Threshold dynmamics of short-term interest rates: empirical evidence and implications for the term structure
AbstractThis paper studies a nonlinear one-factor term structure model in discrete time. The single factor is the short-term interest rate, which is modeled as a self-exciting threshold autoregressive (SETAR) process. Our specification allows for shifts in the intercept and the variance. The process is stationary but mimics the nearly I(1) dynamics typically encountered with interest rates. In comparison with a linear model, we find empirical evidence in favor of the threshold model for Germany and the US. Based on the estimated short-rate dynamics we derive the implied arbitrage-free term structure of interest rates. Since analytical solutions are not feasible, bond prices are computed by means of Monte Carlo integration. The resulting term structure exhibits properties that are qualitatively similar to those observed in the data and which cannot be captured by the linear Gaussian one-factor model. In particular, our model captures the nonlinear relation between long rates and the short rate found in the data. --
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Bibliographic InfoPaper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 1: Economic Studies with number 2007,02.
Date of creation: 2007
Date of revision:
Non-affine term structure models; SETAR models; Asset pricing;
Other versions of this item:
- Theofanis Archontakis & Wolfgang Lemke, 2008. "Threshold Dynamics of Short-term Interest Rates: Empirical Evidence and Implications for the Term Structure," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 37(1), pages 75-117, 02.
- E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-03-10 (All new papers)
- NEP-ETS-2007-03-10 (Econometric Time Series)
- NEP-MAC-2007-03-10 (Macroeconomics)
- NEP-MON-2007-03-10 (Monetary Economics)
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.:
- M. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2006.
"Learning, structural instability and present value calculations,"
Computing in Economics and Finance 2006
529, Society for Computational Economics.
- Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2007. "Learning, Structural Instability, and Present Value Calculations," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 253-288.
- Pesaran, Mohammad Hashem & Pettenuzzo, Davide & Timmermann, Allan, 2006. "Learning, structural instability and present value calculations," Discussion Paper Series 1: Economic Studies 2006,27, Deutsche Bundesbank, Research Centre.
- Pesaran, M.H. & Pettenuzzo, D. & Timmermann, A., 2006. "Learning, Structural Instability and Present Value Calculations," Cambridge Working Papers in Economics 0602, Faculty of Economics, University of Cambridge.
- Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2006. "Learning, Structural Instability and Present Value Calculations," IEPR Working Papers 06.42, Institute of Economic Policy Research (IEPR).
- M. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2006. "Learning, Structural Instability and Present Value Calculations," CESifo Working Paper Series 1650, CESifo Group Munich.
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- Lanne, M. & Saikkonen, P., 2000. "Threshold Autoregression for Strongly Autocorrelated Time Series," University of Helsinki, Department of Economics 489, Department of Economics.
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