Volatility spillovers between stock, bond, oil, and gold with portfolio implications: Evidence from China

Zhang, Yongjie; Wang, Meng; Xiong, Xiong; Zou, Gaofeng

doi:10.1016/j.frl.2020.101786

Cited by 50 publications

(16 citation statements)

References 36 publications

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“…We use Engle's (2002) bivariate DCC-GARCH model for conditional correlation analysis as DCC has been defined as the preferred model by most authors in our field ( Liu and Lee, 2022 , Zhang et al, 2021 ). The model is defined as follows:

where R t = ( R s,t , R h,t )′ is a vector of conditional stock returns, R s,t , and returns of a safe haven asset, R h,t , with h ∈ { gold, bonds }.…”

Section: Methodsmentioning

confidence: 99%

Gold, bonds, and epidemics: A safe haven study

Choudhury

Kinateder

Neupane

2022

Finance Research Letters

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where R t = ( R s,t , R h,t )′ is a vector of conditional stock returns, R s,t , and returns of a safe haven asset, R h,t , with h ∈ { gold, bonds }.…”

Section: Methodsmentioning

confidence: 99%

Gold, bonds, and epidemics: A safe haven study

Choudhury

Kinateder

Neupane

2022

Finance Research Letters

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“…Logistic regression (LR) models are used to forecast binary outcomes. The scientific community in economics, finance, sociology, and other social sciences has already widely adopted this toolkit ( Ben Jabeur, 2017 ; Zhang et al, 2020a , 2020b ). The logistic regression model typically estimates the probability that an occurrence happens from a series of predictors.…”

Section: Machine Learning Modelsmentioning

confidence: 99%

The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning

Jabeur¹,

Khalfaoui

Arfi

2021

Journal of Environmental Management

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This study aims to predict oil prices during the 2019 novel coronavirus (COVID-19) pandemic by looking into green energy resources, global environmental indexes (ESG), and stock markets. The study employs advanced machine learning, such as the LightGBM, CatBoost, XGBoost, Random Forest (RF), and neural network models. An accurate forecasting framework can effectively capture the trend of the changes in oil prices and reduce the impact of the COVID-19 pandemic on such prices. Additionally, a large dataset with different asset classes was used to investigate the crash period. The research also introduced SHapely Additive exPlanations (SHAP) values for model analysis and interpretability. The empirical results indicate the superiority of the RF and LightGBM over traditional models. Moreover, this new framework provides favorable explanations of the model performance using the efficient SHAP algorithm. It also highlights the core features of predicting oil prices. The study found that high values of GER and ESG lead to lower crude oil prices. Our results are crucial for investors and policymakers in promoting climate change mitigation and sustained economic prosperity through green energy resources.

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“…Studies like Koutmos (2018), Aktas, Kryzanowski, and Zhang (2021), and Zhang, Wang, Xiong, and Zou (2020) also examine the return spillover effects between different asset classes. The underlying argument for such spillover effects is the movement of funds across different assets.…”

Section: Introductionmentioning

confidence: 99%

COVID‐19 and ESG preferences: Corporate bonds versus equities

Singh

2021

Int Rev Finance

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I examine investors' within ESG investment preferences during the COVID-19 pandemic by investigating the return spillover effects across the three different corporate bonds and equities-based investment strategies. Investors prefer making investments in ESG leaders in the investment-grade corporate bond market over ESG leaders in the equity and high yield corporate bond markets during times of uncertainty. It suggests that capital flows away from high yield corporate bond and equity markets to the investment-grade corporate bond market. Investors find refuge in firms with relatively higher ESG ratings and creditworthiness in the fixed income market over the equity market during crisis periods.

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Volatility spillovers between stock, bond, oil, and gold with portfolio implications: Evidence from China

Cited by 50 publications

References 36 publications

Gold, bonds, and epidemics: A safe haven study

Gold, bonds, and epidemics: A safe haven study

The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning

COVID‐19 and ESG preferences: Corporate bonds versus equities

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