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Maximum Likelihood Estimation of ARMA Model with Error Processes for Replicated Observations

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Author Info

  • Wing-Keung Wong

    ()
    (National University of Singapore)

  • Robert B. Miller

    (University of Wisconsin-Madison)

  • Keshab Shrestha

    (Concordia University)

Abstract

In this paper we analyse the repeated time series model where the fundamental component follows a ARMA process. In the model, the error variance as well as the number of repetition are allowed to change over time. It is shown that the model is identified. The maximum likelihood estimator is derived using the Kalman filter technique. The model considered in this paper can be considered as extension of the models considered by Anderson (1978), Azzalini (1981) and Wong and Miller (1990)

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File URL: http://www.fas.nus.edu.sg/ecs/pub/wp/wp0217.pdf
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Bibliographic Info

Paper provided by National University of Singapore, Department of Economics in its series Departmental Working Papers with number wp0217.

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Length: 19 pages
Date of creation: 2002
Date of revision:
Handle: RePEc:nus:nusewp:wp0217

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Related research

Keywords: ARMA model; Kalman filter; maximum likelihood estimation;

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References

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  1. Wing-Keung Wong & Guorui Bian, 2004. "Estimating Parameters in Autoregressive Models with Asymmetric Innovations," Departmental Working Papers wp0408, National University of Singapore, Department of Economics.
  2. Wong, Wing-Keung & Li, Chi-Kwong, 1999. "A note on convex stochastic dominance," Economics Letters, Elsevier, vol. 62(3), pages 293-300, March.
  3. Meher Manzur & Wing-Keung Wong & Inn-Chau Chee, 1999. "Measuring international competitiveness: experience from East Asia," Applied Economics, Taylor & Francis Journals, vol. 31(11), pages 1383-1391.
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Cited by:
  1. Wing-keung Wong & Raymond Chan, 2004. "On the estimation of cost of capital and its reliability," Quantitative Finance, Taylor & Francis Journals, vol. 4(3), pages 365-372.
  2. Wing-Keung Wong & Boon-Kiat Chew & Douglas Sikorski, 2002. "Can the Forecasts Generated from E/P Ratio and Bond Yield be Used to Beat Stock Markets?," Departmental Working Papers wp0201, National University of Singapore, Department of Economics.

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