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.

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.

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.