Out-of-Sample Forecasts and Nonlinear Model Selection with an Example of the Term Structure of Interest Rates
AbstractIt is well known that goodness-of-fit measures lead to overfitting. We compare the small-sample properties of linear and several nonlinear models using a Monte Carlo study. A large number of linear series are generated and conventional methods of fitting nonlinear models are applied to each. The best linear and nonlinear models are compared using in-sample and out-of-sample criteria. Out-of-sample forecasts are shown to be superior for selecting the proper specification. The experiment is repeated using a nonlinear model and the in-sample fit and forecasts of the various models are compared. An example is provided using the term structure of interest rates.
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Bibliographic InfoArticle provided by Southern Economic Association in its journal Southern Economic Journal.
Volume (Year): 69 (2003)
Issue (Month): 3 (January)
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- Andros Gregoriou & Niloy Bose & M. Emranul Haque, 2010. "Modeling the non-linear behaviour of option price deviations from the Black Scholes model," Journal of Economic Studies, Emerald Group Publishing, vol. 37(1), pages 26-35, January.
- Qin, Ting & Enders, Walter, 2008. "In-sample and out-of-sample properties of linear and nonlinear Taylor rules," Journal of Macroeconomics, Elsevier, vol. 30(1), pages 428-443, March.
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