Tests of Long Memory: A Bootstrap Approach
Abstract
Many time series in diverse fields have been found to exhibit long memory. This paper analyzes the behaviour of some of the most used tests of long memory: the R/S analysis, the modified R/S, the Geweke and Porter-Hudak (GPH) test and the detrended fluctuation analysis (DFA). Some of these tests exhibit size distortions in small samples. It is well known that the bootstrap procedure may correct this fact. Here I examine the size and power of those tests for finite samples and different distributions, such as the normal, uniform, and lognormal. In the short-memory processes such as AR, MA and ARCH and long memory ones such as ARFIMA, p-values are calculated using the post-blackening moving-block bootstrap. The Monte Carlo study suggests that the bootstrap critical values perform better. The results are applied to financial return time series. Copyright Springer Science + Business Media, Inc. 2005Download Info
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Bibliographic Info
Article provided by Society for Computational Economics in its journal Computational Economics.
Volume (Year): 25 (2005)
Issue (Month): 1 (February)
Pages: 103-113
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Web page: http://www.springerlink.com/link.asp?id=100248
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Keywords: long-memory tests; bootstrap; time series;References
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Cajueiro, Daniel O. & Tabak, Benjamin M., 2010.
"Fluctuation dynamics in US interest rates and the role of monetary policy,"
Finance Research Letters,
Elsevier, vol. 7(3), pages 163-169, September.
- Daniel Oliveira Cajueiro & Benjamin M. Tabak, 2010. "Fluctuation Dynamics in US Interest Rates and the Role of Monetary Policy," Working Papers Series 206, Central Bank of Brazil, Research Department.
- Murphy, A. & Izzeldin, M., 2009.
"Bootstrapping long memory tests: Some Monte Carlo results,"
Computational Statistics & Data Analysis,
Elsevier, vol. 53(6), pages 2325-2334, April.
- Anthony Murphy & Marwan Izzeldin, 2006. "Bootstrapping long memory tests: some Monte Carlo results," Working Papers 574547, Lancaster University Management School, Economics Department.
- Eduardo Lima & Benjamin Tabak, 2009. "Tests of Random Walk: A Comparison of Bootstrap Approaches," Computational Economics, Society for Computational Economics, vol. 34(4), pages 365-382, November.
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