×

Memory and infrequent breaks. (English) Zbl 0968.91036

Summary: We study how processes with infrequent regime switching may generate a long memory effect in the autocorrelation function. In such a case, the use of a strong fractional \(I(d)\) model for economic or financial analysis may lead to spurious results.

MSC:

91E40 Memory and learning in psychology
PDF BibTeX XML Cite
Full Text: DOI

References:

[1] Andersen, T.; Bollerslev, T., Heterogenous information arrivals and return volatility dynamics: uncovering the long run in high frequency returns, Journal of finance, 52, 975-1005, (1997)
[2] Balke, N.; Fomby, T., Shifting trends, segmented trends and infrequent permanent shocks, Journal of monetary economics, 28, 61-85, (1989)
[3] Cioczek-Georges, R.; Mandelbrot, B., A class of micro pulses and antipersistent fractional Brownian motion, Stochastic processes and their applications, 60, 1-18, (1995) · Zbl 0846.60055
[4] Diebold, F.; Inoue, A., Long memory and structural change, (1999), Stern Business School New York University, Discussion Paper
[5] Diebold, F.; Rudebusch, G.D., Long memory and persistence in aggregate output, Journal of monetary economics, 24, 189-209, (1989)
[6] Ding, Z.; Engle, R.; Granger, C., A long memory property of stock market returns and a new model, Journal of empirical finance, 1, 83-106, (1993)
[7] Ghysels, E.; Gourieroux, C.; Jasiak, J., Stochastic volatility duration model, (1997), CREST Paris, Discussion Paper 9
[8] Gourieroux, C.; Jasiak, J., Nonlinear autocorrelograms: an application to intertrade durations, (1998), CREST Paris, Discussion Paper 9841
[9] Granger, C., Aspects of research strategies for time series analysis, (1999), University of California San Diego, Discussion Paper
[10] Granger, C.; Hyung, N., Occasional structural breaks and long memory, (1999), University of California San Diego, Discussion Paper 99.14
[11] Granger, C.; Marmol, F., The correlogram of long memory process plus a simple noise, (1998), University of California San Diego, Discussion Paper 98
[12] Granger, C.; Terasvirta, T., Simple nonlinear time series model with misleading linear properties, Economics letters, 62, 161-165, (1999) · Zbl 0918.90044
[13] Heath, D., Resnick, S., Samorodnitsky, G., 1997. Heavy tails and long range dependence in on/off processes and associated fluid models. Mathematical Operational Research, forthcoming. · Zbl 0981.60092
[14] Jasiak, J., Persistence in intertrade durations, Finance, 19, 166-195, (1999)
[15] Klemes, V., The Hurst phenomenon: a puzzle?, Water resources research, 10, 675-688, (1974)
[16] Lobato, I.; Savin, N., Real and spurious long memory properties of stock market data, Journal of business and economic statistics, 16, 261-283, (1997)
[17] Taqqu, M.; Levy, J., Using renewal processes to generate long range dependence, (), 73-89
[18] Taqqu, M.; Willinger, W.; Sherman, R., Proof of the fundamental result in self similar traffic modelling, Computer communication review, 27, 5-23, (1997)
[19] Willinger, W.; Taqqu, M.; Sherman, R.; Wilson, D., Self similarity through high variability: statistical analysis of Ethernet LAN traffic at the source level, IEEE/ACM transactions on networking, 5, 71-96, (1997)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.