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A simulation on the presence of competing bidders in mergers and acquisitions

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  • Aintablian, Sebouh
  • Khoury, Wissam El

Abstract

The current paper applies Monte Carlo simulation on the presence of competing bidders in mergers and acquisitions. We present a new approach for quantifying uncertainty and use a Brownian model where “the presence of a competing bidder” is the random variable. Our model sets its boundaries by employing physical random number generators. The calculation of boundaries enables the simulation of “certainty” about the presence of a competing bidder, and thereafter, the prediction of the geometric Brownian motion path. We use difference in country and industry as proxies for uncertainty and incorporate them into the model. By applying a sample of 3278 acquisitions we find that the slope of the geometric Brownian motion is increasing.

Suggested Citation

  • Aintablian, Sebouh & Khoury, Wissam El, 2017. "A simulation on the presence of competing bidders in mergers and acquisitions," Finance Research Letters, Elsevier, vol. 22(C), pages 233-243.
    • Handle: RePEc:eee:finlet:v:22:y:2017:i:c:p:233-243
    DOI: 10.1016/j.frl.2017.03.002
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    References listed on IDEAS

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    1. repec:dau:papers:123456789/4273 is not listed on IDEAS
    2. Cain, Matthew D. & Denis, David J. & Denis, Diane K., 2011. "Earnouts: A study of financial contracting in acquisition agreements," Journal of Accounting and Economics, Elsevier, vol. 51(1-2), pages 151-170, February.
    3. Corwin Joy & Phelim P. Boyle & Ken Seng Tan, 1996. "Quasi-Monte Carlo Methods in Numerical Finance," Management Science, INFORMS, vol. 42(6), pages 926-938, June.
    4. Povel, Paul & Sertsios, Giorgo, 2014. "Getting to know each other: The role of toeholds in acquisitions," Journal of Corporate Finance, Elsevier, vol. 26(C), pages 201-224.
    5. Eric Fournié & Jean-Michel Lasry & Pierre-Louis Lions & Jérôme Lebuchoux & Nizar Touzi, 1999. "Applications of Malliavin calculus to Monte Carlo methods in finance," Finance and Stochastics, Springer, vol. 3(4), pages 391-412.
    6. Bris, Arturo, 2002. "Toeholds, takeover premium, and the probability of being acquired," Journal of Corporate Finance, Elsevier, vol. 8(3), pages 227-253, July.
    7. Ibáñez, Alfredo & Zapatero, Fernando, 2004. "Monte Carlo Valuation of American Options through Computation of the Optimal Exercise Frontier," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(2), pages 253-275, June.
    8. Cain, Matthew D. & Denis, David J. & Denis, Diane K., 2011. "Earnouts: A study of financial contracting in acquisition agreements," Journal of Accounting and Economics, Elsevier, vol. 51(1), pages 151-170.
    9. N. Meinshausen & B. M. Hambly, 2004. "Monte Carlo Methods For The Valuation Of Multiple‐Exercise Options," Mathematical Finance, Wiley Blackwell, vol. 14(4), pages 557-583, October.
    10. Boyle, Phelim P., 1977. "Options: A Monte Carlo approach," Journal of Financial Economics, Elsevier, vol. 4(3), pages 323-338, May.
    11. Boyle, Phelim & Broadie, Mark & Glasserman, Paul, 1997. "Monte Carlo methods for security pricing," Journal of Economic Dynamics and Control, Elsevier, vol. 21(8-9), pages 1267-1321, June.
    12. Jérôme B. Detemple & Ren Garcia & Marcel Rindisbacher, 2003. "A Monte Carlo Method for Optimal Portfolios," Journal of Finance, American Finance Association, vol. 58(1), pages 401-446, February.
    13. Spassimir H. Paskov & Joseph F. Traub, 1995. "Faster Valuation of Financial Derivatives," Working Papers 95-03-034, Santa Fe Institute.
    14. Michael B. Giles, 2008. "Multilevel Monte Carlo Path Simulation," Operations Research, INFORMS, vol. 56(3), pages 607-617, June.
    15. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
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    More about this item

    Keywords

    Mergers; Acquisitions; Competing bidders; Monte Carlo simulation; Brownian motion; Uncertainty; Random number generators;
    All these keywords.

    JEL classification:

    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance

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