Knowledge that Transforms

Using hand-collected data from Form Ds on executives in venture capital (VC)-backed private firms, I show that VC-driven top management changes lead to a significantly greater quantity and quality of innovation, which potentially occurs through new management teams hiring more and higher quality inventors. My evidence demonstrates that both founder replacements and non-founder management changes are associated with enhanced innovation. Further, adding top managers with general managerial skills enhances innovation, whereas changing managers with a prior technical background does not. Finally, top management changes lead to the adoption of an exploitative (rather than explorative) innovation search strategy by private firms.

This study examines the effects of trade liberalization on municipal financing costs. Using the granting of permanent normal trade relations (PNTR) to China as an exogenous shock, we find that U.S. counties that are more exposed to trade liberalization issue bonds with significantly higher tax-adjusted yield spreads. Moreover, these counties pay higher gross spreads and are less likely to issue bonds after PNTR. We also show that secondary market yield spreads increase significantly in response to the U.S. granting of PNTR to China. In addition, we provide evidence that a reduction in debt serving capacity serves as a channel underlying the trade shock effects. Our findings highlight the costs of trade liberalization for public finance.

We investigate the impact of implicit government guarantees (IGGs) on the trading behavior of retail stock investors for non-default firms, using China’s first corporate bond default in March 2014 as a negative shock to public expectations of IGGs. Our difference-in-differences analysis shows that, following the Chaori default shock, retail investors withdraw from high-default-risk firms that have not yet defaulted. This outcome is not attributed to industry, geographical or supply-chain contagions, declining stock prices, worsened financial metrics, or merely a seasonal effect. The effect is more pronounced for firms with preexisting larger retail ownership breadth or higher stock trading turnovers, for non-state-owned enterprises, and for firms with less sustainable earnings. When the initial default shows signs of a bailout, retail investors’ withdrawal partially reverses. Overall, the diminishment of IGGs seems to have reduced the moral hazard of retail stock investors and encouraged them to focus more on firms’ fundamentals, potentially enhancing the capital allocation efficiency in China’s stock market in the long run.

We present a methodology for detecting flash crashes by identifying short-term V-shaped price reversals. Our approach, based on drift burst test statistics, aligns with the SEC’s forensic definition of market access rule violations, highlighting its potential as a market surveillance tool. Flash crashes have become more frequent over the past decade and are typically accompanied by high volumes, high volatility, and an increase in odd-lot trades. They are more likely to occur following periods of high volumes, elevated price impact, low volatility, and heightened algorithmic activity.

This paper empirically examines how listed non-financial firms use the “call option” feature of one of the most important financial assets, available-for-sale securities, as earnings manipulation tools owing to bad-news-hoarding motives. In 2007, China set its first accounting standards for financial instruments, which classify financial assets based on the highly subjective “managerial holding intention” criterion. We find that holding available-for-sale securities is positively associated with the likelihood of stock price crashes in Chinese listed firms. The main effect is more pronounced under lax external regulation and lower information transparency. It is further accentuated when CEOs have lower educational backgrounds, weaker competence in managing core business activities, or face greater performance pressures. Our findings indicate that, in typical emerging markets, fair value accounting may have unintended consequences, inducing non-financial firms to employ financial assets as tools to hoard bad news.

Does the informational interdependence among countries affect market quality? Guided by the theoretical literature, this paper examines disruptions to international information flow as a source of financial market frictions. Using nonoverlapping holidays as a novel identification method, I find that disruptions to foreign information inflow deteriorate domestic market liquidity and fairness. I show that market quality worsens through both the informational sensitivity and the abnormal trading channels. Additional analyses indicate that stocks with lower liquidity and higher volatility are prone to more manipulative trading during information disruptions. Furthermore, a stock exchange upgrade weakens the abnormal trading channel. These findings suggest that international information flow is important to financial market quality.

This study investigates the underexplored role of onsite viewing activities in the housing search process. By incorporating buyer heterogeneity into the housing search model of Courant (1978), we show that buyers with higher private valuations tend to view more properties onsite and ultimately pay higher prices. Utilising a proprietary dataset from the largest real estate agency in Beijing, our analysis reveals that increased onsite viewings significantly enhance both the likelihood of a transaction and the final purchase price. We establish causality by employing an instrumental variable approach that leverages exogenous variations in heavy pollution and rainfall, which hinder buyers’ ability to conduct onsite house viewings. More intensive onsite viewings raise transaction price as they reveal a buyer’s higher private valuation to the seller. Besides, onsite viewings also function through reducing information asymmetry and improving match quality.

The increased impact of extreme weather events and droughts has prompted the rapid growth of the water market. This paper develops a real options valuation model for a hydropower plant that incorporates uncertainty in water and electricity prices, water inflows, and drought severity. Using a stochastic optimal control framework, the model is calibrated with monthly data from a reservoir in California. Water inflow and prices are modeled as functions of the California Drought Severity Index. Results highlight strong seasonality and uncertainty in price dynamics and show that revenues from water rights trading are highly sensitive to climate conditions. The model provides a comprehensive understanding into managing and valuing hydropower reservoirs under volatile environmental and market conditions.

This paper examines the impact of intraday periodicity on forecasting realized volatility using a heterogeneous autoregressive model (HAR) framework. We show that periodicity inflates the variance of the realized volatility and biases jump estimators. This combined effect adversely affects forecasting. To account for this, we propose a periodicity-adjusted HAR model, HARP, where predictors are constructed from the periodicity-filtered data. We demonstrate empirically (using 30 stocks from various business sectors and the SPY for the period 2000–2020) and via Monte Carlo simulations that the HARP models produce significantly better forecasts across all forecasting horizons. We also show that adjusting for periodicity when estimating the variance risk premium improves return predictability.

We examine how cybercrime impacts victims’ risk-taking and returns. The results from our difference-in-differences analysis of a sample of victim and matched non-victim investors on the Ethereum blockchain are in line with prospect theory and suggests that victims increase their long-term total risk-taking after losing part of their wealth, leading to lower risk-adjusted returns in the post-cybercrime period. Victims’ long-term total risk-taking increases because they increase diversifiable risk due to victims’ post-cybercrime withdrawal from altcoins. At the same time, the reduction in risk-adjusted returns correlates with increased trading activity and churn, due plausibly to managing cybercrime exposure. In the cross-section of Ethereum addresses, we show that the most affluent victims take a systematic approach to restore their pre-cybercrime wealth level, while the least affluent victims turn into gamblers. Finally, a parsimonious forensic model explains a good part of the addresses’ probability of being involved in cybercrime, on both the victim and the cybercriminal side.