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Parameter Estimation in Mean Reversion Processes with Deterministic Long-Term Trend

Author

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  • Freddy H. Marín Sánchez
  • Verónica M. Gallego

Abstract

This paper describes a procedure based on maximum likelihood technique in two phases for estimating the parameters in mean reversion processes when the long-term trend is defined by a continued deterministic function. Closed formulas for the estimators that depend on observations of discrete paths and an estimation of the expected value of the process are obtained in the first phase. In the second phase, a reestimation scheme is proposed when a priori knowledge exists of the long-term trend. Some experimental results using simulated data sets are graphically illustrated.

Suggested Citation

  • Freddy H. Marín Sánchez & Verónica M. Gallego, 2016. "Parameter Estimation in Mean Reversion Processes with Deterministic Long-Term Trend," Journal of Probability and Statistics, Hindawi, vol. 2016, pages 1-8, August.
    • Handle: RePEc:hin:jnljps:5191583
    DOI: 10.1155/2016/5191583
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    Cited by:

    1. Babacar Seck & Robert J. Elliott, 2021. "Regime Switching Entropic Risk Measures on Crude Oil Pricing," Papers 2112.13041, arXiv.org.

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