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Forecasting Interest Rates - A Comparative Assessment Of Some Second Generation Non-Linear Models

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  • Dilip M. Nachane

    (Indira Gandhi Institute of Development Research)

  • Jose G. Clavel

Abstract

Modelling and forecasting of interest rates has traditionally proceeded in the framework of linear stationary models such as ARMA and VAR, but only with moderate success. We examine here four models which account for several specific features of real world asset prices such as non-stationarity and non-linearity. Our four candidate models are based respectively on wavelet analysis, mixed spectrum analysis, non-linear ARMA models with Fourier coefficients, and the Kalman filter. These models are applied to weekly data on interest rates in India, and their forecasting performance is evaluated vis--vis three GARCH models (GARCH (1,1), GARCH-M (1,1) and EGARCH (1,1)) as well as the random walk model. The Kalman filter model emerges at the top, with wavelet and mixed spectrum models also showing considerable promise.

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Bibliographic Info

Paper provided by East Asian Bureau of Economic Research in its series Finance Working Papers with number 22359.

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Date of creation: Jan 2005
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Handle: RePEc:eab:financ:22359

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Keywords: interest rates; wavelets; mixed spectra; non-linear ARMA; Kalman filter; GARCH; Forecast encompassing.;

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  1. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-78, December.
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  5. Ludlow, Jorge & Enders, Walter, 2000. "Estimating non-linear ARMA models using Fourier coefficients," International Journal of Forecasting, Elsevier, vol. 16(3), pages 333-347.
  6. Guy Melard, 1985. "Examples of the evolutionary spectrum theory," ULB Institutional Repository 2013/13696, ULB -- Universite Libre de Bruxelles.
  7. Rabemananjara, R & Zakoian, J M, 1993. "Threshold Arch Models and Asymmetries in Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 31-49, Jan.-Marc.
  8. Swanson, Norman R & White, Halbert, 1995. "A Model-Selection Approach to Assessing the Information in the Term Structure Using Linear Models and Artificial Neural Networks," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 265-75, July.
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