpected departure of mutual fund managers and the inclusion of the Shanghai-Shenzhen 300 index as identifications, we find that institutional investor networks have a positive impact on firm innovation. Specifically, firms that are hold by well-connected institutional investors are motivated to make R&D investments and receive greater patents than their counterparts. This positive influence is more pronounced for non-SOEs and for firms located in less-developed regions, indicating that institutional investor networks act as information flow facilitator and a value certifier to encourage innovation activities.

We document a novel platform effect caused by the emergence of FinTech platforms in financial intermediation. In China, platform distributions of mutual funds emerged in 2012 and grew quickly into a formidable presence. Utilizing the staggered entrance of funds onto platforms, we find a marked increase of performance-chasing, driven by the centralized information flow unique to FinTech platforms. This pattern is further confirmed using proprietary data from a top platform. Examining the platform impact on fund managers, we find that, incentivized by the amplified performance-chasing, fund managers increase risk taking to enhance their probability of getting onto the top ranking.

This paper studies the presence of informed trading in Taiwan stock index options (TXO) and analyzes the informational role of foreign institutions in incorporating information into Taiwan stock index futures (TX). We have found that only the option-induced part (OOI) of the total TX order imbalance can predict future TX prices, and the OOI calculated from open-buy TXO, defined by Ni et al. (2008), provides incremental predictability. This finding shows that the price predictability stems from the information flow resulting from option transactions rather than from liquidity pressure. We conclude further that option transactions from foreign institutions provide the most significant predictability, out-of-the-money option transactions in particular. These empirical results show that option transactions conducted by foreign institutions have played the primary role in conveying the information inherent in the TXO market to the TX market, foreign institutions being delta-informed traders. Retail investors, the major players in both the TXO and TX markets, have done almost nothing of significance with regard to TXO information transmission into the TX market, with the exception of some near-the-money and out-of-the-money options.

This paper explores the determinants of B-share discounts in the Chinese stock market based on a unique regulatory change in 2001. We find that the B-share discounts declined substantially after the lifting of restrictions on foreign ownership in China, but the H-share discount remained virtually unchanged. Using the intraday data, we find that information flows from the B-share markets to the A-share markets increase significantly after the event, because domestic investors rush into the B-share markets. Using various cross-sectional analyses, we also find that relative supply and behavior factors such as relative spread (or liquidity) and relative risk affect the discounts throughout the sample period.

This paper explores the determinants of B-share discounts in the Chinese stock market based on a unique regulatory change in 2001. We find that the B-share discounts declined substantially after the lifting of restrictions on foreign ownership in China, but the H-share discount remained virtually unchanged. Using the intraday data, we find that information flows from the B-share markets to the A-share markets increase significantly after the event, because domestic investors rush into the B-share markets. Using various cross-sectional analyses, we also find that relative supply and behavior factors such as relative spread (or liquidity) and relative risk affect the discounts throughout the sample period.