Dynamics of Interest Rate Curve by Functional Auto-regression
The paper applies methods of functional data analysis â€“ functional auto-regression, principal components and canonical correlations â€“ 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
|Date of creation:||11 Aug 2004|
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- Andrew Ang & Monika Piazzesi, 2001.
"A No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables,"
NBER Working Papers
8363, National Bureau of Economic Research, Inc.
- Ang, Andrew & Piazzesi, Monika, 2003. "A no-arbitrage vector autoregression of term structure dynamics with macroeconomic and latent variables," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 745-787, May.
- Heath, David & Jarrow, Robert & Morton, Andrew, 1990. "Bond Pricing and the Term Structure of Interest Rates: A Discrete Time Approximation," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(04), pages 419-440, December.
- Ho, Thomas S Y & Lee, Sang-bin, 1986. " Term Structure Movements and Pricing Interest Rate Contingent Claims," Journal of Finance, American Finance Association, vol. 41(5), pages 1011-29, December.
- Heath, David & Jarrow, Robert & Morton, Andrew, 1992. "Bond Pricing and the Term Structure of Interest Rates: A New Methodology for Contingent Claims Valuation," Econometrica, Econometric Society, vol. 60(1), pages 77-105, January.
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