A Complete Nonparametric Event Study Approach

Event studies have been used to examine the direction, magnitude, and speed of security price reactions to various phenomenon. Concerns over the lack of normality in stock return distributions motivated the introduction of nonparametric test statistics in the event study literature. A parametric procedure (OLS), however, has been extensively employed in the estimation of parameters for the market model. This paper, in contrast, applies Theil's nonparametric regression in the estimation of abnormal returns; an approach which is distribution free and provides a complete nonparametric approach for the detection of abnormal performance. Simulation results indicate Theil's estimation procedure offers a slight improvement in power in the detection of abnormal performance over the traditionally employed methodology. The results suggest employing Theil's nonparametric estimation procedure combined with the rank statistic. This complete nonparametric combination offers similar power with fewer underlying assumptions.     

Multi-country event-study methods

We provide the first simulation evidence of event-study test performance in multi-country non-US samples. The nonparametric rank and generalized sign tests are more powerful than two common parametric tests, especially in multi-day windows. The two nonparametric tests are mostly well specified, but neither is perfectly specified in all situations. The parametric standardized cross-sectional test can provide a useful robustness check but is less powerful than the nonparametric tests and rejects too often in single-market samples and when firm-specific events affect the market index. Local-currency market-model abnormal returns using national market indexes are sufficient.     

Event-Induced Volatility and Tests for Abnormal Performance

I analyze a simple test statistic for mean abnormal returns in the presence of stochastic volatility during both event and nonevent windows and in the presence of event‐induced variance increases. Unlike previous tests, the parametric test evaluated here does not require that the volatility effect of the event be the same across all securities. Simulations show that the test exhibits nontrivial gains in power over previously developed parametric and nonparametric tests, and the true null hypothesis is rejected at appropriate levels.     

事件模拟与非正常收益模型的检验力——基于中国A股市场的经验检验

本文分别以1990年12月至2003年12月两市所有A股公司为抽样总体,检验了均值调整模型、市场调整模型和市场模型为基础的多种检验方法的检验力。研究发现,无论事件研究中各公司事件是否相近或重叠,都应采用市场模型为基础的非参数秩检验法。而累积非正常收益的检验也应以市场模型为计算基础。若样本公司事件日相近或重叠,统计量的设置要考虑累积非正常收益截面数据的相关性。均值调整模型在本文所定义的各种检验方法中,均无明显优势。经敏感性测试,本文结论不变。     

Conducting Event Studies on a Small Stock Exchange

Abstract

This paper analyses whether it is possible to perform an event study on a small stock exchange with thinly trade stocks. The main conclusion is that event studies can be performed provided that certain adjustments are made. First, a minimum of 25 events appears necessary to obtain acceptable size and power in statistical tests. Second, trade to trade returns should be used. Third, one should not expect to consistently detect abnormal performance of less than about 1% (or perhaps even 2%), unless the sample contains primarily thickly traded stocks. Fourth, nonparametric tests are generally preferable to parametric tests of abnormal performance. Fifth, researchers should present separate results for thickly and thinly traded stock groups. Finally, when nonnormality, event induced variance, unknown event day, and problems of very thin trading are all considered simultaneously, no one test statistic or type of test statistic dominates the others.     

Discriminating between wealth and information effects in event studies in accounting and finance research

This article examines the power of tests of given size to detect and distinguish between wealth (i.e., mean) and information (i.e., variance) effects in event studies. We find that an Estimated Generalized Least Squares (EGLS) mean-effects test is consistently more powerful than the test based upon the average standardized residual and is as powerful as a nonparametric rank test. Unlike the test based upon the average standardized residual and the rank test, the EGLS test is well specified even when the event affects the variances of the prediction errors. We also find that conventional parametric tests to detect changes in the variance of the event-day average abnormal return are misspecified when the null of no change is true. We analyze the reasons this occurs and suggest a rank procedure that produces tests of the correct size under the null. Our evidence suggests that the critical factors allowing researchers to distinguish between wealth and information effects are an estimation procedure incorporating the heteroskedasticity inherent in market model prediction errors and an explicit test for event-day variance changes.     

Long-Term Market Overreaction: The Effect of Low-Priced Stocks

Conrad and Kaul (1993) report that most of De Bondt and Thaler's (1985) long-term overreaction findings can be attributed to a combination of bid-ask effects when monthly cumulative average returns (CARs) are used, and price, rather than prior returns. In direct tests, we find little difference in test-period returns whether CARs or buy-and-hold returns are used, and that price has little predictive ability in cross-sectional regressions. The difference in findings between this study and Conrad and Kaul's is primarily due to their statistical methodology. They confound cross-sectional patterns and aggregate time-series mean reversion, and introduce a survivor bias. Their procedures increase the influence of price at the expense of prior returns.     

It's Showtime: Do Managers Report Better News Before Annual Shareholder Meetings?

