Skip to main content
SpringerLink
Log in

Leverage and acquisition performance

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

Abstract

From an agency perspective, leverage may have a positive effect on firm performance by limiting managers’ ability to allocate resources to unproductive uses, as well as increasing pressure on them to perform well. Consequently, we might expect leverage to have a positive impact on acquisition performance. However, the increased risks associated with higher leverage, combined with the other risks inherent in an acquisition, could also cause managers to take actions to reduce risk even if doing so is contrary to value maximization. High debt levels might also limit managerial discretion over how resources are allocated during the acquisition process, which can have a negative impact on performance. We investigate the effect of leverage on post-acquisition stock performance and find that post-acquisition performance is decreasing in leverage brought by the target firm and in additional leverage taken on to execute the acquisition. This negative performance is clustered among acquirers who are already financially constrained. Our results are robust to various returns measurement methodologies and to the inclusion of several controls known to predict future returns. Our results also represent viable investment strategies, and suggest that the market underestimates difficulties that arise from acquisition-related increases in leverage.

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
Fig. 3

Similar content being viewed by others

Notes

  1. Loughran and Vijh (1997) report the results of an untabulated robustness check on whether post-acquisition returns for cash acquirers are explained by changes in acquirer debt to equity. They find that debt to equity does not appear to explain their results.

  2. One exception is that our estimated coefficient on target leverage is only marginally significant when we used time- and firm-clustered standard errors.

  3. Specifically, agency theory suggests that debt disciplines management by limiting their discretion on the use of cash flows. As we discuss in the next section, risk aversion is another aspect of agency theory that suggests high debt may not always be desirable.

  4. One anecdotal example from our data is COMFORCE Corporation (CFS), who acquired a highly leveraged target, Uniforce Temporary Personnel Inc., on February 14, 1998. CFS later warned investors that its high leverage may affect its ability to realize its financial objectives. In the same press release, CFS announced plans to continue to repurchase its debt in an effort to reduce its interest expense and improve its capital structure (PR Newswire, March 15, 2001). This suggests that CFS was diverting cash flows to debt reduction that would otherwise have been used to fund new investments (or returned to shareholders).

  5. In untabulated results we also compare reported cash levels from pre- to post-acquisition years. As expected, we find that cash significantly decreases from the pre- to post-acquisition period as debt obligations (with their required interest and principal payments) increase.

  6. These changes in leverage from year −1 to post-acquisition years are all statistically significant, except for the increase in leverage for stock acquisitions from year −1 to year +1. We note that the number of observations change the further we get from the acquisition year because of data availability problems. Our conclusions are the same if we examine only firms with data available as of year +5. Another concern is that our increases in leverage may be caused by decreases in total assets (i.e., a “denominator effect”). However, we find that total assets increase from years −1 to +5, ruling out this possibility.

  7. The significance of this difference is easily illustrated. Suppose firms A and B have $1,000 of debt requiring interest at 10 % and $4,000 of total assets measured using book value. However, Firm A has a market value of assets of $8,000 while firm B has a market value of assets of $5,000. Book leverage is 0.25 for both firms, but market leverage is lower for A (0.125) than for B (0.20) even though managers of both firms are obligated to pay $100 per year for interest. Further, if A’s market value decreases and B’s market value increases than A’s market leverage will appear to have increased and B’s will appear to have decreased even though there is no underlying change in either firm’s debt and interest costs. Firms with a high book-value leverage but low market-value leverage may be able to refinance their debt, depending on the prevailing condition of credit markets, but would incur transaction costs in doing so.

  8. However, in spite of the differences between our samples, when we use firm market value as our denominator instead of firm assets we also find evidence that leverage is beginning to decrease by year +4 after the acquisition, which is roughly consistent with Harford et al.’s results.

  9. This is not to say that stock consideration or holding of a high cash balance causes poor acquisition performance. For example, Shleifer and Vishny (2003) argue that managers may use stock as consideration when they recognize their stock price is overvalued (and, therefore, the firm would have low future returns even without an acquisition). We attempt to control for this by modeling manager’s endogenous choice in our analysis. However, even if stock consideration is only a signal and not the cause of poor future performance, the fact that future returns are predicable based on that prior signal suggests a market under-reaction.

