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Yule-Walker Estimation for the Moving-Average Model

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  • Chrysoula Dimitriou-Fakalou

Abstract

The standard Yule-Walker equations, as they are known for an autoregression, are generalized to involve the moments of a moving-average process indexed on any number of dimensions. Once observations become available, new moments estimators are set to imitate the theoretical equations. These estimators are not only consistent but also asymptotically normal for any number of indexes. Their variance matrix resembles a standard result from maximum Gaussian likelihood estimation. A simulation study is added to conclude on their efficiency.

Suggested Citation

  • Chrysoula Dimitriou-Fakalou, 2011. "Yule-Walker Estimation for the Moving-Average Model," International Journal of Stochastic Analysis, Hindawi, vol. 2011, pages 1-20, August.
    • Handle: RePEc:hin:jnijsa:151823
    DOI: 10.1155/2011/151823
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    Cited by:

    1. Zhang, Lihong & Wang, Jun & Wang, Bin, 2020. "Energy market prediction with novel long short-term memory network: Case study of energy futures index volatility," Energy, Elsevier, vol. 211(C).

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