Artículos de revistas
Forecasting The Term Structure Of Interest Rates Using Integrated Nested Laplace Approximations
Registro en:
Journal Of Forecasting. John Wiley And Sons Ltd, v. 33, n. 3, p. 214 - 230, 2014.
2776693
10.1002/for.2288
2-s2.0-84897012994
Autor
Laurini M.P.
Hotta L.K.
Institución
Resumen
This article discusses the use of Bayesian methods for inference and forecasting in dynamic term structure models through integrated nested Laplace approximations (INLA). This method of analytical approximation allows accurate inferences for latent factors, parameters and forecasts in dynamic models with reduced computational cost. In the estimation of dynamic term structure models it also avoids some simplifications in the inference procedures, such as the inefficient two-step ordinary least squares (OLS) estimation. The results obtained in the estimation of the dynamic Nelson-Siegel model indicate that this method performs more accurate out-of-sample forecasts compared to the methods of two-stage estimation by OLS and also Bayesian estimation methods using Markov chain Monte Carlo (MCMC). These analytical approaches also allow efficient calculation of measures of model selection such as generalized cross-validation and marginal likelihood, which may be computationally prohibitive in MCMC estimations. Copyright © 2014 John Wiley & Sons, Ltd. Copyright © 2014 John Wiley & Sons, Ltd. 33 3 214 230 Bauwens, L., Lubrano, M., Richard, J.-F., (1999) Bayesian Inference in Dynamic Econometric Models, , Cambridge University Press: Cambridge, UK Diebold, F.X., Li, C., Forecasting the term structure of government bond yields (2006) Journal of Econometrics, 130, pp. 337-364 Diebold, F.X., Rudebusch, G.D., Aruoba, S.B., The macroeconomy and the yield curve: A dynamic latent factor approach (2006) Journal of Econometrics, 131, pp. 309-338 Duffie, D., Kan, R., A yield-factor model of interest rates (1996) Mathematical Finance, 6, pp. 379-406 Fama, E., Bliss, R.R., The information in long-maturity forward rates (1987) American Economic Review, 77, pp. 680-691 Geweke, J., (2010) Complete and Incomplete Econometric Models, , Princeton University Press: Princeton, NJ Geweke, J., Amisano, G., Comparing and evaluating Bayesian predictive distributions of asset returns (2010) International Journal of Forecasting, 26 (2), pp. 216-230 Hautsch, N., Yang, F., Bayesian inference in a stochastic volatility Nelson-Siegel model (2012) Computational Statistics and Data Analysis, 56 (11), pp. 3774-3792 Held, L., Schrödle, B., Rue, H., Posterior and cross-validatory predictive checks: A comparison of MCMC and INLA (2010) Statistical Modelling and Regression Structures: Festschrift in Honour of Ludwig Fahrmeir, pp. 91-110. , Kneib T. Tutz G. (eds). Springer: Berlin Kim, D.H., Orphanides, A., (2005) Term Structure Estimation with Survey Data on Interest Rate Forecasts, , Finance and Economics Discussion Series, 2005-08, Board of Directors of Federal Reserve System Koopman, S.J., Mallee, M.I.P., Van Der Wel, M., Analyzing the term structure of interest rates using the dynamic Nelson-Siegel model with time-varying parameters (2010) Journal of Business and Economic Statistics, 28, pp. 329-343 Lahiri, K., Martin, G., Special issue: Bayesian forecasting in economics (2010) International Journal of Forecasting, 26 (2), pp. 211-444 Laurini, M.P., A hybrid data cloning maximum likelihood estimator for stochastic volatility models (2013) Journal of Time Series Econometrics, 5 (2), pp. 193-229 Laurini, M.P., Hotta, L.K., Bayesian extensions to Diebold-Li term structure model (2010) International Review of Financial Analysis, 19 (5), pp. 342-350 Migon, H., Abanto-Valle, C., A Bayesian term structure modeling (2007) Proceedings of the Third Brazilian Conference on Statistical Modelling in Insurance and Finance: IME-USP, pp. 200-203 Nelson, C.R., Siegel, A.F., Parsimonious modelling of yield curves (1987) Journal of Business, 60 (4), pp. 473-489 Newton, M.A., Raftery, A.E., Approximate Bayesian inference by the weighted likelihood bootstrap (with discussion) (1994) Journal of the Royal Statistical Society B, 56, pp. 3-48 Rue, H., Martino, S., Chopin, N., Approximated Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations (with discussion) (2009) Journal of the Royal Statistical Society B, 71, pp. 319-392 Ruiz-Cárdenas, R., Krainski, E.T., Rue, H., Direct fitting of dynamic models using integrated nested Laplace approximations (2012) Computational Statistics and Data Analysis, 56 (6), pp. 1808-1828 Wang, W., Model selection (2004) Handbook of Computational Statistics, pp. 469-498. , Springer: Berlin Yu, W.-C., Zivot, E., Forecasting the term structures of Treasury and corporate yields using dynamic Nelson-Siegel models (2011) International Journal of Forecasting, 27 (2), pp. 579-591