TY - JOUR
T1 - Estimating yield spreads volatility using GARCH-type models
AU - Kim, Jong Min
AU - Kim, Dong H.
AU - Jung, Hojin
N1 - Publisher Copyright:
© 2021 Elsevier Inc.
PY - 2021/7/1
Y1 - 2021/7/1
N2 - The primary focus of this study is on modeling the relationship between the volatility of corporate bond yield spreads and other covariates, including interest rate volatility, equity volatility, and rating. The purpose of this article is to apply various GARCH models to estimate the volatility of corporate bond yield spreads. This attempt is, to the best of our knowledge, the first to analyze the volatility of the yield spreads. In particular, this study utilizes standard GARCH and various asymmetric GARCH models, including E-GARCH, T-GARCH, P-GARCH, Q-GARCH, and I-GARCH models. We select the best fitting models for the noncallable (callable) case based on AIC, and it turns out Q-GARCH (T-GARCH) is the best fitting model. The estimation results indicate that our explanatory variables are statistically significant even at the 1% significance level when we apply the best fitting models. They are generally consistent, but we observe the presence of apparent differences. Our findings should be beneficial to practitioners, including investors.
AB - The primary focus of this study is on modeling the relationship between the volatility of corporate bond yield spreads and other covariates, including interest rate volatility, equity volatility, and rating. The purpose of this article is to apply various GARCH models to estimate the volatility of corporate bond yield spreads. This attempt is, to the best of our knowledge, the first to analyze the volatility of the yield spreads. In particular, this study utilizes standard GARCH and various asymmetric GARCH models, including E-GARCH, T-GARCH, P-GARCH, Q-GARCH, and I-GARCH models. We select the best fitting models for the noncallable (callable) case based on AIC, and it turns out Q-GARCH (T-GARCH) is the best fitting model. The estimation results indicate that our explanatory variables are statistically significant even at the 1% significance level when we apply the best fitting models. They are generally consistent, but we observe the presence of apparent differences. Our findings should be beneficial to practitioners, including investors.
KW - Callable bonds
KW - Garch-type
KW - Noncallable bonds
KW - Yield spreads volatility
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U2 - 10.1016/j.najef.2021.101396
DO - 10.1016/j.najef.2021.101396
M3 - Article
AN - SCOPUS:85102865413
SN - 1062-9408
VL - 57
JO - North American Journal of Economics and Finance
JF - North American Journal of Economics and Finance
M1 - 101396
ER -