Skip to main content
SpringerLink
Log in

The advantages of using quarterly returns for long-term event studies

  • Original Research
  • Published:
Review of Quantitative Finance and Accounting Aims and scope Submit manuscript

Abstract

The main purpose of this paper is to explore the low power and methodological problems as they continue to plague long-term event study research. We investigate long-term tests (up to 2 years) performed on non-overlapping quarterly time frames as a solution. Components of commonly employed characteristic-based matching processes are examined as the source of low power. Single “best” matching firms don’t statistically match their event firms at the time of the event and are vastly inferior to matching with portfolios. A modified market mean method which uses the securities continuously traded during the calendar event period, is shown to be well specified, have comparable power and avoid the costs of more complex matching methodologies. Contrary to popular perception, increased power derives from the decreased variance in comparison returns; not from an increased covariance between comparison firm returns and event firm returns. The tests are easy to implement, well-specified and have higher power when based on quarterly versus monthly data.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Notes

  1. Long-term event studies may also be used to test market efficiency, particularly in those instances where the relationship between long-term stock price performance and short-term announcement effects are investigated.

  2. Palmon et al. (2009) trace the earliest event study work back to Dolley (1933).

  3. Additionally, the tests can have specification problems due to skewness in the distribution of abnormal returns and biases due to new listing, survivorship, overlapping-horizons and portfolio rebalancing. Most of these problems are caused by or amplified by the accumulating and/or compounding of the abnormal returns over long time frames. A number of modifications to the t test based on a characteristic based matching methodology have been proposed in the literature. Kothari and Warner (2005) present a comprehensive summary of these methods.

  4. The buy-and-hold abnormal return (BHAR) approach is another name for the characteristic-based matching method. The BHAR approach is described by Mitchell and Stafford (2000) as “the average multiyear return from a strategy of investing in all firms that complete an event and selling at the end of a prespecified holding period versus a comparable strategy using otherwise similar nonevent firms”.

  5. We review and discuss the prevalence of these techniques as applied in Table 1 and in the following section.

  6. We report only the results using quarterly data. Monthly tests have consistently lower power for a fixed level of induced abnormal return. Monthly results are available upon request.

  7. It is of interest to note that there is an epistemological issue that is largely ignored in the design of long-term event studies. In a short term event study focusing on the information impact of firm news, a relatively short time period, often a single day, is generally believed to be sufficient to assess if the news did indeed have an impact. In long-term event studies, there has been no work to the best of our knowledge to determine an appropriate time period for long-term abnormal return assessment. The selection of an appropriate time frame is left up to the investigator with long-term abnormal return estimation regularly reported as anything from a single year out to 5 years.

  8. Power is a test’s ability to detect abnormal performance when it is present and is measured as one minus the probability of a type II error.

  9. The Journal of Business published 12, the Review of Financial Studies published seven, the Journal of Financial and Quantitative Analysis published 17, the Journal of Financial Economics published 36 and the Journal of Finance published 27.

  10. Fama (1998) argues for a calendar time approach and against the characteristic-based matching approach because of the systematic errors that arise when imperfect expected return proxies are compounded over long horizons. Mitchell and Stafford (2000), in their study of the long-term impact of mergers, seasoned equity offerings and share repurchases, claim that measuring long-term abnormal performance with mean BHARs in conjunction with bootstrapping is not an adequate methodology because it assumes independence of multiyear event-firm abnormal returns. In contrast, Loughran and Ritter (2000) argue that the calendar time portfolio approach has low power to detect abnormal performance because it averages over months of “hot” and “cold” event activity.

  11. To the best of our knowledge, existing research provides no guidance as to the appropriate length of time over which to examine for long-term abnormal returns nor does theoretical work typically specify the appropriate length of time. This is in stark contrast to short-term event studies which propose short time frames for the incorporation of new information as a result of market efficiency.

  12. The problem is similar to that of investigating autocorrelation in time series. Overall tests for the presence of autocorrelation are common, but they are rarely used without a more detailed look at the pattern of the autocorrelations at the individual lags. Separate tests and methodologies are used for the two different dimensions of the problem.

  13. An additional iteration may be added to accommodate the momentum factor noted by Carhart (1997) in which control firms are matched to the prior 1-period returns of the event firms.

  14. Tolerance levels vary from study to study with no clearly dominant choices. In many instances, tolerance levels are not symmetric (e.g. 10% on size but 30% on book-to-market). A comprehensive list of published articles and their tolerance levels for the Journal of Finance, Journal of Financial Economics, Review of Financial Studies, Journal of Business and Journal of Financial and Quantitative Analysis for the 1997–2006 period is available from the authors upon request. Generally, if no match is found within the set defined by the tolerance bands the closest match is selected by relaxing first the tolerance requirements then the level of SIC matching iteratively until no SIC match is required and the firm with the closest criteria match is used.