  10. Petersen (2009) shows that although both Fama–MacBeth and Newey–West standard errors are effective against year effects, they are significantly biased in the presence of firm effects.

  11. As a robustness check, we add additional variables (such as Altman’s Z) from our returns regressions to our probit regression. Even with this “kitchen sink” approach, we find our conclusions are unchanged.

  12. SDC Platinum’s coverage is less complete for years before 1995.

  13. If any of our control firms are delisted before the end of the 2-year period, we include the delisting return of the control firm and replace that firm with a new control firm also selected as of the announcement date. If the acquiring firm is delisted before the end of the 2-year period, we include the delisting return and invest the remaining funds in our portfolio of peer firms (so that delisted firms do not disappear from our dataset).

  14. GICS are determined by Standard and Poor's, and are available from Compustat’s Price, Dividend, and Earnings (PDE) files. GICS codes are 8-digits long, and matching on the first 4 digits approximates the common practice of matching on the first 2-digits of a firm’s SIC code. Bhojraj et al. (1999) show that GICS codes are generally superior to SIC codes for financial research.

  15. One could argue that our use of matching firms also controls for management’s self-selection discussed earlier, and therefore the Heckman’s 2-step approach is unnecessary. However, matching assumes that manager’s private information is useless (Li and Prabhala 2007, page 53), and this seems unlikely in our setting.

  16. Added leverage requires information from the first quarter’s financial statements immediately following the consummation of the acquisition. To ensure that the market is aware of added leverage before we open our “post-acquisition” period, we wait until 45 days after the first acquirer quarter following target delisting before we open this period.

  17. This calculation has the potential to understate added leverage because post-acquisition total assets will include goodwill, which could be inflated by overpayment. This bias serves to work against our finding significant results. Also, to control for the possibility of overpayment, we include the target premium in our regressions, as we discuss in the next paragraph.

  18. We calculate abnormal target returns in the same manner as abnormal acquirer returns, using a reference portfolio of 4 firms based on industry, size, and book-to-market (and then matching on the closest fit to target leverage).

  19. The target premium here is smaller than that reported by Betton et al. (2009); however, their premium is based on raw target returns while ours is based on abnormal target returns.

  20. Although Altman’s Z is venerable, it remains a reasonably accurate predictor of financial distress (see Altman and Hotchkiss 2006) that is still commonly used in academic research (for example, see Chang et al. 2006; Kalay et al. 2007; Eisdorfer 2008; Guner et al. 2008).

  21. One difference is that Harford (1999) finds that his leverage measure loads significantly negatively, using the market value of leverage instead of the book value of leverage. This is a curious result that emphasizes the difference between using book value leverage and market value leverage, and could be a fruitful avenue of further investigation. To show that our subsequent results are not driven by our choice of leverage measure we substitute the market value of leverage in our probit regression and find (1) that it loads significantly negatively, just as Harford found, and (2) when using our revised Inverse Mills ratio from the “market-leverage” probit in our later regressions, our results are substantially the same. Finally, our results are similar if we include year dummies in our probit regression.

  22. To avoid confusion as to whether we are referring to p values based on corrected OLS standard errors following Li and Prabhala (2007) or clustered standard errors following Petersen (2009), all our references will be to clustered standard error p values, which are generally more conservative.

  23. We also note that acquirer returns are higher for small acquirers (+0.013), consistent with the findings of Moeller et al. (2004), but that this result hold only when we use OLS standard errors (p = 0.06). The significance disappears once clustered standard errors are used (p = 0.19).

  24. There are several speculative reasons as to why this might be. For example, Morck et al. (1990) argue that value-destructive acquisitions occur because managers place personal benefits from the acquisition above the interests of shareholders. This information is revealed to the market when the acquisition is announced, and the market’s response appears to be complete by the end of the interim period before the first quarterly financial statements are issued in the post-acquisition period.

  25. One drawback to our definition of post-acquisition returns beginning after the first quarter’s post-acquisition financial statements become available is that there may be a market response to information released after the target delisting but before the first quarter’s financial statements are made available. This works against our finding of significant results. Our selection of a post-acquisition period beginning only after the first quarter’s financial statements are released ensures that we are not peeking ahead when we include added leverage in our analysis.

