Estimation of semiparametric locally stationary diffusion models

Bonsoo Koo, Oliver Linton

Research output: Contribution to journalArticleResearchpeer-review

17 Citations (Scopus)

Abstract

This paper proposes a class of locally stationary diffusion processes. The model has a time varying but locally linear drift and a volatility coefficient that is allowed to vary over time and space. The model is semiparametric because we allow these functions to be unknown and the innovation process is parametrically specified, indeed completely known. We propose estimators of all the unknown quantities based on long span data. Our estimation method makes use of the property of local stationarity. We establish asymptotic theory for the proposed estimators as the time span increases, so we do not rely on infill asymptotics. We apply this method to interest rate data to illustrate the validity of our model. Finally, we present a simulation study to provide the finite-sample performance of the proposed estimators.
Original languageEnglish
Pages (from-to)210 - 233
Number of pages24
JournalJournal of Econometrics
Volume170
Issue number1
DOIs
Publication statusPublished - 2012

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