Parametric Estimation and the CIR Model

Authors

  • Eugenio Saavedra Universidad de Santiago.

DOI:

https://doi.org/10.4067/S0716-09172016000200005

Keywords:

estimating function, quasi—likelihood, stochastic differential equation, función estimativa, casi-parentesco, ecuación diferencial estocástica.

Abstract

We study parametric estimation in the Cox-Ingersoll-Ross model and establish the stochastic differential equations for the parameters involved in it.

Author Biography

Eugenio Saavedra, Universidad de Santiago.

Departamento de Matematica y Ciencias de la Computación.

References

[1] Brown, R. H., Schaefer, S. M., The Term Structure of Real Interest Rates and the Cox, Ingersoll and Ross Model, J. of Financial Economics 35, pp. 3—42, (1994).

[2] Cox, J. S., Ingersoll, J. E., Ross, S. A., A theory of term structure of interest rates, Econometrica. 53, pp. 363—384, (1985).

[3] Feigin, P., Maximum likelihood estimation for continuous-time stochastic processes, J. Appl. Probab. 8, pp. 712—736, (1976).

[4] Heyde, C., Quasi—Likelihood and its Aplications, Springer, New York, (1997).

[5] Kloeden, P., Platen, E., Numerical Solution of Stochastic Differential Equations, Second Edition, Springer, Berlin, (1995).

[6] Kloeden, P., Platen, E., Shurz, H., Sorensen, M., On effects of discretization on estimators of drift parameters for diffusion processes, J. Appl. Probab. 33, pp. 1061—1076, (1996).

[7] Protter, P., Stochastic Integration and Differential Equations, Springer, New York, (1990).

Published

2017-03-23

How to Cite

[1]
E. Saavedra, “Parametric Estimation and the CIR Model”, Proyecciones (Antofagasta, On line), vol. 35, no. 2, pp. 197-211, Mar. 2017.

Issue

Section

Artículos