ABSTRACT Dealers in the over‐the‐counter municipal bond market form trading networks with other dealers to mitigate search frictions. Regulatory data show that this network has a core‐periphery structure with 10 to 30 hubs and over 2,000 peripheral broker‐dealers in which bonds flow from periphery to core and partially back. Central dealers charge investors up to double the round‐trip markups compared to peripheral dealers. In turn, central dealers provide immediacy by matching buyers with sellers more directly and prearranging fewer trades, especially during stress times. Investors thus face a trade‐off between execution cost and speed, consistent with network models of decentralized trade.

Theoretical models have long recognized the role of investor disagreements in the marketplace, but little evidence is documented regarding how belief dispersion affects trading activities in the broad equity market. Using over three decades of data from a survey of US households, we introduced a novel measure of household macroeconomic belief dispersion and document its positive relationship with market-wide stock trading volume, even after controlling for an array of professional analysts’ belief dispersion. Results are more pronounced for the belief dispersion among households who are more likely to own stocks. Furthermore, we show that the household belief dispersion is priced in the cross-section of stock returns, whereas that among professional analysts is not.

We examine product differentiation in the high-frequency trading (HFT) industry, where the “products” are secretive proprietary trading strategies. We demonstrate how principal component analysis can be used to detect underlying strategies common to multiple HFT firms and show that there are three product categories with distinct attributes. We study how HFT competition in each product category affects the market environment and present evidence that indicates how it influences the short-horizon volatility of stocks as well as the viability of trading venues. Received October 10, 2016; editorial decision September 30, 2017 by Editor Itay Goldstein. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

This paper studies whether stock market liquidity has a causal effect on real earnings management. We introduce a new and cleaner identification of liquidity shock - the 2016 Tick Size Pilot Program - to show that firms with less liquid stocks are more likely to engage in real earnings management. We provide direct evidence that stock liquidity helps to deter real earnings management via enhancing governance by long-term institutional investors through trading and direct intervention, and via facilitating short selling to discipline managers. The effect is stronger in firms that do not pay dividends.

This paper empirically examines business starts, deaths, venture capital and patents in relation to U.S. public policy. The most consistent evidence in the data shows that lower levels of labor frictions and higher levels of SBIR awards are associated with more business starts and higher levels of venture capital per population. Counter to expectations, the data indicate a positive impact from the homestead exemption only among the bottom quartile homestead exemption states, and otherwise a negative impact. We analyze a variety of other policy instruments and compare the effects of policy in regular times with the financial crisis of 2008–2010.

This paper investigates the dynamic correlations among six international stock market indices and their relationship to inflation fluctuation and market volatility. The current research uses a newly developed time series model, the Double Smooth Transition Conditional Correlation with Conditional Auto Regressive Range (DSTCC-CARR) model. Findings reveal that international stock correlations are significantly time-varying and the evolution among them is related to cyclical fluctuations of inflation rates and stock volatility. The higher/lower correlations emerge between countries when both countries experience a contractionary/expansionary phase or higher/lower volatilities.

ABSTRACT We examine the labor market consequences of the 2020 Regulation S‐K requiring human capital disclosure in 10K filings. Using large‐sample job‐level data and a Generative Large Language Model (GLLM), we observe that public firms subject to the regulation increase their disclosure of diversity, equity, and inclusion (DEI) information in job postings relative to a matched sample of large private firms. The increase in job‐posting disclosure is more pronounced among firms facing greater external pressure to increase their workforce diversity. These findings suggest a shift in demand for diverse candidates by public firms following the regulation. Yet, consistent with short‐term inelastic labor supply, this demand shift lengthens the recruitment period, with noticeable increases in workplace gender diversity emerging one year after the regulation, particularly among firms that demonstrate a credible commitment to DEI. Our study documents how securities regulations can impact labor market practices and underscores the challenges involved in shaping workforce diversity.

This paper demonstrates that existing quantile regression models used for jointly forecasting Value-at-Risk (VaR) and expected shortfall (ES) are sensitive to initial conditions. Given the importance of these measures in financial systems, this sensitivity is a critical issue. A new Bayesian quantile regression approach is proposed for estimating joint VaR and ES models. By treating the initial values as unknown parameters, sensitivity issues can be dealt with. Furthermore, new additive-type models are developed for the ES component that are more robust to initial conditions. A novel approach using the open-faced sandwich (OFS) method is proposed which improves uncertainty quantification in risk forecasts. Simulation and empirical results highlight the improvements in risk forecasts ensuing from the proposed methods.

Self-imposed risk limits effectively limit dealers' appetite for risks and their capacity to intermediate in Treasury markets in times of market stress. Using granular and high frequency regulatory data on US dealers' Treasury securities trading desk positions and desk-level Value-at-Risk limits, we show that dealers are more inclined to reduce their positions as they get closer to their internal risk limit, consistent with such limit being meaningful and costly for traders to breach. Dealers actively manage their inventories away from their limits by selling longer-term securities and requiring higher compensation to take on additional risks. During the height of the Covid-crisis in 2020, dealer desks that were closer to their VaR limits sold more Treasury securities to the Fed and accepted lower prices in the emergency open market operations. Our findings complement studies that link post-GFC bank regulations to market liquidity by showing that self-imposed risk limits can explain the risk-averse behavior by dealers, and provide a micro-foundation for the link between market volatility and market liquidity in dealer-intermediated OTC markets. In times of crisis, policy prescriptions such as deregulation alone may not be sufficient to induce risk-taking by dealer intermediaries. Moreover, to address market functioning issues, policy actions that address the funding costs of intermediaries would not be as effective as policies that remove risks from intermediary balance sheets directly.

ABSTRACT We study price discovery in municipal bonds, an important OTC market. As in markets for consumer goods, prices “rise faster than they fall.” Round‐trip profits to dealers on retail trades increase in rising markets but do not decrease in falling markets. Further, effective half‐spreads increase or decrease more when movements in fundamentals favor dealers. Yield spreads relative to Treasuries also adjust with asymmetric speed in rising and falling markets. Finally, intraday price dispersion is asymmetric in rising and falling markets, as consumer search theory would predict.