Title: Forecasting the yield of Chinese corporate bonds

Authors: Maojun Zhang; Hao Li

Addresses: School of Computational Science and Mathematics, Guilin University of Electronic Technology, Guilin, China ' School of Computational Science and Mathematics, Guilin University of Electronic Technology, Guilin, China

Abstract: In this paper we focus on predicting the yield that is the centrepiece of bond markets. The dynamic Nelson-Siegel model is used to predict the yield of the Chinese corporate bonds with a class of AA, AA+ and AAA ratings. Our empirical results show that this model not only provides good in-sample fit, but also indicates the long-term, medium-term and short-term dynamic features of the yield curve of the corporate bonds with different credit ratings. Finally, we employ AR(1) model to forecast the three factors of the yield curve. Overall, the outcomes are very encouraging for the development of better forecasting systems for fixed income markets.

Keywords: corporate bonds; yield curve; Nelson-Siegel model; AR(1) model.

DOI: 10.1504/IJCSE.2020.109402

International Journal of Computational Science and Engineering, 2020 Vol.22 No.4, pp.431 - 436

Received: 26 Mar 2019
Accepted: 17 Sep 2019

Published online: 26 Aug 2020 *

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