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Occasional Structural Breaks and Long Memory

154 citations0/0 files storedRePEc: Research Papers in Economics

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Complex Systems and Time Series Analysis Financial Markets and Investment Strategies Financial Risk and Volatility Modeling

Abstract

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. KEY WORDS: Occasional Structural Breaks; Long Memory; Autocorrelation JEL classification: C22 Preliminary, Comments Welcome 2 1. Introduction There have been several works analyzing the long-run properties of stock returns. Granger and Ding (1995a,b) considered long return series, using the well-known Standard and Poor's (S&P) 500 index of about 17,000 daily observations, and established a set of temporal and distributional properties for such series. They suggested that the absolute returns are well characterized by long memory process, but the parameter estimates of the long-memory model sometimes vary considerably from one subseries to the next as show...

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References

1983THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS 1999Volatility in Emerging Stock Markets 1988Estimating the number of change-points via Schwarz' criterion 1996Varieties of long memory models 1999A simple nonlinear time series model with misleading linear properties 1990Random Level-Shift Time Series Models, ARIMA Approximations, and Level-Shift Detection 1998Change of structure in financial time series, long range dependence and the GARCH model

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2002A nonlinear long memory model, with an application to US unemployment 2002Bayesian methods for change‐point detection in long‐range dependent processes 2001Memory and infrequent breaks 2005Level Shifts and the Illusion of Long Memory in Economic Time Series 2001Testing for long memory in the presence of a general trend 2004Long memory versus structural breaks: An overview 2016Treating Time with All Due Seriousness

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