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On the validity of conventional statistical tests given evidence of non-synchronous trading and non-linear dynamics in returns generating process

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  • Samir Saadi
  • Devinder Gandhi
  • Khaled Elmawazini

Abstract

Based on the recent developments in market microstructure and applications of nonlinear dynamics and chaos theory to financial time series, the subsequent article questions the validity of traditional methods used to test the efficient market hypothesis. In particular, it emphasizes the invalidity of unit roots tests since they are not predictability tests.

Suggested Citation

  • Samir Saadi & Devinder Gandhi & Khaled Elmawazini, 2006. "On the validity of conventional statistical tests given evidence of non-synchronous trading and non-linear dynamics in returns generating process," Applied Economics Letters, Taylor & Francis Journals, vol. 13(5), pages 301-305.
    • Handle: RePEc:taf:apeclt:v:13:y:2006:i:5:p:301-305
    DOI: 10.1080/13504850500393402
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    Cited by:

    1. Lim, Kian-Ping, 2007. "Ranking market efficiency for stock markets: A nonlinear perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 445-454.
    2. Azubuike Samuel Agbam, 2015. "Tests of Random Walk and Efficient Market Hypothesis in Developing Economies: Evidence from Nigerian Capital Market," International Journal of Management Sciences, Research Academy of Social Sciences, vol. 5(1), pages 1-53.
    3. Kian-Ping Lim, 2009. "Efficiency tests of the UK financial futures markets and the impact of electronic trading systems: a note on relative market efficiency," Applied Economics Letters, Taylor & Francis Journals, vol. 16(11), pages 1129-1132.
    4. Kian-Ping Lim & Robert Brooks, 2009. "Are Chinese stock markets efficient? Further evidence from a battery of nonlinearity tests," Applied Financial Economics, Taylor & Francis Journals, vol. 19(2), pages 147-155.
    5. Vasileios Kallinterakis & Nomana Munir & Mirjana Radovic-Markovic, 2010. "Herd Behaviour, Illiquidity and Extreme Market States," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 9(3), pages 305-324, December.
    6. Kian-Ping Lim & Robert Brooks, 2009. "On the validity of conventional statistical tests given evidence of nonsynchronous trading and nonlinear dynamics in returns generating process: a further note," Applied Economics Letters, Taylor & Francis Journals, vol. 16(6), pages 649-652.
    7. DeLisle, R. Jared & Diavatopoulos, Dean & Fodor, Andy & Kassa, Haimanot, 2022. "Variation in option implied volatility spread and future stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 152-160.
    8. Andreas Röthig, 2009. "Microeconomic Risk Management and Macroeconomic Stability," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-01565-6, December.
    9. Kian-Ping Lim, 2009. "Weak-form market efficiency and nonlinearity: evidence from Middle East and African stock indices," Applied Economics Letters, Taylor & Francis Journals, vol. 16(5), pages 519-522.
    10. Konstandinos Chourmouziadis & Dimitra K. Chourmouziadou & Prodromos D. Chatzoglou, 2021. "Embedding Four Medium-Term Technical Indicators to an Intelligent Stock Trading Fuzzy System for Predicting: A Portfolio Management Approach," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1183-1216, April.

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