  15. Barber and Lyon (1997), Lyon et al. (1999), Mitchell and Stafford (2000) and others all investigate various aspects of some of the test statistics but not the large set of alternative specifications generated in different empirical applications.

  16. Because the tests are independent, in the application of our proposed sequence of tests, an event firm can be included in only the quarters for which data is available. We exclude such a process here to ensure comparability to prior studies.

  17. Brown and Warner (1980) investigate characteristic-based matching in short-term event studies where event firms were matched to control firms on beta.

  18. The papers cited as being representative do not represent the exhaustive list of all papers employing each particular technique. As previously mentioned, there are a myriad of modifications to basic long-term return estimation. These techniques are representative of the vast majority in basic form.

  19. Indicated simultaneously within the tables on the right hand side with the number 1.

  20. Indicated within the tables on the right hand side with the number 2.

  21. Indicated within the tables on the right hand side with the number 3.

  22. Indicated within the tables on the right hand side with the number 4.

  23. Indicated within the tables on the right hand side with the number 5.

  24. Monthly versions of the tables are available upon request. The evidence in them shows that for a given size of persistent effect, quarterly tests are well-specified and have power equal to or greater than monthly tests.

  25. The induced abnormal returns are reported on a quarterly basis. Thus, a 5% induced abnormal return is equivalent to an annual difference in returns of 21.6%.

  26. While we have not included the bias statistics results here, they are available upon request. It is interesting to note that when the bias is calculated for the differing portfolios at each stage of the sequential matching process, there is no discernable pattern in sign, size or statistical significance. As previously mentioned, if characteristic-based matching works as hypothesized, the bias should be smaller for early matches and larger for later matches with statistical significant differences from zero occurring later in the matching process. This lack of pattern suggests that the reason that the covariance does not increase is because the firms aren’t actually “similar” in a statistical sense even though they satisfy the ad hoc matching rules created by researchers.

  27. Barber and Lyon (1997) find that the market mean is mis-specified when using yearly BHARs at and beyond 1-year. By using quarterly data, we provide a mechanism for testing out to 2 years that is well-specified and has a relatively high level of power.

  28. We are grateful to Stephen Brown for the discussion that led us to refer to this as an error in classification or categorization.

  29. Our findings from this and prior tables also have relevance to the calendar-time matching technique. Regardless of rebalancing, the first-quarter results presented here are the best that can be achieved by rebalancing. Since the first-quarter results in Table 2 are still dominated by portfolio comparison techniques, using a portfolio control sample is also preferable to the much more costly calendar-time portfolio technique.

  30. Speiss and Affleck-Graves (1999) examine long-run performance of debt issues; Krishnan and Laux (2005) and Howe and Lee (2006) examine preferred stock long-run performance; Yang and Lau (2010) examine long-run performance of Yankee stock offerings and Chen et al. (2009) examine the long-run reaction to share repurchases.

References

  • Ang JS, Zhang S (2004) An evaluation of testing procedures of long-term event studies. Rev Quant Financ Acc 23:251–274

    Article  Google Scholar 

  • Barber BM, Lyon JD (1996) Detecting abnormal operating performance: the empirical power and specification of test statistics. J Financ Econ 41:359–399

    Article  Google Scholar 

  • Barber BM, Lyon JD (1997) Detecting long-run abnormal stock returns: the empirical power and specification of test statistics. J Financ Econ 43:341–372

    Article  Google Scholar 

  • Brown SJ, Warner JB (1980) Measuring security performance. J Financ Econ 8:205–258

    Article  Google Scholar 

  • Brown SJ, Warner JB (1985) Using daily stock returns: the case of event studies. J Financ Econ 14:3–31

    Article  Google Scholar 

  • Byoun S (2004) Stock performance following seasoned stock-warrant unit offering. J Bus 77:75–100

    Article  Google Scholar 

  • Carhart MM (1997) On persistence in mutual fund performance. J Finan 52:57–82

    Article  Google Scholar 

  • Carpenter JN, Remmers B (2001) Executive stock option exercises and insider information. J Bus 74(4):513–534

    Article  Google Scholar 

  • Chen HK, Chen YS, Huang CW, Wang Y (2009) Managerial response to initial market reactions on share repurchases. Rev Pacific Basin Finan Markets Policies 12:455–474

    Article  Google Scholar 

  • Chou DW, Gombola M, Liu FY (2006) Earnings management and stock performance of reverse leveraged buyouts. J Finan Quant Anal 41:407–438

    Article  Google Scholar 

  • Chou DW, Gombola M, Liu FY (2010) Earnings management and long-run stock performance following private equity placements. Rev Quant Financ Acc 34:225–245

