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Stochastic Permanent Breaks

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  • Engle, Robert F
  • Smith, Aaron

Abstract

This paper aims to bridge the gap between processes where shocks are permanent and those with transitory shocks by formulating a process in which the long run impact of each innovation is time varying and stochastic. Frequent transitory shocks are supplemented by occasional permanent shifts. The stochastic permanent breaks (STOPBREAK) process is based on the premise that a shock is more likely to be permanent if it is large than if it is small. This formulation is motivated by a class of processes that undergo random structural breaks. Consistency and asymptotic normality of quasi maximum likelihood estimates is established and locally best hypothesis tests of the null of a random walk are developed. The model is applied to relative prices of pairs of stocks and significant test statistics result

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Bibliographic Info

Paper provided by Department of Economics, UC San Diego in its series University of California at San Diego, Economics Working Paper Series with number qt99v0s0zx.

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Date of creation: 01 Jan 1998
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Handle: RePEc:cdl:ucsdec:qt99v0s0zx

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Related research

Keywords: structural breaks; nonlinear moving average; unit root; quasi maximum likelihood estimation; Neyman-Pearson testing; locally best test; temporary cointegration;

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  1. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-28, August.
  2. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
  3. Granger, Clive W. J. & Swanson, Norman R., 1997. "An introduction to stochastic unit-root processes," Journal of Econometrics, Elsevier, vol. 80(1), pages 35-62, September.
  4. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037, Octomber.
  5. Cerchi, Marlene & Havenner, Arthur, 1988. "Cointegration and stock prices : The random walk on wall street revisited," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 333-346.
  6. Clements, Michael P & Hendry, David F, 1996. "Intercept Corrections and Structural Change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 475-94, Sept.-Oct.
  7. de Jong, R.M., 1995. "Laws of Large Numbers for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, vol. 11(02), pages 347-358, February.
  8. Stengos, Thanasis & Panas, E, 1992. "Testing the Efficiency of the Athens Stock Exchange: Some Results from the Banking Sector," Empirical Economics, Springer, vol. 17(2), pages 239-52.
  9. Schoenberg, Ronald, 1997. "Constrained Maximum Likelihood," Computational Economics, Society for Computational Economics, vol. 10(3), pages 251-66, August.
  10. de Jong, Robert M., 1997. "Central Limit Theorems for Dependent Heterogeneous Random Variables," Econometric Theory, Cambridge University Press, vol. 13(03), pages 353-367, June.
  11. Andrews, Donald W. K. & Lee, Inpyo & Ploberger, Werner, 1996. "Optimal changepoint tests for normal linear regression," Journal of Econometrics, Elsevier, vol. 70(1), pages 9-38, January.
  12. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
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