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Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power

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  • Evzen Kocenda
  • Lubos Briatka

Abstract

This paper builds on Kocenda (2001) and extends it in two ways. First, two new intervals of the proximity parameter epsilon (over which the correlation integral is calculated) are specified. For these epsilon-ranges new critical values for various lengths of the data sets are introduced and through Monte Carlo studies it is shown that within new epsilon-ranges the test is even more powerful than within the original epsilon-range. A sensitivity analysis of the critical values with respect to epsilon-range choice is also given. Second, a comparison with existing results of the controlled competition of Barnett et al. (1997) as well as broad power tests on various nonlinear and chaotic data are provided. The results of the comparison strongly favor our robust procedure and confirm the ability of the test in finding nonlinear dependencies. An empirical comparison of the new epsilon-ranges with the original one shows that the test within the new epsilon-ranges is able to detect hidden patterns with much higher precision. Finally, new user-friendly and fast software is introduced.

Suggested Citation

  • Evzen Kocenda & Lubos Briatka, 2004. "Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power," CERGE-EI Working Papers wp235, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  • Handle: RePEc:cer:papers:wp235
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Onour, Ibrahim, 2011. "Does credit for equity investments feedback on stock market volatility? Evidence from an emerging stock market," MPRA Paper 28001, University Library of Munich, Germany.
    2. repec:eee:asieco:v:50:y:2017:i:c:p:62-72 is not listed on IDEAS
    3. Gjika, Dritan & Horváth, Roman, 2013. "Stock market comovements in Central Europe: Evidence from the asymmetric DCC model," Economic Modelling, Elsevier, vol. 33(C), pages 55-64.
    4. Lubos Briatka, 2006. "How Big is Big Enough? Justifying Results of the iid Test Based on the Correlation Integral in the Non-Normal World," CERGE-EI Working Papers wp308, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    5. Alagidede, Paul & Lange, Ian, 2009. "Variability in coal prices: evidence from the U.S," Stirling Economics Discussion Papers 2009-01, University of Stirling, Division of Economics.

    More about this item

    Keywords

    Chaos; Nonlinear dynamics; Correlation integral; Monte Carlo; Single- blind competition; Power tests; High-frequency economic; Financial data;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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