Comparing forecasting ability of parametric and non-parametric methods: an application with Canadian monthly interest rates

The primary objective of this article is to compare the forecasting ability of some recent parametric and non-parametric estimation methods by using monthly Canadian interest rate data between 1964:1–1999:1. The two-factor continuous time term structure model of Brennan and Schwartz was estimated where the first factor represents the short rate and the second factor the long rate using the continuous time estimation procedures developed by Bergstrom. The interest rates using the multivariate GARCH model developed by Engle and Kroner, and two non-parametric estimation methods namely, non-parametric kernel smoothing and the artificial neural networks was modelled. For the short-term rates, it has been found that, the Bergstrom's method and the artificial neural networks model have marginally better forecasting performance than that of the linear benchmark. For the long-term rates, none of the methods produced better forecasting precision than that of the benchmark.

[1]  R. C. Merton,et al.  Theory of Rational Option Pricing , 2015, World Scientific Reference on Contingent Claims Analysis in Corporate Finance.

[2]  Chris Brooks.  Predicting stock index volatility: can market volume help? , 1998 .

[3]  F. Diebold,et al.  Comparing Predictive Accuracy , 1994, Business Cycles.

[4]  Daniel B. Nelson.  ARCH models as diffusion approximations , 1990 .

[5]  R. Lippmann,et al.  An introduction to computing with neural nets , 1987, IEEE ASSP Magazine.

[6]  Halbert White,et al.  Artificial Neural Networks: Approximation and Learning Theory , 1992 .

[7]  K. Nowman.  Continuous-time short term interest rate models , 1998 .

[8]  Campbell R. Harvey,et al.  An Empirical Comparison of Alternative Models of the Short-Term Interest Rate , 1992 .

[9]  C. Sims,et al.  Estimation of continuous-time models in finance , 1994 .

[10]  Eduardo S. Schwartz,et al.  A continuous time approach to the pricing of bonds , 1979 .

[11]  A. Ullah,et al.  Nonparametric Econometrics , 1999 .

[12]  K. Nowman,et al.  Gaussian Estimation of Single‐Factor Continuous Time Models of The Term Structure of Interest Rates , 1997 .

[13]  A. Bergstrom.  Continuous Time Econometric Modelling. , 1992 .

[14]  Marcus J. Chambers.  Forecasting discrete stock and flow data generated by a second order continuous time system , 1991 .

[15]  Eduardo S. Schwartz,et al.  An Equilibrium Model of Bond Pricing and a Test of Market Efficiency , 1982, Journal of Financial and Quantitative Analysis.

[16]  T. Andersen.  THE ECONOMETRICS OF FINANCIAL MARKETS , 1998, Econometric Theory.

[17]  A. Bergstrom.  CONTINUOUS TIME STOCHASTIC MODELS AND ISSUES OF AGGREGATION OVER TIME , 1984 .

[18]  Empirical tests of short-term interest rate models: a nonparametric approach , 1998 .

[19]  A. Bergstrom.  Nonrecursive models as discrete approximation to systems of stochastic di?erential equations , 1966 .

[20]  K. Nowman,et al.  Forecasting U.K. and U.S. interest rates using continuous time term structure models , 1998 .

[21]  A. Ullah,et al.  Nonparametric Econometrics: Semiparametric and Nonparametric Estimation of Simultaneous Equation Models , 1999 .

[22]  T. Bollerslev,et al.  Generalized autoregressive conditional heteroskedasticity , 1986 .

[23]  Ramazan Gençay,et al.  Linear, non-linear and essential foreign exchange rate prediction with simple technical trading rules , 1999 .

[24]  L. Hansen,et al.  Back to the Future: Generating Moment Implications for Continuous-Time Markov Processes , 1993 .

[25]  R. Engle.  Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation , 1982 .

[26]  A. Bergstrom.  Gaussian Estimation of Structural Parameters in Higher Order Continuous Time Dynamic Models , 1983 .

[27]  P. Robinson.  NONPARAMETRIC ESTIMATORS FOR TIME SERIES , 1983 .

[28]  Philip D. Wasserman,et al.  Neural computing - theory and practice , 1989 .

[29]  James M. Nason,et al.  Nonparametric exchange rate prediction , 1990 .

[30]  A. Yatchew,et al.  Nonparametric Regression Techniques in Economics , 1998 .

[31]  Gaussian Estimation and Forecasting of Multi-Factor Term Structure Models with an Application to Japan and the United Kingdom , 2001 .

[32]  Further evidence on the forecasting performance of two factor continuous time interest rate models in international and Asia-Pacific financial markets , 2001 .

[33]  Yoshua Bengio,et al.  Pricing and Hedging Derivative Securities with Neural Networks and a Homogeneity Hint , 2000 .

[34]  Forecasting with the almost ideal demand system: evidence from some alternative dynamic specifications , 1997 .

[35]  R. Engle,et al.  Multivariate Simultaneous Generalized ARCH , 1995, Econometric Theory.

[36]  Wolfgang Härdle,et al.  APPLIED NONPARAMETRIC METHODS , 1992 .