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Ergodicity and parameter estimation for some affine models
Introduction
Exponential ergodicity of an affine two-factor model based on the alpha-root process
The affine two factor model based on the alpha-root process
Affine representation of (Y,X)
Transition densities of the alpha-root process Y
A Foster-Lyapunov function for (Y,X)
Exponential ergodicity of (Y,X)
Moments and ergodicity of the jump-diffusion CIR process and parameter estimation for the drift parameters based on discrete time observations
The jump-diffusion CIR process
Affine representation of the JCIR process
Transition densities of the JCIR process
Moments of the JCIR process
Bessel distribution
Moment characterization of the JCIR process
First and second moment of the JCIR process
Ergodicity of the JCIR process
Exponential ergodicity of the JCIR process
Convergence of moments for the JCIR process
Parameter estimation of the jump-diffusion CIR process
Consistency of the LSE
Asymptotic behavior of least squares estimator
Least square estimator of the drift parameters (a,b)
Appendix
Two-dimensional affine processes
Markov chains on uncountable state spaces
Strong law of large numbers and central limit theorem for discrete time square-integrable martingales
Bibliography
Dissertation
Ergodicity and parameter estimation for some affine models / vorgelegt von: Jonas Kremer
Entstehung
Wuppertal
August 2018
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