Annual shareholder meetings provide an opportunity for shareholders to express their concerns with corporate performance, pressuring managers to demonstrate good performance. We show that managers respond to the shareholder pressure by reporting positive corporate news before the annual shareholder meetings. Specifically, we find significantly positive average cumulative abnormal returns (CARs) during the 40 days before the annual meeting date. The premeeting returns are significantly higher when shareholder discontent with managerial performance is likely to be stronger. The decile of companies with the worst past stock price performance exhibits average CARs of 3.4% and buy‐and‐hold returns of 7.0% during the 40‐day premeeting period. Companies with poor past performance exhibit even higher premeeting returns when shareholder pressure on management is greater, such as when institutional ownership is high, when CEO compensation is high, and when shareholders submit proxy proposals on corporate governance. We complement the evidence based on CARs by showing how managers of poorly performing firms manage the timing and content of earnings announcements and management forecast announcements before the annual shareholder meetings. Overall, the results suggest that managers attempt to influence shareholders before annual shareholder meetings through positive news.     

Equity Markets Do Not Fit All: an Analysis of Public‐to‐Private Deals in Continental Europe

Concentration of family‐based ownership and recent development of private equity companies in Continental Europe suggest that the motivations and results of public‐to‐private (PTP) deals may differ from well‐studied cases in the USA and the UK. We overview the PTP market and measure the cumulative abnormal returns (CARs) of 106 PTP deals concluded in Continental Europe from 2000 to 2005, introducing a model to explain the abnormal returns. Our results partially confirm findings of previous studies, namely, that undervalued and smaller firms register higher CARs. We additionally find that deals promoted by family owners register higher abnormal returns, whereas financial investors and private operating firms show no impact.     

Forecasting the performance of hedge fund styles

This article predicts the relative performance of hedge fund investment styles using time-varying conditional stochastic dominance tests. These tests allow for the construction of dynamic trading strategies based on nonparametric density forecasts of hedge fund returns. During the recent financial turmoil, our tests predict a superior performance for the Global Macro investment style compared with the other strategies of ‘Directional Traders’. The Dedicated Short Bias investment style is stochastically dominated by the other directional styles. These results are confirmed by simple nonparametric tests constructed from realized excess returns. Further, by utilizing a cross-validation method for optimal bandwidth parameter selection, we discover the factors that have predictive power regarding the density of hedge fund returns. We observe that different factors have forecasting power for different regions of the returns distribution and, more importantly, that the Fung and Hsieh factors have power not only for describing the risk premium but also, if appropriately exploited, for density forecasting.     

Does bancassurance add value for banks? - Evidence from mergers and acquisitions between European banks and insurance companies

This paper investigates the risk and wealth effects of 72 mergers and acquisitions between banks in Europe and insurance companies during the period 1989-2004. The empirical results indicate that acquirers’ total risks remain constant relative to the world, home market indices and home banking indices. There are no changes for the systematic risks (beta) with respect to the world market index or the home banking index. After removing world and home market indices effect, systematic risk against home banking index reduce significantly for domestic deals. In addition, positive wealth effects are documented. Two factors have contributed to the bidders’ cumulative abnormal returns (CARs): relative deal size and being a serial acquirer. Finally, change of beta shows negative relations with CARs.     

The deal of the century in Chile Endesa España's takeover of Enersis

We analyze the effect of the announcement of the tender offer made by Endesa España to control Enersis Chile through the Chispas holding structure. In this clinical study of the case, we summarize the salient points of the Chispa case—one of the most controversial in Chile—and obtain the abnormal returns to the shareholders of the target firm using three alternative models for robustness of results: the constant mean model, the market model, and the market model adjusted for non-synchronous trading problems. Contrary to expectations based on prior empirical research in the United States and United Kingdom, our results demonstrate the absence of positive cumulative abnormal returns (CARs) for Chispa stockholders during the takeover bidding event window. We present evidence in this case that the governance structure of the target firm led to this seeming anomaly and conclude that the generally accepted theories of corporate control and governance in the United States and United Kingdom do not automatically apply to developing countries with differing legal environments.     

Testing for abnormal security-price performance under conditions of event-period uncertainty

This paper examines an event study test procedure based on cumulative average residuals (CARs) and a boundary-crossing probability for Brownian motion. The boundary-crossing test procedure is designed to detect abnormal security-price performance under conditions of event-period uncertainty. Simulations with daily security-return data show that the boundary-crossing test is well specified under the null hypothesis and has good power properties under the alternative hypothesis of abnormal security-price performance distributed over an event period of uncertain length.     

