We study how financial markets integrate news about pollution abatement costs into firm values. Using China’s automation of pollution monitoring, we find that firms with factories in bad-news cities---cities that used to report much lower pollution than the automated reading---see significant declines in stock prices. This is consistent with the view that investors expect firms in high-pollution cities to pay significant adjustment and abatement costs to become “greener.” However, the efficiency with which such information is incorporated into prices varies widely---while the market reaction is quick in the Hong Kong stock market, it is considerably delayed in the mainland ones, resulting in a drift. The equity markets expect most of these abatement costs to be paid by private firms and not by state-owned enterprises, and by brown firms and not by green firms.

This paper provides evidence that some seasoned equity offerings are motivated by public information. We test this channel in the supply chain setting, where supplier managers are more attentive than outside investors to customer news. We find that supplier firms are more likely to issue seasoned equity when their customer firms have negative earnings surprises. The results are mitigated when there is common scrutiny on the customer-supplier firm pairs by outside investors and analysts. Furthermore, long-run stock market performance appears to be worse for firms that issue seasoned equity following the negative earnings surprise of their customer firms.

Exploiting a unique market-oriented media reform initiated in 1996 in China, we investigate the role of media environment in affecting firm behaviour. We find robust evidence that market-oriented media environment is conductive to firm innovation, with the reform promoting patent quantity and quality substantially. The effect is more pronounced for firms with higher information asymmetry. Matching firm data with 1.3 million news reports, we find the market-oriented media reform significantly improves the criticalness and unbiasedness of news coverage and shapes an innovation-friendly environment. Our findings highlight economic outcomes of relaxing media control and underline substantial gains from deepening the reform.

Why is price momentum absent in China? Since momentum is commonly considered arising from investors’ under-reaction to fundamental news, we decompose monthly stock returns into news- and non-news-driven components and document a news day return continuation along with an offsetting non-news day reversal in China. The non-news day reversal is particularly strong for stocks with high retail ownership, relatively less recent positive news articles, and limits to arbitrage. Evidence on order imbalance suggests that stock returns overshoot on news days due to retail investors' excessive attention-driven buying demands, and mispricing gets corrected by institutional investors on subsequent non-news days. To avoid this tug-of-war in stock price, we use a signal that directly captures the recent news performance and re-document a momentum-like underreaction to fundamental news in China.

We construct a daily Chinese Housing Market Sentiment Index by applying GPT-4o to Chinese news articles. Our method outperforms traditional models in several validation tests, including a test based on a suite of machine learning models. Applying this index to household-level data, we find that after monetary easing, an important group of homebuyers (who have a college degree and are aged between 30 and 50) in cities with more optimistic housing sentiment have lower responses in non-housing consumption, whereas for homebuyers in other age-education groups, such a pattern does not exist. This suggests that current monetary easing might be more effective in boosting non-housing consumption than in the past for China due to weaker crowding-out effects from pessimistic housing sentiment. The paper also highlights the need for complementary structural reforms to enhance monetary policy transmission in China, a lesson relevant for other similar countries. Methodologically, it offers a tool for monitoring housing sentiment and lays out some principles for applying generative AI models, adaptable to other studies globally.

The relationship between corporate Environmental, Social, and Governance (ESG) performance and its value has garnered increasing attention in recent times. However, the utilization of ESG scores by rating agencies, a critical intermediary in the linkage between ESG performance and value, presents challenges to ESG research and investment as a result of inherent subjectivity, hysteresis, and discrepant coverage. Fortunately, news can provide an objective, timely, and socially relevant perspective to augment prevailing rating frameworks and alleviate their shortcomings. This study endeavors to scrutinize the influence of ESG-related news on the Chinese stock market, to showcase its efficacy in supplementing the appraisal of ESG performance. The study's findings demonstrate that (1) the stock market is significantly impacted by ESGrelated news; (2) ESG-related news with different attributes (sentiments and sources) have notably diverse effects on the stock market; and (3) the heterogeneity among enterprises (industries and ownership structures) affects their ability to withstand ESGrelated news shocks. This study contributes novel insights to the comprehensive and objective assessment of corporate ESG performance and the management of its media image by providing a vantage point on ESG-related news.

The general financial theory predicts a carbon premium, as brown stocks bear greater uncertainty under climate transition. However, a contrary green premium has been identified in China, as evidenced by the return spread between green and brown sectors. The aggregated climate transition sentiment, measured from news data using a large language model, explains 12%-33% of the variability in the anomalous alpha. This factor intensifies after China announced its national commitments. The sentiment-driven green premium is attributed to speculative trading by retail investors targeting green “concept stocks.” Additionally, the discussion highlights the advantages of large language models over lexicon-based sentiment analysis.

We find that investors react more favorably to corporate announcements of share repurchases, SEOs, earnings, dividend changes, and acquisitions if the announcement is made immediately prior to or on holidays. These announcements are associated with more positive reactions for favorable events and less negative reactions for unfavorable events. This effect is robust to controls for market conditions and a selection bias, is accompanied by subsequent reversals, and is present in several international markets. Our findings suggest that predictable individual mood changes can cause biases in market reactions to firm-specific news.

We examine how pre-announcement weather conditions near a firm’s major institutional in- vestors affect stock market reactions to firms’ earnings announcements. We find that unpleasant weather experienced by institutional investors leads to more delayed market responses to sub- sequent earnings news. Moreover, unpleasant weather of institutional investors is associated with higher earnings announcement premia. The influence of institutional investors’ weather is robust after controlling for New York City weather, extreme weather conditions, and firm local weather. Additional cross-sectional evidence suggests that the strength of this weather effect is related to institutional investors’ trading behavior.

Many corporate executives believe blockchain technology is broadly scalable and will achieve mainstream adoption, yet there is little evidence of significant shareholder value creation associated with corporate adoption of blockchain technology. We collect a broad sample of firms that invest in blockchain technology and examine the stock price reaction to the “first” public revelation of this news. Initial reac- tions average close to +13% and are followed by reversals over the next 3 months. However, we report a striking differ- ence based on the credibility of the investment. Blockchain investments that are at an advanced stage or are con- firmed in subsequent financial statements are associated with higher initial reactions and little or no reversal. The results suggest that credible corporate strategies involving blockchain technology are viewed favorably by investors.