  26. We also note that explanatory variables in the probit regression differ from those in our OLS (2nd stage) regression. This is econometrically permissible (for example, see Breen 1996, page 35. For another example of Heckman’s technique used in a similar manner to ours, see Louis 2005).

  27. We also investigate whether high-added-leverage acquirers, our worst-performers in Panel C of Table 5, show other indications of poor performance; specifically, whether they show less ability to take advantage of post-acquisition profitable opportunities. We conducted additional analyses (not included in a table in this paper, but available from the authors upon request) and found that high-added-leverage acquirers show a significant decrease in cash and a significant decrease in capital expenditures in the post-acquisition period, suggesting that these acquirers have less ability to make profitable investments in the post-acquisition period.

  28. For example, see http://accounting-information.net/accounting_information/financial_ratios/Interest_Coverage_Ratio-times_interest_earned_ratio.shtml. More sophisticated models to identify financially constrained firms exist (e.g., Kaplan and Zingales 1997; Whited and Wu 2006); however, the data requirements for these models increase our loss of observations and also introduce an endogeneity problem because they include variables that we already control for (e.g., acquirer size). In contrast, times-interest-earned is a measure that is independent of our other controls, requires little additional data, and is also likely to be familiar to most investors as it is covered in most financial statement analysis textbooks.

  29. Because we establish cutoffs based on the prior year, we lose 10 acquisitions from 1972 in this analysis. Our results are similar if we set an arbitrary cutoff at the 75 % percentile of target leverage from Table 2.

  30. Note that both the returns to the short-position and long-position strategies are each hedge returns. For example, the returns of 11 % for the short position result from shorting 430 acquisitions where target leverage is above our cutoff level and going long on the related portfolio of four matching firms per acquirer. Returns to the long position strategy are similarly determined. Our results suggest that only the short position strategy is successful at generating positive returns.

  31. We do not tabulate our split of Panel E combined returns into constrained and non-constrained acquirers because only 8 of the 50 acquirers were financially constrained. However, of those 8, abnormal returns were 76 % (as compared to the 31 % from the 50 observations in Panel E).

  32. We do not tabulate our results to breaking our observations into financially constrained versus non-constrained acquirers in our calendar time analysis because our results become more erratic with the reduction in observations.

  33. Similarly, more recent research by Cao and Lerner (2009) also suggests that the future returns of reverse leveraged buyout firms are not significantly decreasing in total leverage.

References

  • Agrawal A, Jaffe JF (2000) The post-merger performance puzzle. In: Cooper C, Gregory A (eds) Advances in mergers and acquisitions, vol 1. Elsevier, New York, pp 7–41

    Google Scholar 

  • Agrawal A, Jaffe JF, Mandelker GN (1992) The post-merger performance of acquiring firms: a re-examination of an anomaly. J Financ 47:1605–1621

    Google Scholar 

  • Allen DE, Soongswang A (2006) Post-takeover effects on Thai bidding firms: are takeovers in the bidder’s interests? Rev Pac Basin Financ Mark Polic 9:509–531

    Google Scholar 

  • Altman EI (1968) Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J Financ 23:589–609

    Google Scholar 

  • Altman EI, Hotchkiss E (2006) Corporate financial distress and bankruptcy. Wiley, Hoboken, NJ

    Google Scholar 

  • Anderson RI, Stowe JD, Xing X (2011) Does corporate diversification reduce firm risk? Evidence from diversifying acquisitions. Rev Pac Basin Financ Mark Polic 14:485–504

    Google Scholar 

  • Asquith P, Bruner RF, Mullins DW Jr (1983) The gains to bidding firms from merger. J Financ Econ 11:121–139

    Google Scholar 

  • Baker GP, Wruck KH (1989) Organizational changes and value creation in leveraged buyouts: the case of the O.M. Scott and Sons Company. J Financ Econ 25:163–190

    Google Scholar 

  • Banal-Estañol A, Seledslachts J (2011) Merger failures. J Econ Manag Strateg 20:589–624

