BIROn - Birkbeck Institutional Research Online

    Estimating and forecasting the yield curve using a Markov switching dynamic Nelson and Siegel model

    Hevia, C. and Gonzalez-Rozada, M. and Sola, Martin and Spagnolo, F. (2015) Estimating and forecasting the yield curve using a Markov switching dynamic Nelson and Siegel model. Journal of Applied Econometrics 30 (6), pp. 987-1009. ISSN 0883-7252.

    Full text not available from this repository.

    Abstract

    We estimate versions of the Nelson–Siegel model of the yield curve of US government bonds using a Markov switching latent variable model that allows for discrete changes in the stochastic process followed by the interest rates. Our modeling approach is motivated by evidence suggesting the existence of breaks in the behavior of the US yield curve that depend, for example, on whether the economy is in a recession or a boom, or on the stance of monetary policy. Our model is parsimonious, relatively easy to estimate and flexible enough to match the changing shapes of the yield curve over time. We also derive the discrete time non-arbitrage restrictions for the Markov switching model. We compare the forecasting performance of these models with that of the standard dynamic Nelson and Siegel model and an extension that allows the decay rate parameter to be time varying. We show that some parametrizations of our model with regime shifts outperform the single-regime Nelson and Siegel model and other standard empirical models of the yield curve.

    Metadata

    Item Type: Article
    School: School of Business, Economics & Informatics > Economics, Mathematics and Statistics
    Research Centres and Institutes: Applied Macroeconomics, Birkbeck Centre for
    Depositing User: Administrator
    Date Deposited: 19 Nov 2014 19:52
    Last Modified: 07 Dec 2016 14:53
    URI: https://eprints.bbk.ac.uk/id/eprint/11035

    Statistics

    Downloads
    Activity Overview
    0Downloads
    299Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item