Advancing the iid Test Based on Integration across the Correlation Integral: Ranges, Competition, and Power
Abstract
This paper builds on Kočenda (2001) and extends it in two ways. First, two new intervals of the proximity parameter ε (over which the correlation integral is calculated) are specified. For these ε- ranges new critical values for various lengths of the data sets are introduced and through Monte Carlo studies it is shown that within new ε-ranges the test is even more powerful than within the original ε-range. A sensitivity analysis of the critical values with respect to ε-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 ε-ranges with the original one shows that the test within the new ε-ranges is able to detect hidden patterns with much higher precision. Finally, new user-friendly and fast software is introduced.Download Info
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Paper provided by EconWPA in its series Econometrics with number 0409001.Length: 40 pages
Date of creation: 02 Sep 2004
Date of revision:
Handle: RePEc:wpa:wuwpem:0409001
Note: Type of Document - pdf; pages: 40. Paper has the link to a webpage to download the software.
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Web page: http://128.118.178.162
Related research
Keywords: chaos; nonlinear dynamics; correlation integral; Monte Carlo; single-blind competition; power tests; high-frequency economic and financial data;Other versions of this item:
- 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 - Economic Institute, Prague.
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-09-05 (All new papers)
- NEP-ECM-2004-09-05 (Econometrics)
- NEP-ETS-2004-09-05 (Econometric Time Series)
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References listed on IDEASPlease report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- 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.
- 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 - Economic Institute, Prague.
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