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Journal article

Accurate short-term yield curve forecasting using functional gradient descent

  • Audrino, Francesco Istituto di finanza (IFin), Facoltà di scienze economiche, Università della Svizzera italiana, Svizzera
  • Trojani, Fabio Istituto di finanza (IFin), Facoltà di scienze economiche, Università della Svizzera italiana, Svizzera
    2007
Published in:
  • Journal of financial econometrics. - Oxford Publishing Limited. - 2007, vol. 5, no. 4, p. 591–623
Conditional mean and variance estimation
filtered historical simulation
functional gradient descent
term structure
multivariate CCC-GARCH models
English We propose a multivariate nonparametric technique for generating reliable shortterm 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 non- linearities 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.
Language
  • English
Classification
Economics
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Identifiers
  • RERO DOC 11764
  • ARK ark:/12658/srd1318086
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https://n2t.net/ark:/12658/srd1318086
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