A rapidly growing literature claims to reject the efficient market hypothesis by producing large estimates of long-term abnormal returns following major corporate events. The preferred methodology in this literature is to calculate average multi-year buy-and-hold abnormal returns and conduct inferences via a bootstrapping procedure. We show that this methodology is severely flawed because it assumes independence of multi-year abnormal returns for event firms, producing test statistics that are up to four times too large. After accounting for the positive cross-correlations of event firm abnormal returns we find virtually no evidence of reliable abnormal performance for our samples.

I review empirical research on the relation between capital markets and financial statements.The principal sources of demand for capital markets research in accounting are fundamental analysis and valuation, tests of market efficiency, and the role of accounting numbers in contracts and the political process.The capital markets research topics of current interest to researchers include tests of market efficiency with respect to accounting information, fundamental analysis, and value relevance of financial reporting.Evidence from research on these topics is likely to be helpful in capital market investment decisions, accounting standard setting, and corporate financial

Statistical inference in long-horizon event studies has been hampered by the fact that abnormal returns are neither normally distributed nor independent. This study presents a new approach to inference that overcomes these difficulties and dominates other popular testing methods. I illustrate the use of the methodology by examining the long-horizon returns of initial public offerings ~IPOs!. I find that the Fama and French ~1993! three-factor model is inconsistent with the observed long-horizon price performance of these IPOs, whereas a characteristic-based model cannot be rejected. RECENT EMPIRICAL STUDIES IN FINANCE document systematic long-run abnormal price reactions subsequent to numerous corporate activities. 1 Since these results imply that stock prices react with a long delay to publicly available information, they appear to be at odds with the Efficient Markets Hypothesis ~EMH!. Long-run event studies, however, are subject to serious statistical difficulties

This paper uses firm-level information to examine how the Asian and Russian crises affected different types of firms around the world. It constructs a new data set of financial statistics, industry information, geographic data, and stock returns for over 10,000 companies in 46 countries. Results indicate that firms that competed with exports from the crisis countries, and firms which had direct sales exposure to the crisis countries, had substantially lower abnormal stock returns during these periods. On the other hand, firms with higher debt ratios did not experience significantly lower abnormal returns. Country-specific effects, although important determinants of company stock returns, generally have a smaller impact than the firm-specific characteristics. This series of results suggests that trade channels are important determinants of how crises are transmitted internationally.

We study the stock price reaction to news about tax aggressiveness. We find that, on average, a company’s stock price declines when there is news about its involvement in tax shelters, but the reaction is small relative to reactions to other corporate misdeeds. We find some limited evidence for cross-sectional variation in the reaction. For example, the stock price decline is smaller for firms that have good governance which is consistent with the idea that for these firms the news is less likely to trigger concerns about insiders’ aggressiveness toward the investors themselves. The reaction is more negative for firms in the retail sector, suggesting that part of the reaction may be a consumer/taxpayer backlash. We also test whether the reaction varies with the market’s perception of how tax-aggressive the firm is, using the firm’s current effective tax rate as a proxy for the market’s beliefs, and find mixed results. We also explore the stock price reaction to reports of current effective tax rate calculations released by Citizens for Tax Justice. We hypothesize that these reports signal tax aggressiveness without the implications for tax penalties or illegal behavior

The choice of model of normal returns in event studies has been widely discussed in the literature. While researchers frequently continue to use an array of alternatives, there is currently some tendency to favour cruder but simpler mean- or marketadjusted returns models. This paper presents a general-to-specific model selection framework for testing the data admissibility of the principal models in current use. Results from a pilot study yield useful insights and indicate a strong preliminary preference in favour of the regression-based models, with the market model generally outperforming the capital asset pricing model.

This paper applies the event study method to analyze investors ’ average evaluation of mergers between publicly traded banking organizations in the 1990s. It uses three models of stock returns, including the multi-factor Fama-French (1992, 1993) model, to estimate the abnormal returns experienced by the merging companies ’ stocks upon the announcement of the merger. Overall, the targets are found to enjoy significant excess gains in stock prices, whereas the acquirers suffer considerable losses. The market-valueweighted average abnormal returns to the two parties combined are positive but insignificant. In addition, the paper shows that estimates of the abnormal returns can be sensitive to the choice of models describing stock returns, assumptions about the error generating process, and other factors. This problem is more severe if one reports only tests of the null hypothesis. Hence, the paper instead reports pvalues and confidence intervals. In summary, this study finds that bank mergers in the 1990s are generally expected to raise future profits of the merged entities, but not strongly so. But due to model sensitivity, the precise numerical estimates of abnormal returns should be interpreted with caution. Acknowledgments: I am grateful to Jim Adams, Bob Barsky, Susanto Basu, Lutz Kilian, and Michelle White for valuable comments, advice and support, and thank many others for help. All errors remain the sole responsibility of the author.

from the bond markets

In spring 2000, three clustered events, two political statements by Bill Clinton and Tony Blair and a breakthrough announcement by Celera Genomics, had altogether a tremendous impact on biotechnology stocks. Their effects are analyzed over a comprehensive set of biopharmaceutical companies, using a composite return-generating model with an industry-specific patent-based factor. The analysis shows that stocks can be grouped depending on their responsiveness to political and scientific events. Furthermore, in-depth examination of event returns reveals that political events produced more favorable effects in sectors where patent protection has the greatest market value, contrarily to the impact of the scientific announcement.

Ziebart for helpful discussions on this topic. Researchers studying stock price reactions to accounting information releases can choose among several statistical methods/models. Firm-specific equation methods appear to be particularly appropriate when the research hypotheses involve possible differences across firms. However, the firm-specific equation methods make more demands on the data, requiring estimation of firm-specific coefficients and (possibly) covariance parameters. Therefore, it is not clear whether the researcher realizes net gains by using firm-specific equation methods. In this paper, we examine the empirical behavior of test statistics arising from one firm-specific equation method, seemingly unrelated regression (SUR), and alternative test statistics based on the same set of equations, but not incorporating estimates of cross-sectional correlation. 1 Evidence on the empirical distributions of these statistics may guide researchers in designing and interpreting research. Understanding the empirical behavior of SUR is essential before accounting researchers can correctly interpret results of existent research or take full advantage of its conceptually desirable features when testing hypotheses involving possible differences across firms. If characteristics of the data used by accountants lead to high Type I error rates or poor power,