Impact of carbon market prices on oil market fear across quantiles DOI
Jihong Xiao, Yan Zheng

Applied Economics Letters, Год журнала: 2024, Номер unknown, С. 1 - 7

Опубликована: Июль 30, 2024

This paper uses quantile regression to investigate how carbon market prices affect oil fear. Our results show a significant and strong negative effect of changes in on fear at high quantiles. Notably, this is driven by the decrease rather than increase prices. We also observe that COVID-19 pandemic enhances impact decreased

Язык: Английский

Shockwaves across borders: Did the 2023 banking crisis reshape global banking sector linkages? DOI Creative Commons
Chun‐Sung Huang, Ailie Charteris

Finance research letters, Год журнала: 2025, Номер unknown, С. 107571 - 107571

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Geopolitical risks and oil market fear: Country-specific spillover effects DOI
Jihong Xiao, Jingyu Zhang, Yan Zheng

и другие.

Research in International Business and Finance, Год журнала: 2025, Номер unknown, С. 102985 - 102985

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Navigating Median and Extreme Volatility in Stock Markets: Implications for Portfolio Strategies DOI Creative Commons
Muhammad Abubakr Naeem

International Review of Economics & Finance, Год журнала: 2024, Номер 95, С. 103507 - 103507

Опубликована: Авг. 16, 2024

This study explores the interdependencies among developed stock markets using LASSO technique with quantile regression within a network analysis framework. Traditional forecasting methods often fail during volatile market conditions, necessitating innovative approaches that blend interconnectedness and factor modeling. By employing regression, which examines financial assets across various distribution quantiles, this addresses tail risk, critical aspect of behavior crises. The framework provides insights into relationships between markets, highlighting how variables interact complex system. assesses behaviors at different levels, considering clustering coefficients to analyze cycles, middlemen, ins, outs. Additionally, it impact several factors on interconnectedness, offering interplay individual stocks broader conditions. Key findings demonstrate incorporating models enhances accuracy informs better decision-making, leading portfolios can withstand extreme conditions provide superior risk-adjusted returns.

Язык: Английский

Процитировано

1

Introducing a novel fragility index for assessing financial stability amid asset bubble episodes DOI
Radu Lupu, Adrian Cantemir Călin, Dan Gabriel Dumitrescu

и другие.

The North American Journal of Economics and Finance, Год журнала: 2024, Номер unknown, С. 102291 - 102291

Опубликована: Сен. 1, 2024

Язык: Английский

Процитировано

1

From Economic Policy Uncertainty to Implied Market Volatility: Nothing to Fear? DOI
Lu Yang

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0

Impact of carbon market prices on oil market fear across quantiles DOI
Jihong Xiao, Yan Zheng

Applied Economics Letters, Год журнала: 2024, Номер unknown, С. 1 - 7

Опубликована: Июль 30, 2024

This paper uses quantile regression to investigate how carbon market prices affect oil fear. Our results show a significant and strong negative effect of changes in on fear at high quantiles. Notably, this is driven by the decrease rather than increase prices. We also observe that COVID-19 pandemic enhances impact decreased

Язык: Английский

Процитировано

0