    Article  Google Scholar 

  • Clarke J, Dunbar C, Kahle K (2004) The long-run performance of secondary equity issues: a test of the windows of opportunity hypothesis. J Bus 77(3):575–603

    Article  Google Scholar 

  • Datta S, Iskandar-Datta M, Raman K (2001) Executive compensation and corporate acquisition decision. J Finan 56(6):2299–2336

    Article  Google Scholar 

  • Dichev ID, Piotroski JD (2001) The long-run stock returns following bond ratings changes. J Finan 55:173–203

    Article  Google Scholar 

  • Dolley J (1933) Characteristics and procedure of common stock split-ups. Harv Bus Rev 11:316–326

    Google Scholar 

  • Fama EF (1998) Market efficiency, long-term returns, and behavioral finance. J Financ Econ 49:283–306

    Article  Google Scholar 

  • Fama EF, French KR (1993) Common risk factors in the returns on stocks and bonds. J Financ Econ 33:3–56

    Article  Google Scholar 

  • Howe JS, Lee H (2006) The long-run stock performance of preferred stock issues. Rev Finan Econ 15:237–250

    Article  Google Scholar 

  • Ikenberry D, Lakonishok J, Vermaelen T (1995) The under-reaction to open market share repurchases. J Financ Econ 39:181–208

    Article  Google Scholar 

  • Jaffe JF (1974) Special information and insider trading. J Bus 47:411–428

    Article  Google Scholar 

  • Kothari SP, Warner JB (1997) Measuring long-horizon security price performance. J Financ Econ 43:301–339

    Article  Google Scholar 

  • Kothari SP, Warner JB (2005) Econometrics of event studies. In: Espen Eckbo B (ed) Handbook in empirical finance. North Holland

  • Krishnan CNV, Laux PA (2005) Misreaction. J Finan Quant Anal 40:403–434

    Article  Google Scholar 

  • Loughran T, Ritter J (2000) Uniformly least powerful tests of market efficiency. J Financ Econ 55:361–389

    Article  Google Scholar 

  • Lyon JD, Barber BM, Tsai CL (1999) Improved methods for tests of long-run abnormal stock returns. J Finan 54:165–201

    Article  Google Scholar 

  • Mandelker G (1974) Risk and return: the case of merging firms. J Financ Econ 1:303–335

    Article  Google Scholar 

  • McConnell JJ, Osbilgin M, Wahal S (2001) Spin-offs, ex ante. J Bus 74:245–280

    Article  Google Scholar 

  • Mitchell ML, Stafford E (2000) Managerial decisions and long-term stock price performance. J Bus 73:287–329

    Article  Google Scholar 

  • Palmon D, Sudit EF, Yezegel A (2009) The value of columnist’s stock recommendations: an event study approach. Rev Quant Financ Acc 33:209–232

    Article  Google Scholar 

  • Prevost AK, Rao R (2000) Of what value are shareholder proposals sponsored by public pension funds? J Bus 73:177–204

    Article  Google Scholar 

  • Savickas R (2003) Event-induced volatility and test for abnormal performance. J Finan Res 26:165–178

    Article  Google Scholar 

  • Speiss DK, Affleck-Graves J (1999) The long-run performance of stock returns following debt offerings. J Financ Econ 54:45–73

    Article  Google Scholar 

  • Yang T, Lau ST (2010) An empirical investigation of Yankee stock offerings. Rev Quant Financ Acc 34:351–370

    Article  Google Scholar 

Download references

Acknowledgments

We would like to thank Stephen Brown, Kim Sawyer, Ted Moore, Jeff Netter, LeRoy Brooks, Terry Shevlin, Rob Brown, Steven Mann, participants at the 2006 Financial Management Association Meetings and 2007 Southern Finance Association Meetings for their valuable suggestions and conversations regarding this paper. Any remaining errors are our own.

Author information

Authors and Affiliations

  1. Department of Information Systems and Quantitative Studies, Rawls College of Business, Texas Tech University, Lubbock, TX, 79409, USA

    Ronald Bremer

  2. Department of Finance, Albers School of Business, Seattle University, 901 12th Avenue, Seattle, WA, 98122-1090, USA

    Bonnie G. Buchanan

  3. Department of Finance and Real Estate, Kogod School of Business, American University, 4400 Massachusetts Ave NW, Washington, DC, 20016-8044, USA

    Philip C. English II

Authors
  1. Ronald Bremer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bonnie G. Buchanan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Philip C. English II
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bonnie G. Buchanan.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bremer, R., Buchanan, B.G. & English, P.C. The advantages of using quarterly returns for long-term event studies. Rev Quant Finan Acc 36, 491–516 (2011). https://doi.org/10.1007/s11156-010-0191-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11156-010-0191-2

Keywords

JEL Classification

Search

Navigation