Modeling and forecasting short‐term interest rates: The benefits of smooth regimes, macroeconomic variables, and bagging
AbstractIn this paper we propose a smooth transition tree model for both the conditional mean and variance of the short-term interest rate process. The estimation of such models is addressed and the asymptotic properties of the quasi-maximum likelihood estimator are derived. Model specification is also discussed. When the model is applied to the US short-term interest rate we find (1) leading indicators for inflation and real activity are the most relevant predictors in characterizing the multiple regimesâ structure; (2) the optimal model has three limiting regimes. Moreover, we provide empirical evidence of the power of the model in forecasting the first two conditional moments when it is used in connection with bootstrap aggregation (bagging).
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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.
Volume (Year): 26 (2011)
Issue (Month): 6 (09)
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- Francesco Audrino & Marcelo Cunha Medeiros, 2010. "Modeling and Forecasting Short-term Interest Rates: The Benefits of Smooth Regimes, Macroeconomic Variables, and Bagging," Textos para discussÃ£o 570, Department of Economics PUC-Rio (Brazil).
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- Francesco Audrino & Enrico De Giorgi, .
"Beta Regimes for the Yield Curve,"
IEW - Working Papers
244, Institute for Empirical Research in Economics - University of Zurich.
- van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000.
"Smooth transition autoregressive models - A survey of recent developments,"
Econometric Institute Research Papers
EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
- van Dijk, Dick & Teräsvirta, Timo & Franses, Philip Hans, 2000. "Smooth Transition Autoregressive Models - A Survey of Recent Developments," Working Paper Series in Economics and Finance 380, Stockholm School of Economics, revised 17 Jan 2001.
- 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.
- 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.
- Medeiros, Marcelo C. & Veiga, Alvaro, 2009. "Modeling Multiple Regimes In Financial Volatility With A Flexible Coefficient Garch(1,1) Model," Econometric Theory, Cambridge University Press, vol. 25(01), pages 117-161, February.
- Asbjørn T. Hansen & Rolf Poulsen, 2000. "A simple regime switching term structure model," Finance and Stochastics, Springer, vol. 4(4), pages 409-429.
- Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
- Shiqing Ling & Michael McAleer, 2001.
"Asymptotic Theory for a Vector ARMA-GARCH Model,"
ISER Discussion Paper
0549, Institute of Social and Economic Research, Osaka University.
- Andrew Ang & Sen Dong, 2005.
"No-Arbitrage Taylor Rules,"
2005 Meeting Papers
22, Society for Economic Dynamics.
- Inoue, Atsushi & Kilian, Lutz, 2008. "How Useful Is Bagging in Forecasting Economic Time Series? A Case Study of U.S. Consumer Price Inflation," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 511-522, June.
- Audrino, Francesco, 2006. "Tree-Structured Multiple Regimes in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 338-353, July.
- Eric Hillebrand & Marcelo Cunha Medeiros, 2007. "Forecasting realized volatility models:the benefits of bagging and nonlinear specifications," Textos para discussÃ£o 547, Department of Economics PUC-Rio (Brazil).
- Diebold, Francis X. & Rudebusch, Glenn D. & Borag[caron]an Aruoba, S., 2006.
"The macroeconomy and the yield curve: a dynamic latent factor approach,"
Journal of Econometrics,
Elsevier, vol. 131(1-2), pages 309-338.
- Tom Doan, . "RATS programs to replicate Diebold,Rudebusch,Aruoba 2006 factor model," Statistical Software Components RTZ00047, Boston College Department of Economics.
- Francis X. Diebold & Glenn D. Rudebusch & S. Boragan Aruoba, 2004. "The Macroeconomy and the Yield Curve: A Dynamic Latent Factor Approach," NBER Working Papers 10616, National Bureau of Economic Research, Inc.
- da Rosa, Joel Correa & Veiga, Alvaro & Medeiros, Marcelo C., 2008. "Tree-structured smooth transition regression models," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2469-2488, January.
- Ravi Bansal & Hao Zhou, 2001.
"Term structure of interest rates with regime shifts,"
Finance and Economics Discussion Series
2001-46, Board of Governors of the Federal Reserve System (U.S.).
- Ravi Bansal & Hao Zhou, 2002. "Term Structure of Interest Rates with Regime Shifts," Journal of Finance, American Finance Association, vol. 57(5), pages 1997-2043, October.
- White,Halbert, 1994.
"Estimation, Inference and Specification Analysis,"
Cambridge University Press, number 9780521252805, April.
- Medeiros, Marcelo C. & Teräsvirta, Timo & Rech, Gianluigi, 2002.
"Building neural network models for time series: A statistical approach,"
Working Paper Series in Economics and Finance
508, Stockholm School of Economics.
- Timo Teräsvirta & Marcelo C. Medeiros & Gianluigi Rech, 2006. "Building neural network models for time series: a statistical approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 49-75.
- Marcelo C. Medeiros & Timo Terasvirta & Gianluigi Rech, 2002. "Building Neural Network Models for Time Series: A Statistical Approach," Textos para discussÃ£o 461, Department of Economics PUC-Rio (Brazil).
- Diebold, Francis X & Mariano, Roberto S, 1995.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 13(3), pages 253-63, July.
- Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Tom Doan, . "DMARIANO: RATS procedure to compute Diebold-Mariano Forecast Comparison Test," Statistical Software Components RTS00055, Boston College Department of Economics.
- Ravi Bansal & George Tauchen & Hao Zhou, 2003.
"Regime-shifts, risk premiums in the term structure, and the business cycle,"
Finance and Economics Discussion Series
2003-21, Board of Governors of the Federal Reserve System (U.S.).
- Ravi Bansal & George Tauchen & Hao Zhou, 2004. "Regime Shifts, Risk Premiums in the Term Structure, and the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 396-409, October.
- Wooldridge, Jeffrey M., 1990. "A Unified Approach to Robust, Regression-Based Specification Tests," Econometric Theory, Cambridge University Press, vol. 6(01), pages 17-43, March.
- Huiyu Huang & Tae-Hwy Lee, 2013. "Forecasting Value-at-Risk Using High-Frequency Information," Econometrics, MDPI, Open Access Journal, vol. 1(1), pages 127-140, June.
- Erik Hillebrand & Tae-Hwy Lee & Marcelo Cunha Medeiros, 2012.
"Let´s do it again: bagging equity premium predictors,"
Textos para discussÃ£o
604, Department of Economics PUC-Rio (Brazil).
- Eric Hillebrand & Tae-Hwy Lee & Marcelo C. Medeiros, 2012. "Let's Do It Again: Bagging Equity Premium Predictors," CREATES Research Papers 2012-41, School of Economics and Management, University of Aarhus.
- Francesco Audrino, 2012. "What Drives Short Rate Dynamics? A Functional Gradient Descent Approach," Computational Economics, Society for Computational Economics, vol. 39(3), pages 315-335, March.
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