    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

    Google Scholar 

  • Baxter ND (1967) Leverage, risk of ruin, and the cost of capital. J Financ 22:395–403

    Google Scholar 

  • Baysinger B, Hoskisson RE (1989) Diversification strategy and R&D intensity in multi-product firms. Acad Manag J 32:310–332

    Google Scholar 

  • Bernard VL (1987) Cross-sectional dependence and problems in inference in market-based accounting research. J Acc Res 25:1–48

    Google Scholar 

  • Betton S, Eckbo BE, Thorburn KS (2009) Merger negotiations and the toehold puzzle. J Financ Econ 91:158–178

    Google Scholar 

  • Bhagat S, Dong M, Hirshleifer D, Noah R (2005) Do tender offers create value? New methods and evidence. J Financ Econ 76:3–60

    Google Scholar 

  • Bhojraj S, Lee CMC, Oler DK (1999) What’s my line? A comparison of industry classification schemes for capital market research. J Acc Res 41:745–774

    Google Scholar 

  • Billet MT, King THD, Mauer DC (2004) Bondholder wealth effects in mergers and acquisitions: new evidence from the 1980s and 1990s. J Financ 59:107–135

    Google Scholar 

  • Bloom M, Milkovich GT (1998) Relationships among risk, incentive pay, and organizational performance. Acad Manag J 41:283–297

    Google Scholar 

  • Breen R (1996) Regression models: censored, sample selected, or truncated data. Sage Publications, Thousand Oaks, CA

    Google Scholar 

  • Cao J, Lerner J (2009) The performance of reverse leveraged buyouts. J Financ Econ 91:139–159

    Google Scholar 

  • Chidambaran NK, John K, Shangguan Z, Vasudevan G (2010) Hot and cold merger markets. Rev Quant Financ Acc 34:327–349

    Google Scholar 

  • Collins AR (1985) Expected utility, debt-equity structure, and risk balancing. Am J Agric Econ 67:627–629

    Google Scholar 

  • Collins AR (1997) Toward a positive economic theory of hedging. Am J Agric Econ 79:488–499

    Google Scholar 

  • COMFORCE Corporation (2001) COMFORCE Corporation announces repurchase of $5.2 million principal amount of payment-in-kind debentures. PR Newswire, March 15

  • Cutler D, Poterba J, Summers L (1991) Speculative dynamics. Rev Econ Stud 58:529–546

    Google Scholar 

  • DeBondt WFM, Thaler R (1985) Does the stock market overreact? J Financ 40:793–805

    Google Scholar 

  • Eckbo BE, Maksimovic V, Williams J (1990) Consistent estimation of cross-sectional models in event studies. Rev Financ Stud 3:343–365

    Google Scholar 

  • Eisdorfer A (2008) Empirical evidence of risk shifting in financially distressed firms. J Financ 63:609–637

    Google Scholar 

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

    Google Scholar 

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

    Google Scholar 

  • Fama EF, French KR (2007) Disagreement, tastes, and asset prices. J Financ Econ 83:667–689

    Google Scholar 

  • Franks J, Harris RS, Mayer C (1988) Means of payment in takeovers: results for the United Kingdom and the United States. In: Auerbach AJ (ed) Corporate takeovers: causes and consequences. University of Chicago Press, Chicago

    Google Scholar 

  • Gervais S, Odean T (2001) Learning to be overconfident. Rev Financ Stud 14:1–27

    Google Scholar 

  • Ghosh A, Jain PC (2000) Financial leverage changes associated with corporate mergers. J Corp Financ 6:377–402

    Google Scholar 

  • Gloy BA, Baker TG (2002) The importance of financial leverage and risk aversion in risk-management strategy selection. Am J Agric Econ 84:1130–1143

    Google Scholar 

  • Grossman SJ, Hart OD (1982) Corporate financial structure and managerial incentives. In: McCall JJ (ed) The economics of information and uncertainty. University of Chicago Press, Chicago, pp 107–137

    Google Scholar 

  • Grundy BD, Martin JS (2001) Understanding the nature of the risks and the source of the rewards to momentum investing. Rev Financ Stud 14:29–78

