The Stock Market between Classical and Behavioral Hypotheses: An Empirical Investigation of the Warsaw Stock Exchange

  • Mostafa Raeisi Sarkandiz Department of Management and Economics, University of Tabriz, Iran
  • Robabeh Bahlouli Department of Management and Economics, University of Tabriz, Iran
Keywords: Efficient Market Hypothesis, Informational Efficiency, Adaptive Market Hypothesis, Fractal Market Hypothesis, Warsaw Stock Exchange

Abstract

In empirical studies of the efficient market hypothesis using a classic approach, attention has generally been paid to the weak form of performance; other aspects of efficiency, such as informational efficiency, have not been addressed. Also, the study of alternative theories, such as behavioral hypotheses, is neglected. This article seeks to investigate not only the weak and informational forms of the efficient market hypothesis, but also to test the adaptive and fractal market hypotheses as two alternative theories by conducting an empirical study on the Warsaw Stock Exchange.

References

Ananzeh, I. (2016). Weak Form Efficiency of the Amman Stock Exchange: An Empirical Analysis (2000-2013). International Journal of Business and Management, 11(1):173–180.

Bai, J. and Perron, P. (1998). Estimation and Testing Linear Models with Multiple Structural Changes. Econometrica, 66(1):47–78.

Bai, J. and Perron, P. (2003). Computation and Analysis of Multiple Structural Change Models. Journal of Applied Econometrics, 18(1):1–22.

Beaver, W. H. (1981). Market Efficiency. Accounting Review, 56(1):23–27.

Borges, M. R. (2010). Efficiency Market Hypothesis in European Stock Markets. The European Journal of Finance, 16(7):711–726.

Charles, A., Darne, O., and Kim, J. H. (2012). Exchange Rate Return Predictability and the Adaptive Market Hypothesis: Evidence from Major Foreign Exchange Rate. Journal of International Money and Finance, 31(6):1607–1626.

Chow, G. C. (1960). Tests of Equality Between Sets of Coefficients in Two Linear Regressions. Econometrica, 28(3):591–605.

Chow, K. V. and Denning, K. C. (1993). A Simple Multiple Variance Ratio Test. Journal of Econometrics, 58(3):385–401.

Cochrane, J. H. (1991). A Critique of the Application of Unit Root Tests. Journal of Economics Dynamics and Control, 15(2):275–284.

Cressie, N. A. C. and Whitford, H. J. (1986). How to Use the Two Sample t-test. Biometrical Journal, 28(2):131–148.

Dedunu, H. H. (2017). Weak Form Efficiency of the Sri Lankan Stock Market From 2010-2014. IOSR-Journal of Economics and Finance, 8(3):75–81.

Diba, B. T. and Grossman, H. I. (1988). Explosive Rational Bubbles in Stock Prices. American Economic Review, 78(3):520–530.

Dickey, D. A. and Fuller, W. A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49(4):1057–1072.

Dragota, V., Ciobanu, A., Cotarama, D., Semenescu, A., and Lacatus, C. (2009). Minority Shareholders’ Protection: The Romanian Experience. Theoretical and Applied Economics, 2(2):35–48.

Eakins, S. and Mishkin, F. (2012). Financial Markets and Institutions . Massachusetts.

Elliott, G., Rothenberg, T. S., and Stock, J. H. (1996). Efficient Tests for an Autoregressive Unit Root. Econometrica, 64(4):813–836.

Evans, G. (1991). Pitfalls in Testing for Explosive Bubbles in Asset Prices. American Economic Review, 81(4):922–930.

Fama, E. F. (1965). The Behavior of Stock-Market Prices. The Journal of Business, 38(1):34– 105.

Gyamfi, E. N. (2018). Adaptive Market Hypothesis: Evidence from the Ghanaian Stock Market. Journal of African Business, 19(2):195–209.

Hall, P. (1992). On the Removal of Skewness by Transformation. Journal of the Royal Statistical Society Series, 54(1):221–228.

Hiremath, G. S. and Narayan, S. (2016). Testing the Adaptive Market Hypothesis and its Determinants for the Indian Stock Market. Financial Research Letters, 19(C):173–180.

Keynes, J. M. (1936). The General Theory of Employment, Interest, and Money. Macmillan.

Kim, J. H., Shamsuddin, A., and Lim, K. P. (2011). Stock Returns Predictability and the Adaptive Market Hypothesis: Evidence from Century-Long U.S. Data. Journal of Empirical Finance, 18(5):868–879.

Kwiatkowski, D., Phillips, P. C., Schmidt, P., and Shin, Y. (1992). Testing the Null Hypothesis of Stationary Against the Alternative of a Unit Root. Journal of Econometrics, 54(1-3):159–178.

Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. The Journal of Portfolio Management, 30(5):15–29.

Lo, A. W. (2012). Reading about the Financial Crisis: A Twenty-One-Book Review. Journal of Economic Literature, 50(1):151–178.

Lo, A. W. and Mackinley, C. A. (1988). Stock Market Prices Do Not Follow Random Walks: Evidence from a Simple Specification Test. The Review of Financial Studies, 1(1):41–66.

Morales, R., Matteo, D., T., G. R., and Aste, T. (2012). Dynamical Generalized Hurst Exponent as a Tool to Monitor Unstable Periods in Financial time series. Physica A: Statistical Mechanics and its Applications, 391(11):3180–3189.

Nagayasu, J. (2003). The Efficiency of the Japanese Equity Market. Working Paper WP/03/142, International Monetary Fund, Washington, D.C.

Neely, C. J., Weller, P. A., and Ulrich, J. M. (2009). The Adaptive Market Hypothesis: Evidence from Foreign Exchange Market. Journal of Financial and Quantitative Analysis, 44(2):467–488.

Ng, S. and Perron, P. (2001). Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power. Econometrica, 69(6):1519–1554.

Oprean, C., Tanasescu, C., and Bucur, A. (2017). A new proposal for efficiency quantification of capital markets in the context of complex nonlinear dynamics and chaos. Economic Research-Ekonomska Istrazivanja, 30(1):1669–1692.

Panas, E. and Ninni, V. (2010). The Distribution of London Metal Exchange Prices: A Test of the Fractal Market Hypothesis. European Research Studies Journal, 13(2):192–210.

Perron, P. (1989). The Great Crash,The Oil Price Shock,and the Unit Root Hypothesis. Econometrica, 57(6):1361–1401.

Peters, E. E. (1994). Fractal market analysis. Wiley, New York.

Phillips, P. C. and Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2):335–346.

Phillips, P. C., Shi, S.-P., and Yu, J. (2015). Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500. International Economic Review, 56(4):1043–1078.

Phillips, P. C., Wu, Y., and Yu, J. (2011). Explosive Behavior in the 1990s Nasdaq: When Did Exuberance Escalate Asset Values. International Economic Review, 52(1):201–226.

Resta, M. (2012). Hurst Exponent and its Applications in Time-series Analysis. Recent Patents on Computer Science, 5(3):211–219.

Risso, W. A. (2008). The Informational Efficiency and the Financial Crashes. Research in International Business and Finance, 22(3):396–408.

Shaker, A. M. (2013). Testing the Weak-form Efficiency of the Finnish and Swedish Stock Markets. European Journal of Business and Social Sciences, 2(9):176–185.

Shannon, C. E. (1948). A Mathematical Theory of Communication. Bell System Technical Journal, 27(3):379–423.

Shao, X. and Wu, W. B. (2007). Asymptotic Spectral Theory for Nonlinear Time Series. The Annals of Statistics, 35(4):1773–1801.

Shiller, R. (1979). The Volatility of Long-term Interest Rates and Expectations Models of the Term Structure. Journal of Political Economy, 87(6):1190–1219.

Shleifer, A. (2000). Inefficient Markets: An Introduction to Behavioural Finance. Clarendon Lectures in Economics. OUP Oxford.

Soteriou, A. and Svensson, L. (2017). Testing the Adaptive Market Hypothesis on the OMXS30 Stock Index: 1986-2014 (Master Thesis). Jonkoping International Business School, Jonkoping.

Todea, A., Ciupac-Ulici, M., and Silaghi, S. (2009). Adaptive Market Hypothesis: Evidence from Asia-Pacific Financial Markets. The Review of Finance and Banking, 1(1):7–13.

Van Quang, T. (2005). The Fractal Market Analysis and its Application on Czech Conditions. Acta Oeconomica Pragensia, 13(1):101–111.

Wald, A. and Wolfowitz, J. (1940). On a Test Whether Two Samples are from the Same Population. Annals of Mathematical Statistics, 11(2):147–162.

Wu, S. (2010). Lag Length Selection in DF-GLS Unit Root Tests. Communications in Statistics-Simulation and Computation, 39(8):1590–1604.

Published
2019-09-24
How to Cite
Raeisi Sarkandiz, M., & Bahlouli, R. (2019). The Stock Market between Classical and Behavioral Hypotheses: An Empirical Investigation of the Warsaw Stock Exchange. Econometric Research in Finance, 4(2), 67 - 88. https://doi.org/10.33119/ERFIN.2019.4.2.1
Section
Articles
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