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Journal of Financial Econometrics Advance Access published online on August 8, 2007
Journal of Financial Econometrics, doi:10.1093/jjfinec/nbm011
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Copyright © The Author 2007. Published by Oxford University Press.

Accurate Short-Term Yield Curve Forecasting using Functional Gradient Descent

Francesco Audrino
     University of Lugano, Switzerland

Fabio Trojani
     University of St. Gallen, Switzerland

Address correspondence to Francesco Audrino, USI, Institute of Finance, Via Buffi 13, CH-6900 Lugano, Switzerland, or e-mail: francesco.audrino{at}lu.unisi.ch


  Abstract

We 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 RiskMetricsTM approach.

KEYWORDS: conditional mean and variance estimation, filtered historical simulation, functional gradient descent, multivariate CCC-GARCH models, term structure

We are grateful to the editor (George Tauchen) and two anonymous referees for their very valuable comments and suggestions. Financial support by the Swiss National Science Foundation (grants 100012-103781, 100012-105745 and NCCR FINRISK) and by the Foundation for Research and Development of the University of Lugano is gratefully acknowledged.

Received April 10, 2007; revised May 11, 2007; accepted June 20, 2007


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