17 research outputs found

    Managers' private information, investor underreaction and long-run SEO underperformance

    Full text link
    Applying the framework of conditional event studies shows that equity issues reveal managers' private information about stock mispricing, which investors only partially discount into stock prices at the seasoned equity offering (SEO) announcement date. Negative abnormal returns occur as prices fully impound the information over a 17-month post-offer period. SEOs exhibit no subsequent underperformance. The study provides a more realistic explanation of SEO underperformance and a framework for testing behavioral explanations of abnormal performance following corporate events

    Does firm reporting quality and analyst forecasting skill influence the analyst choice to issue revenue forecasts?

    Get PDF
    This study documents that analysts are more likely to issue revenue forecasts to complement earnings-per-share estimates (EPS) when the quality of firm financial reporting is low. This is because compared to EPS forecasts accuracy, revenue forecast accuracy is less adversely affected by poor reporting quality, and as a result, investors rely more on revenue than EPS estimates in their investment decisions when the reporting quality is low. The result is robust to using five proxies for the quality of firm financial reporting: the variation in discretionary accruals, the absolute level of discretionary accruals, earnings persistence, absolute total accruals, and earnings volatility. Further, we document that better earnings forecasters are more likely to issue revenue estimates. This is because only better quality analysts would want their forecasts to be subject to higher market scrutiny, and because a combination of accurate revenue and EPS forecasts is a stronger signal of the analyst forecasting skill compared to an accurate stand-alone EPS estimate only

    Three essays on the long-run performance of films issuing seasoned equity offerings

    No full text
    Three essays on the long-run performance of firms issuing seasoned equity offering. Does liquidity risk explain the underperformance following seasoned equity offerings? In the first essay, I examine whether firms that issue seasoned equity experience stock liquidity gains after the offering and explore the role of liquidity risk in explaining their long-run performance. Long-run returns following seasoned equity offerings: market timing or discount rate effect? In the second essay, I build on conditional latent information models to test the market timing explanation for the long-run performance following seasoned equity offerings (SEOs). Propensity score matching and long-run performance following seasoned equity offerings Li and Zhao (2006) and Cheng (2003) report that propensity score matching eliminates the abnormal performance of firms issuing seasoned equity.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

    Does Algorithmic Trading Affect Analyst Research Production?

    No full text
    We document a causal negative relationship between algorithmic trading (AT) and analyst research production, as captured by a decreased frequency of earnings forecasts and stock recommendations and lower analyst coverage. This is consistent with AT increasing the speed of price discovery, reducing the profitability of trades on analyst research by non-algorithmic traders and, consequently, their demand for analyst investment advice. Supporting evidence shows that the effect of AT on analyst research production is stronger for stock recommendations, which institutions follow primarily for investment decisions, and for forecasts issued before earnings announcements when analysts’ information discovery dominates the information interpretation role. We also find a negative relationship between AT and investment-focused institutional investors such as transient and non-monitoring investors. Our analysis demonstrates that AT can have long-lasting consequences on capital markets, beyond microstructure effects, through its negative effect on firm’s information environment

    Does Algorithmic Trading Affect Analyst Research Production?

    No full text
    We document a causal negative relationship between algorithmic trading (AT) and analyst research production, as captured by a decreased frequency of earnings forecasts and stock recommendations and lower analyst coverage. This is consistent with AT increasing the speed of price discovery, reducing the profitability of trades on analyst research by non-algorithmic traders and, consequently, their demand for analyst investment advice. Supporting evidence shows that the effect of AT on analyst research production is stronger for stock recommendations, which institutions follow primarily for investment decisions, and for forecasts issued before earnings announcements when analysts’ information discovery dominates the information interpretation role. We also find a negative relationship between AT and investment-focused institutional investors such as transient and non-monitoring investors. Our analysis demonstrates that AT can have long-lasting consequences on capital markets, beyond microstructure effects, through its negative effect on firm’s information environment
    corecore