The paper applies methods of functional data analysis – functional auto-regression, principal components and canonical correlations – to the study of the dynamics of interest rate curve. In addition, it introduces a novel statistical tool based on the singular value decomposition of the functional cross-covariance operator. This tool is better suited for prediction purposes as opposed to either principal components or canonical correlations. Based on this tool, the paper provides a consistent method for estimating the functional auto-regression of interest rate curve. The theory is applied to estimating dynamics of Eurodollar futures rates. The results suggest that future movements of interest rates are predictable only at very short and very long horizons
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.: