We identify choke points in global production networks as industries bridging flows across global value chains. These industries exhibit low substitutability: US firms exposed to Chinese choke points during the 2022 Covid-19 lockdowns experienced large and persistent sales declines. The Red Sea crisis demonstrates how negative shocks to water transport, a single choke point, propagate throughout the global network. This structural fragility is priced in global stock markets: firms in choke point industries earn annualized benchmark-adjusted returns exceeding 6%. The premium compensates for aggregate consumption risk, as downturns in choke point industries predict lower future US and global consumption growth.

Investors’ prior experiences with a stock substantially affect their willingness to repurchase it. This paper explores the repurchase effect, a psychological bias in which investors are reluctant to repurchase stocks that have appreciated after a prior sale. To quantify this bias, we develop a novel stock-level measure, termed Repur, and investigate its implications for cross-sectional asset pricing. Our findings show that stocks with higher Repur tend to experience reduced future buying pressure from investors, which in turn results in lower subsequent returns. Economically, long-short portfolios based on Repur yield annualized abnormal returns exceeding 23% for equal-weighted and 11% for value-weighted risk-adjusted returns. Further analyses show that the pricing effect of Repur is more pronounced following periods of high investor sentiment, for stocks with greater arbitrage constraints, and for firms with smaller investor bases. Out-of-sample evidence from China confirms the significant pricing impact of the repurchase effect.

We propose the AI Narrative Gap as a novel firm characteristic—the systematic divergence between a firm’s AI strategic narrative intensity and its subsequent AI capital expenditure commitment—and document its capital market consequences. Using Chinese A-share listed firms from 2015 to 2022, we show that firms with a wider AI Narrative Gap attract significantly more optimistic and less accurate analyst earnings forecasts. These distorted expectations, in turn, predict lower subsequent stock returns, lower industry-adjusted abnormal returns, and weaker future accounting performance. A double-sort portfolio placing firms simultaneously in the highest tercile of the AI Narrative Gap and highest tercile of analyst optimism earns a mean return 22.8 percentage points below that of the lowest tercile on both dimensions (t = −5.10). The return reduction in the AI Narrative Gap coefficient is attenuated but not eliminated after controlling for optimism, consistent with a partial expectation-distortion channel. Collectively, these results establish the AI Narrative Gap as a cross-sectionally informative firm characteristic that captures the credibility of a firm’s AI strategic identity, with systematic implications for analyst expectations and asset prices.

We present a novel methodology for constructing portfolios to hedge economic and financial risks arising from climate change. We utilize ChatGPT-4 to identify climate-related conversations during earnings conference calls and connect these time-stamped transcripts with high-frequency stock price data pinpointed to the conversation level. This approach allows us to assess a company’s dynamic exposure to climate change risks by analyzing real-time stock price responses to discussions about climate issues between managers and analysts. Our proposed portfolio, constructed by taking long (short) positions in stocks with positive (negative) market responses to climate conversations, appreciates in value during future periods with negative aggregate climate news shocks. Compared to portfolios constructed using alternative methods, our real-time market response-based portfolios demonstrate superior out-of-sample hedge performance. A key advantage of our approach is its ability to capture time-series and cross-sectional variations in stocks’ rapidly-evolving exposures to climate risk, relying on the timing of when climate-related issues become salient topics that warrant conference call discussions and real-time market responses to such conversations. Additionally, we showcase the versatility of our approach in hedging other types of dynamic risks: namely political risk and pandemic risk.

Using a proprietary database of stock transactions in China, we document significant trading disparities between retail and institutional investors around important macro announcements. These disparities are driven by differences in information positions. We find that before the monthly releases of China’s key monetary aggregates data, institutional investors reduce their stock exposure and shift towards riskier, smaller-cap stocks. In contrast, retail investors increase their stock exposure and avoid riskier stocks. The risk positions of institutional investors are compensated by the pre-announcement premium in smaller stocks. Following the announcements, institutional investors trade in line with news surprises, contributing to price discovery and reinforcing monetary policy transmission into asset prices. Our findings have implications for understanding announcement-related equity premium and for evaluating the general efficiency of stock market in China.

The macroeconomic risk associated with climate change potentially results in a risk premium on asset prices. Using a sample of 11,468 Chinese quasi-municipal bonds from 2014-2021 in 267 cities, this research investigates the impact of climate risk on the credit spreads of quasi-municipal bonds. We employ principal component analysis (PCA) to construct a climate risk index and find that climate risk significantly increases credit spreads by increasing the local government fiscal gap and debt burden. The effect of climate risk is more remarkable for bonds that have shorter maturity and lower corporate ratings, issued by smaller city investment companies and corporations located in regions with stronger environmental regulation, stronger climate risk perception, and better green financial development. A significant relationship is also observed in the eastern regions but not the western regions. This study broadens the scope of quasi-municipal bond credit spread determinants from traditional financial to climate indicators.

This paper investigates the intertemporal relation between expected aggregate stock market returns and conditional variance considering periodic trading breaks. We propose a modified version of Merton’s intertemporal asset pricing model that merges two different processes driving asset prices, (i) a continuous process modeling diffusive risk during the trading day and, (ii) a discontinuous process modeling overnight price changes of random magnitude. Relying on high-frequency data, we estimate distinct premia for diffusive trading volatility and volatility induced by overnight jumps. While diffusive trading volatility plays a minor role in explaining the expected market risk premium, overnight jumps carry a significant risk premium and establish a positive risk-return trade-off. Our study thereby contributes to the ongoing debate on the sign of the intertemporal risk-return relation.

In Chinese culture, digit 8 (4) is taken as lucky (unlucky). We find that the numerological superstition has a profound impact across China’s stock, bond, foreign exchange and commodities markets, affecting asset prices in both the primary and secondary markets. The superstition effect, i.e., the probability of asset price ending with a lucky (unlucky) digit far exceeds (falls short of) what would be expected by chance, is prevalent. The effect is driven by investors’ reliance on superstition as an anchor to face uncertainty in asset pricing and the overoptimism of unsophisticated investors. While the superstition effect does not lead to systemic mispricing for assets traded by sophisticated investors, it implies overpricing for assets involving more unsophisticated investors.

We examine a unique one day lockup constraint in stock markets in China and contribute to the understanding of impact of non-marketability on asset prices. Buyers of Chinese stocks are subject to a one day lockup and cannot sell their shares until the next day, but warrant traders are free of such restrictions. We demonstrate that the lockup creates a price discount relative to stock value implied by warrants. We show that the discount decreases throughout the trading day and that investors tend to purchase stocks when the lockup becomes less binding. The paper provides implications to value illiquid assets.

We investigate the impact of state ownership structure on asset prices and corporate policies. By primarily focusing on China’s corporations, we show that the relationship between expected returns and capital investment varies significantly across state owned enterprises (SOE) and private owned enterprises (POE). A portfolio that longs low investment and shorts high investment firms earns an average annual excess stock return of 5% in the SOE sector. In contrast, there is no relationship between investment and expected returns in the POE sector. We show that the difference in the link between expected returns and investment across SOE and POE firms is driven by their differential exposures to the debt issuance shocks, which captures the monetary supply shocks in China. As SOE firms have easier access to bank loans, the high investment firms in the SOE sector are more able to raise debt despite that debt supply is shrinking, and hence they are less risky. We develop a dynamic model with SOE and POE firms facing different frictions in debt markets. The economic mechanism emphasizes that heterogeneous access to the debt market is an important determinant of equilibrium risk premiums across sectors with different state ownership.