EconPapers    
Economics at your fingertips  
 

Estimating Latent Variables and Jump Diffusion Models Using High-Frequency Data

George J. Jiang and Roel Oomen ()

Journal of Financial Econometrics, 2007, vol. 5, issue 1, 1-30

Abstract: This article proposes a new approach to exploit the information in high-frequency data for the statistical inference of continuous-time affine jump diffusion (AJD) models with latent variables. For this purpose, we construct unbiased estimators of the latent variables and their power functions on the basis of the observed state variables over extended horizons. With the estimates of the latent variables, we propose a generalized method of moments (GMM) procedure for the estimation of AJD models with the distinguishing feature that moments of both observed and latent state variables can be used without resorting to path simulation or discretization of the continuous-time process. Using high frequency return observations of the S&P 500 index, we implement our estimation approach to various continuous-time asset return models with stochastic volatility and random jumps. Copyright 2007, Oxford University Press.

Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (9) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1093/jjfinec/nbl007 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:jfinec:v:5:y:2007:i:1:p:1-30

Ordering information: This journal article can be ordered from
http://www.oup.co.uk/journals

Access Statistics for this article

Journal of Financial Econometrics is currently edited by RenÈ Garcia and Eric Renault

More articles in Journal of Financial Econometrics from Society for Financial Econometrics Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().

 
Page updated 2020-09-15
Handle: RePEc:oup:jfinec:v:5:y:2007:i:1:p:1-30