Financial Management最新文献

This study examines whether information about a firm's engagement in environmental, social, and governance (ESG) practices is material to market participants. Evidence from a sample of 1856 initial public offerings (IPOs) by U.S. companies for the 2007–2018 period robustly documents that firms for which there is available ESG performance information prior to going public exhibit higher underpricing due to a positive market response. Such a reaction is validated by agency cost-reducing practices that ESG-rated firms follow prior to the IPO, the superior post-IPO market performance they exhibit in terms of equity financing, and the higher share of financially sophisticated investors they attract compared to their ESG-unrated peers. Overall, our results highlight that it pays off to do good and to have the right investors; however, firms’ good ESG practices need to be visible to the market, through rating practices, to reap the benefits.

We study how trading activity affects liquidity and volatility by introducing two periodicities in trading activity. First, trades and quote updates are much more frequent within the first 100 ms of a second than during its remainder. Second, trading activity often spikes at intervals of exactly one second. For these two periodicities, higher trade and quote intensities lead to higher volatility, but they do not significantly affect stock liquidity. These periodicities are likely caused by algorithms that trade predictably by repeating instructions in loops with round start times and time increments. Such predictable behavior may provide an example of behavioral biases in trading algorithms.

This paper provides novel evidence of information asymmetry in exchange-traded fund (ETF) markets. By decomposing daily ETF flows, we find that the unexpected flow component, orthogonal to the components driven by market making and arbitraging, wields substantial power in predicting next day's ETF returns. Informed traders are able to exploit their information advantage to realize an annualized open-to-close return of 19.16% or close-to-close return of 22.42%. The informativeness of the unexpected ETF component is further confirmed by its strong power of predicting next day's macroeconomic and ETF-related news, while the market-making- and arbitraging-driven components are not closely related to forthcoming news.

We study 2009 and 2020 dark trading for U.S. stocks. Dark trading is lower when volume is low, volatility high, and in periods of markets stress. Dark pools are more active for large caps, while internalization is more common for small caps. Traders use dark pools to jump the queue for large caps in 2009, and to avoid crossing the spread for small caps in both years. Internalization is higher when spreads are wide and depth is high. Dark pool trading improves spreads in 2009, but worsens market quality for large caps in 2020. We discuss explanations for the change.

We analyze the impact of trading dynamics, including fragmentation of markets, undisplayed (dark), and algorithmic trading, on liquidity formation in initial public offerings (IPOs). We find that these various trading dynamics evolve throughout the IPO secondary market and are dependent on the IPO's initial offering-day underpricing. Higher levels of fragmentation in displayed (lit) markets and algorithmic trading improve market quality in IPOs, while higher levels of undisplayed (dark) trading harm it. Overall, we find that, with the exception of the impact of dark trading, the concerns regarding the impact of fragmented markets and algorithmic trading on IPO liquidity are mostly unwarranted.

Exploiting a recent anticorruption campaign in China, an event that incentivizes government officials to hide negative news from central inspection teams (CITs), we study whether market participants can counter that. We find that firm-level information embedded in stock price actually increases during CIT visits, especially in regions with poor legal environments, stronger social connection, or state-owned firms. Further, media coverage, analyst coverage, and corporate site visits by external stakeholders increase during the CIT visits. Collectively, our findings indicate that the market defeats local government officials’ attempt to hide firm-specific news.

We model dynamic bank capital structure under three optimally-designed regulatory regimes for dealing with potential default—bailout, in which the government provides capital; bail-in, which the private-sector provides needed funds; and no regulatory intervention, allowing the institutions to fail. Only under the optimally-designed bail-in regime do banks recapitalize during times of distress. Their pre-commitment to recapitalize reduces debt costs and increases debt capacity. No regulatory intervention is suboptimal for all agents. Optimal bailouts and bail-ins both generate no asset substitution-moral hazard behavior under optimal policies in which regulators intervene at early stages of distress. Empirical tests of changes in capital behavior from the pre-Global Financial Crisis bailout period to the post-crisis bail-in period corroborate the model's predictions.

In recent years, the majority of additions to and deletions from the S&P 500 index have been stocks that were previously or subsequently included in the S&P 400 index. The announcement returns of these changes have been the opposite of what has been documented for all S&P 500 additions and deletions in an extensive literature. During 2016–2020, such “upward additions” to the S&P 500 index resulted in an average announcement excess return of –2.48% over a 3-day period, while “downward deletions” to the S&P 400 index resulted in an excess return of +1.37%. We explain these new results by the increasing total institutional ownership of S&P 400 stocks. Our results thus show the increasing benefits of being included in the mid-cap S&P 400 index relative to being included in the large-cap S&P 500 index.

We use rich data on all business, economics, and engineering graduates in Sweden to study the lack of women among chief executive officers (CEOs). A comprehensive battery of graduates’ characteristics explains 40% of the gender gaps in CEO appointments and 60% among graduates with children. The explanatory power mostly comes from absences and unemployment, which are about twice as likely for women as men. These gender differences increase following childbirth, and they persist in the long run. We present and discuss potential explanations to the explained and remaining gaps. Although the large unexplained share makes it hard to pinpoint the exact reason for the gender gap in CEO appointments, the large contribution of labor market attachment to the explained share suggests work–family trade-offs are an important part of the story.

We construct a measure of dispersion in beliefs among individual investors. We find that dispersion in beliefs negatively predicts future cross-sectional stock returns, and it is positively related to trading volume and stock volatility. We also find that illiquidity does not affect the significance of dispersion in beliefs in predicting future stock return, and that the negative disagreement-return relation is significant under high-sentiment periods but becomes insignificant under low-sentiment periods. Moreover, investor characteristics affect their dispersion in beliefs even when controlling firm fundamentals. In particular, stocks with more wealthy, younger, and male investors tend to have higher dispersion in beliefs, and stocks with more experienced investors have lower dispersion in beliefs.