est.CKLS.GMM: Generalized method of moments estimator for the CKLS model

In alejandralopezperez/estsde: Parametric Estimation of SDE

Generalized method of moments estimator for the CKLS model

Description

Parametric estimation for the CKLS model using the Generalized Method of Moments. The parametric form of the CKLS model used here is given by

dX_t = (α - κ X_t)dt + σ X_t^γ dW_t.

Usage

est.CKLS.GMM(X, Delta = deltat(X), par = NULL, maxiter = 25)

Arguments

X	a numeric vector, the sample path of the SDE.
Delta	a single numeric, the time step between two consecutive observations.
par	a numeric vector with dimension four indicating initial values of the parameters. Defaults to NULL, fits a linear model using generalized least squares with AR1 correlation and a power variance heteroscedasticity structure.
maxiter	an integer, the maximum number of iterations.

Value

A list containing a matrix with the estimated coefficients and the associated standard errors.

References

Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica, pages 1029–1054.

Chan, K. C., Karolyi, G. A., Longstaff, F. A., and Sanders, A. B. (1992). An empirical comparison of alternative models of the short-term interest rate. The journal of finance, 47(3):1209–1227.

Examples

x <- rCKLS(360, 1/12, 0.09, 0.08, 0.9, 1.2, 1.5)
est.CKLS.GMM(x)

alejandralopezperez/estsde documentation built on Sept. 4, 2022, 4:48 a.m.