Accurate Short-Term Yield Curve Forecasting using Functional Gradient Descent
AbstractWe propose a multivariate nonparametric technique for generating reliable short-term historical yield curve scenarios and confidence intervals. The approach is based on a Functional Gradient Descent (FGD) estimation of the conditional mean vector and covariance matrix of a multivariate interest rate series. It is computationally feasible in large dimensions and it can account for nonlinearities in the dependence of interest rates at all available maturities. Based on FGD we apply filtered historical simulation to compute reliable out-of-sample yield curve scenarios and confidence intervals. We back-test our methodology on daily USD bond data for forecasting horizons from 1 to 10 days. Based on several statistical performance measures we find significant evidence of a higher predictive power of our method when compared to scenarios generating techniques based on (i) factor analysis, (ii) a multivariate CCC-GARCH model, or (iii) an exponential smoothing covariances estimator as in the RiskMetrics-super-TM approach. Copyright , Oxford University Press.
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Bibliographic InfoArticle provided by Society for Financial Econometrics in its journal Journal of Financial Econometrics.
Volume (Year): 5 (2007)
Issue (Month): 4 (Fall)
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- Francesco Audrino & Fabio Trojani, 2007. "Accurate Short-Term Yield Curve Forecasting using Functional Gradient Descent," University of St. Gallen Department of Economics working paper series 2007 2007-24, Department of Economics, University of St. Gallen.
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- Buhlmann P. & Yu B., 2003. "Boosting With the L2 Loss: Regression and Classification," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 324-339, January.
- 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.
- Gourieroux,Christian, 2000. "Econometrics of Qualitative Dependent Variables," Cambridge Books, Cambridge University Press, number 9780521331494, October.
- Mancini, Loriano & Ronchetti, Elvezio & Trojani, Fabio, 2005.
"Optimal Conditionally Unbiased Bounded-Influence Inference in Dynamic Location and Scale Models,"
Journal of the American Statistical Association,
American Statistical Association, vol. 100, pages 628-641, June.
- Loriano Mancini & Elvezio Ronchetti & Fabio Trojani, 2005. "Optimal Conditionally Unbiased Bounded-Influence Inference in Dynamic Location and Scale Models," University of St. Gallen Department of Economics working paper series 2005 2005-01, Department of Economics, University of St. Gallen.
- Loriano Mancini & Elvezio Ronchetti & Fabio Trojani, 2004. "Optimal Conditionally Unbiased Bounded-Influence Inference in Dynamic Location and Scale Models," Research Papers by the Institute of Economics and Econometrics, Geneva School of Economics and Management, University of Geneva 2004.04, Institut d'Economie et Econométrie, Université de Genève.
- Audrino, Francesco & Barone-Adesi, Giovanni, 2005. "Functional gradient descent for financial time series with an application to the measurement of market risk," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 959-977, April.
- Kiefer, Nicholas M, 1988. "Economic Duration Data and Hazard Functions," Journal of Economic Literature, American Economic Association, vol. 26(2), pages 646-79, June.
- Francesco Audrino & Giovanni Barone-Adesi, 2005. "A multivariate FGD technique to improve VaR computation in equity markets," Computational Management Science, Springer, vol. 2(2), pages 87-106, 03.
- Tse, Y. K., 2000.
"A test for constant correlations in a multivariate GARCH model,"
Journal of Econometrics,
Elsevier, vol. 98(1), pages 107-127, September.
- Tom Doan, . "TSECCTEST: RATS procedure to perform Tse test for constant correlation in MV-GARCH model," Statistical Software Components RTS00214, Boston College Department of Economics.
- Tom Doan, . "RATS programs to replicate Tse's constant correlation GARCH test results," Statistical Software Components RTZ00161, Boston College Department of Economics.
- Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
- Gourieroux,Christian, 2000. "Econometrics of Qualitative Dependent Variables," Cambridge Books, Cambridge University Press, number 9780521589857, October.
- Farshid Jamshidian & Yu Zhu, 1996. "Scenario Simulation: Theory and methodology (*)," Finance and Stochastics, Springer, vol. 1(1), pages 43-67.
- Francis X. Diebold & Canlin Li, 2003.
"Forecasting the Term Structure of Government Bond Yields,"
NBER Working Papers
10048, National Bureau of Economic Research, Inc.
- Diebold, Francis X. & Li, Canlin, 2006. "Forecasting the term structure of government bond yields," Journal of Econometrics, Elsevier, vol. 130(2), pages 337-364, February.
- Francis X. Diebold & Canlin Li, 2002. "Forecasting the Term Structure of Government Bond Yields," Center for Financial Institutions Working Papers 02-34, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Diebold, Francis X. & Li, Canlin, 2003. "Forecasting the term structure of government bond yields," CFS Working Paper Series 2004/09, Center for Financial Studies (CFS).
- Gallant, A.R. & Tauchen, G., 1988.
"Seminonparametric Estimation Of Conditionally Constrained Heterogeneous Processes: Asset Pricing Applications,"
88-59, Chicago - Graduate School of Business.
- Gallant, Ronald & Tauchen, George, 1989. "Seminonparametric Estimation of Conditionally Constrained Heterogeneous Processes: Asset Pricing Applications," Econometrica, Econometric Society, vol. 57(5), pages 1091-1120, September.
- 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.
- Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
- Teresa Buchen & Klaus Wohlrabe, 2013. "Assessing the Macroeconomic Forecasting Performance of Boosting - Evidence for the United States, the Euro Area, and Germany," CESifo Working Paper Series 4148, CESifo Group Munich.
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