Estimation for the change point of the volatility in a stochastic differential equation

Stefano Iacus () and Nakahiro Yoshida
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Nakahiro Yoshida: Graduate School of Mathematical Sciences, Tokyo University, Tokyo

No unimi-1084, UNIMI - Research Papers in Economics, Business, and Statistics from Universitá degli Studi di Milano

Abstract: We consider a multidimensional Ito process Y=(Y_t), t in [0,T], with some unknown drift coefficient process b_t and volatility coefficient sigma(X_t,theta) with covariate process X=(X_t), t in[0,T], the function sigma(x,theta) being known up to theta in Theta. For this model we consider a change point problem for the parameter theta in the volatility component. The change is supposed to occur at some point t* in (0,T). Given discrete time observations from the process (X,Y), we propose quasi-maximum likelihood estimation of the change point. We present the rate of convergence of the change point estimator and the limit thereoms of aymptotically mixed type.

Keywords: It\^o processes; discrete time observations; change point estimation; volatility (search for similar items in EconPapers)
Date: 2009-06-18
Note: oai:cdlib1:unimi-1084
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Estimation for the change point of volatility in a stochastic differential equation (2012)
Working Paper: Estimation for the change point of the volatility in a stochastic differential equation (2009)
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