IDEAS home Printed from https://ideas.repec.org/p/jrp/jrpwrp/2008-056.html
   My bibliography  Save this paper

Testing the Modigliani-Miller theorem directly in the lab: a general equilibrium approach

Author

Listed:
  • Prashanth Mahagaonkar

    (Max Planck Institute of Economics, EGP Group, Jena, Germany)

  • Jianying Qiu

    (Max Planck Institute of Economics, EGP Group, Jena, Germany)

Abstract

In this paper, we experimentally test the Modigliani-Miller theorem. Applying a general equilibrium approach and not allowing for arbitrage among firms with different capital structure, we are able to address a question fundamental to the valuation of firms: does capital structure affect the value of the firm? If so, how? We find that, consistent with the Modigliani-Miller theorem, experimental subjects well recognized the increased systematic risk of the equity with increasing leverage and accordingly demanded higher rate of return. Yet, this adjustment was not perfect: subjects underestimated the systematic risk of low leveraged equity whereas overestimated the systematic risk of high leveraged equity, resulting in a U shape weighted average cost of capital.

Suggested Citation

  • Prashanth Mahagaonkar & Jianying Qiu, 2008. "Testing the Modigliani-Miller theorem directly in the lab: a general equilibrium approach," Jena Economics Research Papers 2008-056, Friedrich-Schiller-University Jena.
  • Handle: RePEc:jrp:jrpwrp:2008-056
    as

    Download full text from publisher

    File URL: https://oweb.b67.uni-jena.de/Papers/jerp2008/wp_2008_056.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Shleifer, Andrei & Vishny, Robert W, 1997. "The Limits of Arbitrage," Journal of Finance, American Finance Association, vol. 52(1), pages 35-55, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. R. Andergassen, 2003. "Rational destabilising speculation and the riding of bubbles," Working Papers 475, Dipartimento Scienze Economiche, Universita' di Bologna.
    2. Dash, Saumya Ranjan & Maitra, Debasish, 2018. "Does sentiment matter for stock returns? Evidence from Indian stock market using wavelet approach," Finance Research Letters, Elsevier, vol. 26(C), pages 32-39.
    3. Florian Meier, 2020. "The Age of Cheap Money and Passive Investing: Are Pro Forma Earnings Value Relevant?," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 9(2), pages 1-1.
    4. Jun Liu, 2004. "Losing Money on Arbitrage: Optimal Dynamic Portfolio Choice in Markets with Arbitrage Opportunities," The Review of Financial Studies, Society for Financial Studies, vol. 17(3), pages 611-641.
    5. Julia Reynolds & Leopold Sögner & Martin Wagner, 2021. "Deviations from Triangular Arbitrage Parity in Foreign Exchange and Bitcoin Markets," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(2), pages 105-146, June.
    6. Chen, Catherine Huirong & Choy, Siu Kai & Tan, Yongxian, 2022. "The cash conversion cycle spread: International evidence," Journal of Banking & Finance, Elsevier, vol. 140(C).
    7. Hitoshi Matsushima, 2018. "Bank Runs and Minimum Reciprocity," CIRJE F-Series CIRJE-F-1099, CIRJE, Faculty of Economics, University of Tokyo.
    8. G. Menzies & R. Bird & P. Dixon & M. Rimmer, 2010. "Asset Price Regulators, Unite: you have Macroeconomic Stability to Win and the Microeconomic Losses are Second-order," Centre of Policy Studies/IMPACT Centre Working Papers g-205, Victoria University, Centre of Policy Studies/IMPACT Centre.
    9. Ben-Rephael, Azi & Kandel, Shmuel & Wohl, Avi, 2012. "Measuring investor sentiment with mutual fund flows," Journal of Financial Economics, Elsevier, vol. 104(2), pages 363-382.
    10. Adrian, Tobias, 2009. "Inference, arbitrage, and asset price volatility," Journal of Financial Intermediation, Elsevier, vol. 18(1), pages 49-64, January.
    11. Anella Munro, 2014. "Exchange rates, expected returns and risk," Reserve Bank of New Zealand Discussion Paper Series DP2014/01, Reserve Bank of New Zealand.
    12. Tobias J. Moskowitz & Mark Grinblatt, 2002. "What Do We Really Know About the Cross-Sectional Relation Between Past and Expected Returns?," Yale School of Management Working Papers ysm259, Yale School of Management.
    13. Campbell, John Y & Kim, Sangjoon & Lettau, Martin, 1998. "Dispersion and Volatility in Stock Returns: An Empirical Investigation," CEPR Discussion Papers 1923, C.E.P.R. Discussion Papers.
    14. Chang, Xiaochen & Guo, Songlin & Huang, Junkai, 2022. "Kidnapped mutual funds: Irrational preference of naive investors and fund incentive distortion," International Review of Financial Analysis, Elsevier, vol. 83(C).
    15. Stephen Morris & Hyun Song Shin, 2004. "Liquidity Black Holes," Review of Finance, Springer, vol. 8(1), pages 1-18.
    16. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    17. Bruno Biais & Fany Declerck & Sophie Moinas, 2016. "Who supplies liquidity, how and when?," BIS Working Papers 563, Bank for International Settlements.
    18. Chue, Timothy K. & Gul, Ferdinand A. & Mian, G. Mujtaba, 2019. "Aggregate investor sentiment and stock return synchronicity," Journal of Banking & Finance, Elsevier, vol. 108(C).
    19. Zhong, Angel, 2018. "Idiosyncratic volatility in the Australian equity market," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 105-125.
    20. Paul De Grauwe & Marianna Grimaldi, 2004. "Bubbles and Crashes in a Behavioural Finance Model," CESifo Working Paper Series 1194, CESifo.

    More about this item

    Keywords

    Modigliani-Miller Theorem; Experimental Study; Decision Making under Uncertainty; General Equilibrium;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jrp:jrpwrp:2008-056. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Markus Pasche (email available below). General contact details of provider: http://www.jenecon.de .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.