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The Beta intervalling effect during a deep economic crisis - evidence from Greece

Author

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  • Georgios Mantsios

    (University of the Aegean, Dept. of Mathematics-Track of Statistics & Actuarial-Financial Mathematics, Karlovassi 83200, Samos, Greece)

  • Stylianos Xanthopoulos

    (University of the Aegean, Dept. of Mathematics-Track of Statistics & Actuarial-Financial Mathematics, Karlovassi 83200, Samos, Greece)

Abstract

Purpose – The intervalling effect bias of beta refers to the sensitivity of beta estimation with respect to the reference time interval on which returns are measured and its manifestation may indicate the degree of market inefficiencies. The purpose of this paper is to study the intervalling effect bias within an environment and during a sample period that embraces the evolution of a deep economic crisis and show in particular that its intensity is profoundly magnified. Design/methodology/approach – The Athens Stock Exchange is studied via the market model during the sample period 2007-2012 that embraces the Greek debt restructuring. Two portfolios are formed to distinguish between large and small market capitalizations, three reference intervals are considered for measurement of returns (daily, weekly, monthly) and the respective betas are calculated via OLS simple regression. The results are compared to similar studies. The results are further confirmed by using a second proxy for the market portfolio. Findings – The intensity of the intervalling effect bias was very pronounced during this sample period with regard to all aspects of the phenomenon that similar studies have reported and to which the results of this paper are compared. Originality/value – This is the first time that the intervalling effect is examined in conjunction to a deep economic crisis environment. The intensity of the intervalling effect reflects the depth of the inefficiencies of a market for some period. As a consequence, some function measuring this intensity may be devised to serve as a measure of market inefficiencies.

Suggested Citation

  • Georgios Mantsios & Stylianos Xanthopoulos, 2016. "The Beta intervalling effect during a deep economic crisis - evidence from Greece," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 9(1), pages 19-26, April.
    • Handle: RePEc:tei:journl:v:9:y:2016:i:1:p:19-26
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    References listed on IDEAS

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    1. Scholes, Myron & Williams, Joseph, 1977. "Estimating betas from nonsynchronous data," Journal of Financial Economics, Elsevier, vol. 5(3), pages 309-327, December.
    2. Elton, Edwin J & Gruber, Martin J & Blake, Christopher R, 1996. "Survivorship Bias and Mutual Fund Performance," The Review of Financial Studies, Society for Financial Studies, vol. 9(4), pages 1097-1120.
    3. Hawawini, Gabriel, 1983. "Why beta shifts as the return interval changes," MPRA Paper 44893, University Library of Munich, Germany.
    4. Roll, Richard, 1977. "A critique of the asset pricing theory's tests Part I: On past and potential testability of the theory," Journal of Financial Economics, Elsevier, vol. 4(2), pages 129-176, March.
    5. Cohen, Kalman J. & Hawawini, Gabriel A. & Maier, Steven F. & Schwartz, Robert A. & Whitcomb, David K., 1983. "Friction in the trading process and the estimation of systematic risk," Journal of Financial Economics, Elsevier, vol. 12(2), pages 263-278, August.
    6. Brailsford, Timothy J. & Josev, Thomas, 1997. "The impact of the return interval on the estimation of systematic risk," Pacific-Basin Finance Journal, Elsevier, vol. 5(3), pages 357-376, July.
    7. Handa, Puneet & Kothari, S. P. & Wasley, Charles, 1989. "The relation between the return interval and betas : Implications for the size effect," Journal of Financial Economics, Elsevier, vol. 23(1), pages 79-100, June.
    8. Corhay, Albert, 1992. "The intervalling effect bias in beta: A note," Journal of Banking & Finance, Elsevier, vol. 16(1), pages 61-73, February.
    9. Ho, Li-Chin Jennifer & Tsay, Jeffrey J, 2001. "Option Trading and the Intervalling Effect Bias in Beta," Review of Quantitative Finance and Accounting, Springer, vol. 17(3), pages 267-282, November.
    10. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    11. Dimson, Elroy, 1979. "Risk measurement when shares are subject to infrequent trading," Journal of Financial Economics, Elsevier, vol. 7(2), pages 197-226, June.
    12. Pogue, Gerald A. & Solnik, Bruno H., 1974. "The Market Model Applied to European Common Stocks: Some Empirical Results," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 9(6), pages 917-944, December.
    13. Black, Fischer, 1972. "Capital Market Equilibrium with Restricted Borrowing," The Journal of Business, University of Chicago Press, vol. 45(3), pages 444-455, July.
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    Cited by:

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    More about this item

    Keywords

    intervalling effect; systematic risk; economic crisis; market inefficiency;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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