Transition and measurement noise correlation in affine and Gaussian models: the case of oil prices

Carla Gomes Costa De Souza and Fernando Antonio Aiube ()

International Journal of Financial Markets and Derivatives, 2021, vol. 8, issue 1, 50-64

Abstract: This paper proposes a new approach for the estimation of affine and Gaussian factor models with the Kalman filter method. It considers the correlation between the innovations of transition and measurement equations. We use crude oil prices in the analysis. When applying this correlation approach in two- and three-factor models, we obtain improvements of error measures between estimated and observed future prices with inexpensive estimation procedures.

Keywords: commodity factor models; Kalman filter estimation; future prices; oil prices. (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=113858 (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:ids:ijfmkd:v:8:y:2021:i:1:p:50-64

Access Statistics for this article

More articles in International Journal of Financial Markets and Derivatives from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().