    Google Scholar 

  • Habeck MM, Kroger F, Tram MR (2000) After the merger—seven rules for successful post-merger integration. Pearson Education Limited, Great Britain

    Google Scholar 

  • Harford J (1999) Corporate cash reserves and acquisitions. J Financ 54:1969–1997

    Google Scholar 

  • Harford J, Klasa S, Walcott N (2009) Do firms have leverage targets? Evidence from acquisitions. J Financ Econ 93:1–14

    Google Scholar 

  • Harris M, Raviv A (1991) The theory of capital structure. J Financ 46:297–355

    Google Scholar 

  • Heckman JJ (1979) Sample selection bias as a specification error. Econometrica 47:153–162

    Google Scholar 

  • Hirshleifer DK, Hou S, Teoh H, Zhang Y (2004) Do investors overvalue firms with bloated balance sheets? J Acc Econ 38:297–331

    Google Scholar 

  • Hitt MA, Hoskisson RE, Ireland RD (1990) Mergers and acquisitions and managerial commitment to innovation in M-form firms. Strateg Manag J 11(Special issue):29–47

    Google Scholar 

  • Hitt MA, Hoskisson RE, Ireland RD, Harrison JS (1991) Effects of acquisitions on R&D inputs and outputs. Acad Manag J 34:693–706

    Google Scholar 

  • Hong H, Stein J (1999) A unified theory of underreaction, momentum trading and overreaction in asset markets. J Financ 54:2143–2184

    Google Scholar 

  • Huber PJ (1973) Robust regression: asymptotics, conjectures and Monte Carlo. Ann Stat 1:799–821

    Google Scholar 

  • Jarrell GA, Poulsen AB (1989) The returns to acquiring firms in tender offers: evidence from three decades. Financ Manag Autumn 18:12–19

    Google Scholar 

  • Jegadeesh N, Titman S (1993) Returns to buying winners and selling losers: implications for stock market efficiency. J Financ 48:65–91

    Google Scholar 

  • Jensen MC (1986) Agency costs, free cash flow, corporate finance and takeovers. Am Econ Rev 76:323–329

    Google Scholar 

  • Jensen MC, Meckling WH (1976) Theory of the firm: managerial behavior, agency costs and ownership structure. J Financ Econ 3:305–360

    Google Scholar 

  • Kalay A, Singhal R, Tashjian E (2007) Is Chapter 11 costly? J Financ Econ 84:772–796

    Google Scholar 

  • Kaplan SN (1989) The effects of management buyouts on operating performance and value. J Financ Econ 24:217–254

    Google Scholar 

  • Kaplan SN, Zingales L (1997) Do investment cash-flow sensitivities provide useful measures of financing constraints? Quart J Econ 112:169–216

    Google Scholar 

  • Kayhan A, Titman S (2007) Firms’ histories and their capital structures. J Financ Econ 83:1–32

    Google Scholar 

  • Korteweg A (2010) The net benefits to leverage. J Financ 65:2137–2170

    Google Scholar 

  • Kothari SP, Warner JB (2007) Econometrics of event studies. In: Eckbo BE (ed) Handbook of corporate finance, vol 1., Empirical corporate financeElsevier, Amsterdam, pp 3–36

    Google Scholar 

  • Leland HE (1998) Agency costs, risk management and capital structure. J Financ 53:1213–1243

    Google Scholar 

  • Lewellen WG (1971) A pure financial rationale for the conglomerate merger. J Financ 26:521–537

    Google Scholar 

  • Li K, Prabhala NR (2007) Self-selection models in corporate finance. In: Eckbo BE (ed) Handbook of corporate finance, vol 1: empirical corporate finance. Elsevier, Amsterdam, pp 37–86

    Google Scholar 

  • Lin W-C, Chang S-C (2012) Corporate governance and the stock market reaction to new product announcements. Rev Quant Financ Acc 39:273–291

    Google Scholar 

  • Loughran T, Vijh AM (1997) Do long-run shareholders benefit from corporate acquisitions? J Financ 52:1765–1790

    Google Scholar 

  • Louis H (2005) Acquirers’ abnormal returns and the non-big 4 auditor clientele effect. J Acc Econ 40:75–99

