Forecasting US bond yields at weekly frequency
AbstractForecasting models for bond yields often use macro data to improve their properties. Unfortunately, macro data are not available at frequencies higher than monthly. In order to mitigate this problem, we propose a nonlinear VEC model with conditional heteroskedasticity (NECH) and find that such model has superior in-sample performance than models which fail to encompass nonlinearities and/or GARCH-type effects. Out-of-sample forecasts by our model are marginally superior to competing models; however, the data points we used for evaluating forecasts refer to a period of relative tranquillity on the financial markets, whereas we argue that our model should display superior performance under "unusual" circumstances.
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Bibliographic InfoPaper provided by Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali in its series Working Papers with number 261.
Date of creation: May 2006
Date of revision:
conditional heteroskedasticity; forecasting; interest rates; nonlinear cointegration;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-05-27 (All new papers)
- NEP-ECM-2006-05-27 (Econometrics)
- NEP-ETS-2006-05-27 (Econometric Time Series)
- NEP-FMK-2006-05-27 (Financial Markets)
- NEP-FOR-2006-05-27 (Forecasting)
- NEP-MAC-2006-05-27 (Macroeconomics)
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