Discussions on the Zero-drift GARCH model: Evidence from an Markov regime-switching extension

Lingbing Feng; Tong Fu; Yanlin Shi; Zili Wang

doi:10.1016/j.frl.2020.101713

Discussions on the Zero-drift GARCH model: Evidence from an Markov regime-switching extension

Lingbing Feng, Tong Fu^*, Yanlin Shi, Zili Wang

^*Corresponding author for this work

Department of Actuarial Studies and Business Analytics

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

A Zero-drift GARCH (ZD-GARCH) model is recently proposed to study conditional and unconditional heteroskedasticity together. Despite its attractive statistical properties, our research demonstrate that the stability test based on this model fails when structural changes are present. To overcome this issue, we allow the Markov regime-switching (MRS) feature within the ZD-GARCH framework and propose an MRS-ZD-GARCH model. The powerfulness of this approach is evidenced via simulation studies. Using the S&P 500 empirical data, we show that the new model can also outperform the ZD-GARCH model in practice.

Original language	English
Article number	101713
Pages (from-to)	1-8
Number of pages	8
Journal	Finance Research Letters
Volume	40
Early online date	10 Aug 2020
DOIs	https://doi.org/10.1016/j.frl.2020.101713
Publication status	Published - May 2021

Keywords

Heteroskedasticity
Regime switching
Volatility modelling
Zero-drift GARCH

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10.1016/j.frl.2020.101713

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abstract = "A Zero-drift GARCH (ZD-GARCH) model is recently proposed to study conditional and unconditional heteroskedasticity together. Despite its attractive statistical properties, our research demonstrate that the stability test based on this model fails when structural changes are present. To overcome this issue, we allow the Markov regime-switching (MRS) feature within the ZD-GARCH framework and propose an MRS-ZD-GARCH model. The powerfulness of this approach is evidenced via simulation studies. Using the S&P 500 empirical data, we show that the new model can also outperform the ZD-GARCH model in practice.",

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AU - Fu, Tong

AU - Shi, Yanlin

AU - Wang, Zili

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AB - A Zero-drift GARCH (ZD-GARCH) model is recently proposed to study conditional and unconditional heteroskedasticity together. Despite its attractive statistical properties, our research demonstrate that the stability test based on this model fails when structural changes are present. To overcome this issue, we allow the Markov regime-switching (MRS) feature within the ZD-GARCH framework and propose an MRS-ZD-GARCH model. The powerfulness of this approach is evidenced via simulation studies. Using the S&P 500 empirical data, we show that the new model can also outperform the ZD-GARCH model in practice.

KW - Heteroskedasticity

KW - Regime switching

KW - Volatility modelling

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Discussions on the Zero-drift GARCH model: Evidence from an Markov regime-switching extension

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Keywords

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