    Google Scholar 

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

    Google Scholar 

  • Maloney MT, McCormick RE, Mitchell ML (1993) Managerial decision making and capital structure. J Bus 66:189–217

    Google Scholar 

  • Martin KJ (1996) The method of payment in corporate acquisitions, investment opportunities, and management ownership. J Financ 51:1227–1246

    Google Scholar 

  • Miller KD, Bromiley P (1990) Strategic risk and corporate performance: an analysis of alternative risk measures. Acad Manag J 33:756–779

    Google Scholar 

  • Miller JS, Wiseman RM, Gomez-Mejia LR (2002) The fit between CEO compensation design and firm risk. Acad Manag J 45:745–756

    Google Scholar 

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

    Google Scholar 

  • Modigliani F, Miller MH (1963) Corporate income taxes and the cost of capital: a correction. Am Econ Rev 53:433–443

    Google Scholar 

  • Moeller SB, Schlingemann FP, Stulz RM (2004) Firm size and the gains from acquisitions. J Financ Econ 73:201–228

    Google Scholar 

  • Morck R, Shleifer A, Vishny RW (1990) Do managerial objectives drive bad acquisitions? J Financ 45:31–48

    Google Scholar 

  • Myers SC, Majluf NS (1984) Corporate financing and investment decisions when firms have information that investors do not have. J Financ Econ 13:187–221

    Google Scholar 

  • Oler DK (2008) Does acquirer cash level predict post-acquisition returns? Rev Acc Stud 13:479–511

    Google Scholar 

  • Oler DK, Waegelein JF (2011) Can long-term performance plans mitigate the negative effects of stock consideration and high cash for acquirers? Rev Quant Financ Acc 37:63–86

    Google Scholar 

  • Oler DK, Harrison JS, Allen MR (2008) The danger of misinterpreting short-window event study findings in strategic management research: an empirical illustration using horizontal acquisitions. Strateg Org 6:151–184

    Google Scholar 

  • Palepu KG (1990) Consequences of leveraged buyouts. J Financ Econ 27:247–262

    Google Scholar 

  • Petersen MA (2009) Estimating standard errors in finance panel data sets: comparing approaches. Rev Financ Stud 22:435–480

    Google Scholar 

  • Poterba J, Summers L (1988) Mean reversion in stock returns: evidence and implications. J Financ Econ 22:27–59

    Google Scholar 

  • Ramaswamy KP, Waegelein JF (2003) Firm financial performance following mergers. Rev Quant Financ Acc 20:115–126

    Google Scholar 

  • Rau PR, Vermaelen T (1998) Glamour, value, and the post-acquisition performance of acquiring firms. J Financ Econ 49:223–253

    Google Scholar 

  • Roll R (1986) The hubris hypothesis of corporate takeovers. J Bus 59:197–216

    Google Scholar 

  • Schlingemann FP (2004) Financing decisions and bidder gains. J Corp Financ 10:683–701

    Google Scholar 

  • Schultz P (2003) Pseudo market timing and the long-run underperformance of IPOs. J Financ 58:483–517

    Google Scholar 

  • Seth A (1990) Sources of value creation in acquisitions: an empirical investigation. Strateg Manag J 11:431–446

    Google Scholar 

  • Shelton LM (1988) Strategic business fits and corporate acquisitions: empirical evidence. Strateg Manag J 9:279–287

    Google Scholar 

  • Shim J (2011) Efficiency changes around mergers in the U.S. property-liability insurance industry: a data envelopment analysis. J Bus Econ Stud 17:77–96

    Google Scholar 

  • Shleifer A (2000) Inefficient markets. Oxford University Press, New York

    Google Scholar 

  • Shleifer A, Vishny RW (2003) Stock market driven acquisitions. J Financ Econ 70:295–311

    Google Scholar 

  • Shrivastava P (1986) Postmerger integration. J Bus Strateg 7:65–76

    Google Scholar 

  • Sirower ML (1997) The synergy trap. The Free Press, USA

    Google Scholar 

  • Slama MB, Saidane D, Fedhila H (2012) How to identify targets in the M&A banking operations? Case of cross-border strategies in Europe by line of activity. Rev Quant Financ Acc 38:209–240

