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RCA models: Joint prediction of mean and volatility

Author

Listed:
  • Liang, Y.
  • Thavaneswaran, A.
  • Ravishanker, N.

Abstract

This paper first describes moment properties for Random Coefficient Autoregressive (RCA) processes and the corresponding squared processes, and then studies joint prediction of the mean and volatility. Recursive estimates based on estimating functions are used to compute joint predictions for volumes of the NASDAQ index.

Suggested Citation

  • Liang, Y. & Thavaneswaran, A. & Ravishanker, N., 2013. "RCA models: Joint prediction of mean and volatility," Statistics & Probability Letters, Elsevier, vol. 83(2), pages 527-533.
    • Handle: RePEc:eee:stapro:v:83:y:2013:i:2:p:527-533
    DOI: 10.1016/j.spl.2012.10.031
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    References listed on IDEAS

    as
    1. A. Thavaneswaran & B. Abraham, 1988. "Estimation For Non‐Linear Time Series Models Using Estimating Equations," Journal of Time Series Analysis, Wiley Blackwell, vol. 9(1), pages 99-108, January.
    2. Thavaneswaran, A. & Appadoo, S.S. & Peiris, S., 2005. "Forecasting volatility," Statistics & Probability Letters, Elsevier, vol. 75(1), pages 1-10, November.
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