Parameter Estimation in Mean Reversion Processes with Deterministic Long-Term Trend
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Fecha
2016-01-01
Autores
Marin Sanchez, Freddy H.
Gallego, Veronica M.
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Editor
Hindawi Publishing Corporation
Resumen
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.