    Google Scholar 

  • Sloan RG (1996) Do stock prices fully reflect information in accruals and cash flows about future earnings? Acc Rev 71:289–315

    Google Scholar 

  • Smith AJ (1990) Corporate ownership structure and performance. J Financ Econ 27:143–164

    Google Scholar 

  • Smith CW Jr, Warner JB (1979) Bankruptcy, secured debt, and optimal capital structure: a comment. J Financ 34:347–351

    Google Scholar 

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

    Google Scholar 

  • Stulz RM (1990) Managerial discretion and optimal financing policies. J Financ Econ 26:3–27

    Google Scholar 

  • Turk TA (1992) Takeover resistance, information leakage, and target firm value. J Manag 18:503–522

    Google Scholar 

  • Turvey CG, Baker TG (1990) A farm-level financial analysis of farmers’ use of futures and options under alternative farm programs. Am J Agric Econ 72:186–192

    Google Scholar 

  • Villalonga B (2004) Does diversification cause the “diversification discount”? Financ Manag Summ 33:5–27

    Google Scholar 

  • Walker MM (2000) Corporate takeovers, strategic objectives, and acquiring-firm shareholder wealth. Financ Manag Spring 29:53–66

    Google Scholar 

  • Whited TM, Wu G (2006) Financial constraints risk. Rev Financ Stud 19:531–559

    Google Scholar 

  • Wilber RS (2007) Why do firms repurchase stock to acquire another firm? Rev Quant Financ Acc 29:155–172

    Google Scholar 

  • Yen G, Lee CF (2008) Efficient market hypothesis (EMH): past, present, and future. Rev Pac Basin Financ Mark Polic 11:305–329

    Google Scholar 

  • Yook KC (2003) Larger return to cash acquisitions: signaling effect or leverage effect? J Bus 76:477–498

    Google Scholar 

  • Yu S (2012) New empirical evidence on the investment success of momentum strategies based on relative stock prices. Rev Quant Financ Acc 39:105–121

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Robins School of Business, University of Richmond, Richmond, VA, 23173, USA

    Jeffrey S. Harrison

  2. Area of Accounting, Rawls College of Business, Texas Tech University, Box 42101, Lubbock, TX, 79409, USA

    Matthew Hart & Derek K. Oler

Authors
  1. Jeffrey S. Harrison
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Matthew Hart
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Derek K. Oler
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeffrey S. Harrison.

Appendix: Variable definitions and calculations

Appendix: Variable definitions and calculations

Stock price and shares outstanding are taken from the CRSP database. All financial statement information is taken from the combined CRSP/Compustat (annual) database provided by Wharton Research Data Services (WRDS). Information is taken at the most recent month-end that is at least 30 days before the announcement of the acquisition. We assume a 3-month lag between a firm’s year-end and when annual financial statements are publicly available, and a 45 day lag between a firm’s quarter-end and when quarterly financial statements are publicly available.

Our multivariate BHARs are calculated as follows:

$$ {\text{BHAR}}_{{_{i} }} = \prod\limits_{t = s}^{e} {(1 + R_{i,t} } ) - \prod\limits_{t = s}^{e} {(1 + R_{{{\text{mp}},t}} } ) = {\text{BHR}}_{\text{firm}} - {\text{BHR}}_{\text{mp}} $$

Where: R i,t  = returns for firm i over the period beginning with day s and ending with day e, where s = day −2 and e = +2 relative to announcement for announcement period returns, s = day +3 and e = 45 days from the first fiscal quarter-end following the target delisting date for interim period returns, and s = day +1 relative to the end of the interim period and e = end of month 24 month later for post-acquisition returns, and R mp,t  = mean portfolio returns (from four peer firms) over the same period

Table 8 provides details on the calculations of our independent variables:

Table 8 Description and calculation of independent variables
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Harrison, J.S., Hart, M. & Oler, D.K. Leverage and acquisition performance. Rev Quant Finan Acc 43, 571–603 (2014). https://doi.org/10.1007/s11156-013-0385-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11156-013-0385-5

Keywords

JEL Classification

Search

Navigation