[HTML][HTML] Investors' perspective on forecasting crude oil return volatility: Where do we stand today?

L Liu, Q Geng, Y Zhang, Y Wang - Journal of Management Science and …, 2022 - Elsevier
In this paper, we review studies of oil volatility prediction from a new perspective: that of
investors who require economic evaluations of forecasting performance. Our results indicate …

Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19

J Li, R Liu, Y Yao, Q Xie - Resources Policy, 2022 - Elsevier
This study investigates the impact of the recent COVID-19 pandemic on the time-frequency
volatility spillovers across the international crude oil market and Chinese major energy …

Volatility forecasting of crude oil futures based on Bi-LSTM-Attention model: The dynamic role of the COVID-19 pandemic and the Russian-Ukrainian conflict

Y Xu, T Liu, P Du - Resources Policy, 2024 - Elsevier
The COVID-19 epidemic and the Russian-Ukrainian conflict have created significant
uncertainty in the crude oil market, greatly increasing the difficulty of crude oil futures price …

Effects of COVID-19 vaccination programs on EU carbon price forecasts: Evidence from explainable machine learning

C Yang, H Zhang, F Weng - International Review of Financial Analysis, 2024 - Elsevier
The COVID-19 pandemic continues to destroy the carbon market. To alleviate the situation,
governments launched vaccination program campaigns. This study aims to predict two …

COVID-19 pandemic and Romanian stock market volatility: A GARCH approach

ȘC Gherghina, DȘ Armeanu, CC Joldeș - Journal of Risk and Financial …, 2021 - mdpi.com
This paper investigates the volatility of daily returns on the Romanian stock market between
January 2020 and April 2021. Volatility is analyzed by means of the representative index for …

Information fusion-based genetic algorithm with long short-term memory for stock price and trend prediction

A Thakkar, K Chaudhari - Applied Soft Computing, 2022 - Elsevier
Abstract Information fusion is one of the critical aspects in diverse fields of applications;
while the collected data may provide certain perspectives, a fusion of such data can be a …

Analysis of financial pressure impacts on the health care industry with an explainable machine learning method: China versus the USA

F Weng, J Zhu, C Yang, W Gao, H Zhang - Expert Systems with Applications, 2022 - Elsevier
This study analyzes the role of financial pressure in forecasting the volatility of health care
stock. The main finding shows that financial pressure helps to improve the volatility …

Asymmetric impact of COVID-19 news on the connectedness of the green energy, dirty energy, and non-ferrous metal markets

L Wang, L Guan, Q Ding, H Zhang - Energy Economics, 2023 - Elsevier
In the transition from dirty to green energy, non-ferrous metals are crucial. The COVID-19
pandemic has severely hampered the energy transition process and affected risk …

RETRACTED ARTICLE: Forecasting carbon emissions future prices using the machine learning methods

U Shahzad, T Sengupta, A Rao, L Cui - Annals of Operations Research, 2023 - Springer
Due to the uncertainty surrounding the coupling and decoupling of natural gas, oil, and
energy commodity futures prices, the current study seeks to investigate the interactions …

[HTML][HTML] Introspecting predictability of market fear in Indian context during COVID-19 pandemic: An integrated approach of applied predictive modelling and …

I Ghosh, MK Sanyal - … Journal of Information Management Data Insights, 2021 - Elsevier
Financial markets across the globe have seen rapid volatility and uncertainty owing to scary
and disruptive impacts of COVID-19 pandemic. Mayhem wrecked by frequent lockdowns …