Rachid Belhachemi
E-MAIL:Rachid.Belhachemi@xjtlu.edu.cn
Deparment: School of Science

Items: 2

Views: 467

1. Yield Curve Forecasting with the Burg Model

Author:Rostan, P;Belhachemi, R;Racicot, FE

Source:JOURNAL OF FORECASTING,2017,Vol.36

Abstract:We introduce a versatile and robust model that may help policymakers, bond portfolio managers and financial institutions to gain insight into the future shape of the yield curve. The Burg model forecasts a 20-day yield curve, which fits a pth-order autoregressive (AR) model to the input signal by minimizing (least squares) the forward and backward prediction errors while constraining the autoregressive parameters to satisfy the Levinson-Durbin recursion. Then, it uses an infinite impulse response prediction error filter. Results are striking when the Burg model is compared to the Diebold and Li model: the model not only significantly improves accuracy, but also its forecast yield curves stick to the shape of observed yield curves, whether normal, humped, flat or inverted. Copyright (c) 2016 John Wiley & Sons, Ltd.
2. Modelling conditional moments and correlation with the continuous hidden-threshold-skew-normal distribution

Author:Belhachemi, R;Rostan, P;Racicot, FE

Source:APPLIED ECONOMICS,2015,Vol.47

Abstract:A key issue in modelling conditional densities of returns of financial assets is the time-variation of conditional volatility. The classic econometric approach models volatility of returns with the generalized autoregressive conditional heteroscedasticity (GARCH) models where the conditional mean and the conditional volatility depend only on historical prices. We propose a new family of distributions in which the conditional distribution depends on a latent continuous factor with a continuum of states. The distribution has an interpretation in terms of a mixture distribution with time-varying mixing probabilities. The distribution parameters have economic interpretations in terms of conditional volatilities and correlations of the returns with the hidden continuous state. We show empirically that this distribution outperforms its main competitor, the mixed normal conditional distribution, in terms of capturing the stylized facts known for stock returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence.
Total 2 results found
Copyright 2006-2020 © Xi'an Jiaotong-Liverpool University 苏ICP备07016150号-1 京公网安备 11010102002019号