Occasional Structural Breaks and Long Memory
This paper shows that a linear process with breaks can mimic autocorrelations and other properties of I(d) processes, where d can be a fraction. Simulation results show that S&P 500 absolute stock returns are more likely to show the "long memory" property because of the presence of breaks in the series rather than an I(d) process.
References listed on IDEAS
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- Jushan Bai & Pierre Perron, 1998.
"Estimating and Testing Linear Models with Multiple Structural Changes,"
Econometric Society, vol. 66(1), pages 47-78, January.
- Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
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- Robert F. Engle & Aaron D. Smith, 1999. "Stochastic Permanent Breaks," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 553-574, November.
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- Jushan Bai, 1995. "Estimating Multiple Breaks One at a Time," Working papers 95-18, Massachusetts Institute of Technology (MIT), Department of Economics.
- Chen, Chung & Tiao, George C, 1990. "Random Level-Shift Time Series Models, ARIMA Approximations, and Level-Shift Detection," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 83-97, January.
- Marmol, Francesc & Granger, C.W.J. (Clive William John), 1998. "The correlogram of a long memory process plus a simple noise," DES - Working Papers. Statistics and Econometrics. WS 9820, Universidad Carlos III de Madrid. Departamento de Estadística.
- Nunes, Luis C. & Kuan, Chung-Ming & Newbold, Paul, 1995. "Spurious Break," Econometric Theory, Cambridge University Press, vol. 11(04), pages 736-749, August. Full references (including those not matched with items on IDEAS)
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