Estimating Corporate Bond Market Volatility Using Asymmetric GARCH Models

This study investigates the volatility of the Israeli corporate bond market, where corporate bonds are traded on a Limit Order Book (LOB) exchange with high retail trading activity. Using data from the Tel-Bond 20 and Tel-Bond 60 indices, we estimate various asymmetric GARCH models to capture the dynamics of bond returns. Our findings highlight a leverage effect, where negative shocks have a more significant impact on volatility than positive shocks, underscoring the importance of investor sentiment. The GJR model with a Student’s t-distribution best captures serial correlation, persistence of conditional volatility, and asymmetric volatility clustering. These results have significant implications for risk management, portfolio allocation, and regulatory policies, emphasizing the need for robust volatility forecasting models in transparent and active corporate bond markets.

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Publication Details

Journal
Risks
Published
2025-11-10
DOI
https://doi.org/10.3390/risks13110224
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
0.00
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article

Estimating Corporate Bond Market Volatility Using Asymmetric GARCH Models

Elroi Hadad, Rami Yosef, Amit Malka Fridman
Risks
Financial Risk and Volatility Modeling
article

Estimating Corporate Bond Market Volatility Using Asymmetric GARCH Models

Elroi Hadad, Rami Yosef, Amit Malka Fridman
article en

Abstract

This study investigates the volatility of the Israeli corporate bond market, where corporate bonds are traded on a Limit Order Book (LOB) exchange with high retail trading activity. Using data from the Tel-Bond 20 and Tel-Bond 60 indices, we estimate various asymmetric GARCH models to capture the dynamics of bond returns. Our findings highlight a leverage effect, where negative shocks have a more significant impact on volatility than positive shocks, underscoring the importance of investor sentiment. The GJR model with a Student’s t-distribution best captures serial correlation, persistence of conditional volatility, and asymmetric volatility clustering. These results have significant implications for risk management, portfolio allocation, and regulatory policies, emphasizing the need for robust volatility forecasting models in transparent and active corporate bond markets.

RisksVol. 13(11)
Ben-Gurion University of the Negev (IL), Sami Shamoon College of Engineering (IL)
Openalex Percentile: Top 58%
Financial Risk and Volatility Modeling
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