Semiparametric estimation of a characteristic-based factor model of common stock returns

We introduce an alternative version of the Fama–French three-factor model of stock returns together with a new estimation methodology. We assume that the factor betas in the model are smooth nonlinear functions of observed security characteristics. We develop an estimation procedure that combines nonparametric kernel methods for constructing mimicking portfolios with parametric nonlinear regression to estimate factor returns and factor betas simultaneously. The methodology is applied to US common stocks and the empirical findings compared to those of Fama and French.     

ON THE INFORMATIONAL EFFECT OF SHORT‐SALES CONSTRAINTS: EVIDENCE FROM THE TOKYO STOCK EXCHANGE

Using a database of stock lending fees for Japanese centralized margin transactions, I show that short‐sales constraints reduce the adjustment speed of stock prices to negative information before the announcements of revised earnings forecasts disclosed by firms in the Tokyo Stock Exchange from July 1998 to December 2001. I find that the cumulative abnormal returns (CARs) of the stocks with high short‐sales costs are insensitive to negative information on pre‐announcement days, but the CARs of these stocks become significantly lower than the CARs of the stocks with low short‐sales costs when the announcements reveal negative information to the public.     

Quarterly earnings announcements and intra-industry information transfer from the Pacific to the Atlantic

In this study, we explore intra-industry information transfer of quarterly earnings announcements for six major developed markets including the United States. Using an event study methodology, we find that the average cumulative abnormal returns (CARs) of peer firms exhibit a positive and significant relationship with the CARs of announcing firms in the same country and industry over the three-day window surrounding quarterly earnings announcements. During periods of high past market volatility, earnings announcements demonstrate magnified information spillover effects on peer firms. Also, our results suggest that announcing firms with larger market capitalization generate greater intra-industry information transfer.     

Co-dependence of extreme events in high frequency FX returns

In this paper, we investigate extreme events in high frequency, multivariate FX returns within a purposely built framework. We generalize univariate tests and concepts to multidimensional settings and employ these novel techniques for parametric and nonparametric analysis. In particular, we investigate and quantify the co-dependence of cross-sectional and intertemporal extreme events. We find evidence of the cubic law of extreme returns, their increasing and asymmetric dependence and of the scaling property of extreme risk in joint symmetric tails.     

Powerful bidders and value creation in M&As

This paper explores the role of bargaining ability in corporate mergers and acquisitions (M&As) by focusing on acquiring firms with ex-ante market power—powerful bidders. Drawing from a bargaining power theoretical stance, we argue that powerful bidders create value from M&A activity by paying comparatively lower premiums. We test our empirical proposition using a sample of 9327 M&A deals announced between 2004 and 2016 by bidders across 30 countries. Contrary to the stylized fact that bidders do not gain from M&A activity, we uncover evidence suggesting that powerful bidders pay lower bid premiums and, consequently, earn positive (and relatively higher) cumulative announcement returns (CARs) from M&A deals. On average, the mean returns to powerful bidders (1.3%) are at least twice those of their less powerful counterparts (0.6%). We identify “low financial constraints” as a potential channel through which higher bidder power translates to improved deal performance. Overall, our results provide new evidence on how industry dynamics, notably bargaining power, influences M&A outcomes.     

Does the timing of dividend reductions signal value? Empirical evidence

This paper examines a firm's dividend reduction timing relative to other dividend reductions in the same industry. It tests if the timing of dividend cuts is informative in firm valuation. The findings suggest that during periods of less accessible external financing, such as recessions, firms with greater investment opportunities are among the first firms to make necessary dividend reductions to take advantage of such opportunities. When external financing is more accessible, firms with superior investment opportunities are able to access capital markets in lieu of dividend-reducing internal financing, indicating higher firm values for earlier dividend reductions during periods of costly external financing and significantly lower firm values for early reductions when financing is more easily obtained. A series of empirical tests show that, in periods of less accessible external financing or during a recession, early dividend-reducing firms significantly outperform late reducers in announcement day and contraction cycle cumulative abnormal returns. The results also show that, outside of a recession, early dividend-reducing firms have significantly lower industry contraction cycle returns than late dividend reducers. Additionally, this study compares early dividend reductions that occur during periods of costly external financing (or during a recession) against early reductions that occur when external financing is more available (or outside of a recession) and finds the former to have significantly higher announcement day and contraction cycle cumulative abnormal returns.     

A Simple Econometric Approach for Utility-Based Asset Pricing Models

Utility-based models of asset pricing may be estimated with or without assuming a distribution for security returns; both approaches are developed and compared here. The chief strength of a parametric estimator lies in its computational simplicity and statistical efficiency when the added distributional assumption is true. In contrast, the nonparametric estimator is robust to departures from any particular distribution, and it is more consistent with the spirit underlying utility-based asset pricing models since the distribution of asset returns remains unspecified even in the empirical work. The nonparametric approach turns out to be easy to implement with precision nearly indistinguishable from its parametric counterpart in this particular application. The application shows that log utility is consistent with the data over the period 1926–1981.