Knowledge that Transforms

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.

Since the 2008 financial crisis, regulators and supervisors have been granted increased independence from political bodies. But there is no clear evidence of the benefits of more independence for the stability of the banking sector. In this paper we introduce a new indicator of regulatory and supervisory independence for 98 countries from 1999 to 2019. We combine this index with bank-level data to investigate the relationship between independence and financial stability. We find that greater regulatory and supervisory independence is associated with improved financial stability. We show that these results are robust to alternative measures of financial stability and to a number of tests. Overall, our findings indicate that increasing the independence of regulators and supervisors is beneficial for financial stability.

Using an international sample of 38 countries, we find that firms located in countries experiencing greater socioeconomic damage from extreme climate events have higher implied costs of equity capital. This finding is attributed to heightened operational uncertainty, greater information asymmetry, and intensified agency conflicts that arise in the wake of extreme climate events. The relation is stronger for firms that derive substantial revenue from domestic markets, operate in climate-vulnerable industries, or are closely held by domestic institutional investors. The effect also varies across countries and is concentrated in markets characterized by low transparency or limited integration into the global financial market. While extreme climate events negatively influence firm performance and valuation, they raise corporate awareness of climate risk.

This study examines the ability of the linear-rational square-root model to simultaneously capture cross-sectional and time-series dynamics of bond yields and their variances. The preferred model specification comprises five factors, two of which are not spanned by the yield curve, introducing unspanned stochastic volatility (USV). This specification provides a close in-sample fit to yields and yield variances, emphasizing the need for USV. Out-of-sample testing demonstrates low variance forecast errors. The specification provides evidence of USV in conditional yield variance and bond risk premia, linked to macroeconomic uncertainty.

Despite regulatory reforms, Money Market Funds (MMFs) experienced severe stress in March 2020, following large redemptions and dislocations in short-term markets. We provide a model showing the trade-offs between liquidity and capital preservation services offered by MMFs. We show that in a crisis, MMFs cannot provide liquidity and capital preservation to investors at the same time. As a result, investors have an incentive to run pre-emptively. We calibrate our model on data from USD MMFs and find that most funds would have been unable to meet redemptions above 30% mid-March 2020. Unless short-term funding markets are made resilient in times of stress, MMFs will face similar challenges during future liquidity crises.

We show that families are an engine of venturing activities: almost 30 percent of corporate venture capital (CVC) deals in the US from 2000 to 2017 originated from family firms. Family firms, primarily those led by family CEOs, orchestrate CVC activities differently than non-family firms: they syndicate more often and with more reputable investors, join larger syndicates, and make more proximate deals (geography- and industry-wise). This approach to corporate venturing maps into performance results: family CVC-backed ventures exhibit a higher likelihood of successful exit. Collectively, our results shed light on the important, and largely unexplored, role of family firms in CVC.