Baozhong Yang

Mandatory Portfolio Disclosure, Stock Liquidity, and Mutual Fund Performance

We examine the impact of mandatory portfolio disclosure by mutual funds on stock liquidity and fund performance. We develop a model of informed trading with disclosure and test its predictions using the SEC regulation in May 2004 requiring more frequent disclosure. Stocks with higher fund ownership, especially those held by more informed funds or subject to greater information asymmetry, experience larger increases in liquidity after the regulation change. More informed funds, especially those holding stocks with greater information asymmetry, experience greater performance deterioration after the regulation change. Overall, mandatory disclosure improves stock liquidity but imposes costs on informed investors.

Dynamic Capital Structure with Heterogeneous Beliefs and Market Timing

Article history: Received 5 December 2011 Received in revised form 23 May 2013 Accepted 30 May 2013 Available online 10 June 2013 This paper builds a dynamic trade-off model of corporate financing with differences in belief between the insider manager and outside investors. The optimal leverage depends on differences of opinion and can differ significantly from that in standard trade-off models. The managers market timing behavior leads to several stylized facts, such as the low average debt ratios of firms in the cross section, the substantial presence of zero-debt firms that pay larger dividends and keep higher cash balances than other firms, and negative long-run abnormal returns following stock issuance. Market timing behavior leads to substantial losses of firm value through excessive financing activities. Market timing and debt conservatism depend negatively on shareholder control of the firm.

The uniqueness of tangent cones for Yang–Mills connections with isolated singularities

We proved a uniqueness theorem of tangent connections for a Yang–Mills connection with an isolated singularity with a quadratic growth of the curvature at the singularity. We also obtained control over the rate of the asymptotic convergence of the connection to the tangent connection if furthermore the connection is stationary or the tangent connection is integrable, with a stronger result in the latter case. There are parallel results for the cones at infinity of a Yang–Mills connection on an asymptotically flat manifold. We also gave an application of our methods to the Yang–Mills flow and proved that the Yang–Mills flow exists for all time and has asymptotic limit if the initial value is close to a smooth local minimizer of the Yang–Mills functional.

Communication, Excess Comovement and Factor Structures

This paper develops a model in which investors communicate before trading in a general equilibrium. Investors repeatedly communicate in a social network but have limited knowledge of the network structure and thus do not fully realize the consequences of their communication and belief updating. As a result, asset returns contain excess comovement and more concentrated factor structures than fundamental values do. The model generates testable empirical predictions that are consistent with the empirical literature on excess comovement in asset returns.

Optimal Dynamic Risk Taking

We analyze a continuous-time stochastic control problem that arises in the study of several important issues in financial economics. An agent controls the drift and volatility of a diffusion output process by dynamically selecting one of an arbitrary (but finite) number of projects and the termination time. The optimal policy depends on the projects’ risk-adjusted drifts that are determined by their drifts, volatilities, and the curvature (or relative risk aversion) of the agent’s payoff function. We prove that the optimal policy only selects projects in the spanning subset. Furthermore, if the projects’ risk-adjusted drifts are consistently ordered for all output values, then the optimal policy is characterized by at most K − 1 switching triggers, where K is the number of projects in the spanning subset. We also characterize the optimal policy when the consistent ordering condition does not hold, and we outline a general and tractable computational algorithm to derive the optimal policies.

How Valuable is FinTech Innovation

We provide large-scale evidence on the occurrence and value of FinTech innovation. Using data on patent filings from 2003 to 2017, we apply machine learning to identify and classify innovations by their underlying technologies. We find that most FinTech innovations yield substantial value to innovators, with blockchain being particularly valuable. For the overall financial sector, internet of things (IoT), robo-advising, and blockchain are the most valuable innovation types. Innovations affect financial industries more negatively when they involve disruptive technologies from nonfinancial startups, but market leaders that invest heavily in their own innovation can avoid much of the negative value effect.ReceivedMay 31, 2017; editorial decision September 30, 2018 by Editor Andrew Karolyi.

Communication and Comovement: Evidence from Online Stock Forums: Communication and Comovement

We develop a model of investor communication generating return comovement and test its predictions using a novel dataset on an active online stock forum in China. For each stock, we consider its “related stocks,” which are frequently discussed in the sub-forum dedicated to the given stock. We find substantial comovement among the returns of a stock and related stocks. Comovement is greater when related stocks are more frequently discussed. Further, the effect of frequent communication on comovement is stronger for stocks associated with higher information asymmetry. Our results are robust in tests using a forum outage event as a natural experiment and tests controlling for media coverage, market, industry, and economic variables. Our findings highlight the impact of investor communication on stock return covariance.

Communication and Comovement: Evidence from Online Stock Forums

We study investor communication and stock comovement using a novel dataset for an active online stock forum in China. We find substantial comovement among the returns of a stock and its “related stocks,” that are frequently discussed in the sub-forum dedicated to the given stock. Comovement is greater when related stocks are more frequently discussed. Further, the effect of frequent communication on comovement is stronger for stocks associated with higher information asymmetry. We also use a forum outage event as a quasi-natural experiment to establish causality. Our findings highlight the impact of investor communication on stock return comovement.