Results 61 to 70 of about 11,262 (157)
Environmetrics, Volume 36, Issue 7, October 2025.ABSTRACT Climate change is increasingly recognized as a driver of health‐related outcomes, yet its impact on pharmaceutical demand remains largely understudied. As environmental conditions evolve and extreme weather events intensify, anticipating their influence on medical needs is essential for designing resilient healthcare systems.
Viviana Schisa, Matteo Farnè
wiley +1 more source
VARMA-EGARCH Model for Air-Quality Analyses and Application in Southern Taiwan
Atmosphere, 2020 This study adopted the Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) model to analyze seven air pollutants (or the seven variables in this study) from ten air quality monitoring stations in the Kaohsiung–Pingtung Air ...
Edward Ming-Yang Wu, Shu-Lung Kuo
doaj +1 more source
Hedging Foreign Exchange Risks with Gold: EGARCH Approach [PDF]
African Journal of Applied Statistics, 2014 This work presents an investigation on whether investments in Gold can serve as a hedge against the depreciation in currencies. The long term relationship between Gold price and the Japanese Yen per US Dollar, British Pound per US Dollar and South African Rand per US Dollar exchange rate was investigated using monthly data on Gold price and the three ...
GIDEON, Frednard, NUUGULU, Samuel
openaire +2 more sources
Examining the Financial Impact of Biodiversity‐Related Reputational Disasters
Corporate Social Responsibility and Environmental Management, Volume 32, Issue 4, Page 4500-4522, July 2025.ABSTRACT This research investigates the reaction of financial markets to biodiversity‐related corporate events, utilising an EGARCH model to assess the implications on stock returns and volatility. Results reveal that markets significantly respond to these events, demonstrating heightened sensitivity and volatility that underscore the financial ...
Erdinc Akyildirim, Shaen Corbet
wiley +1 more source
Assessing the relation between equity risk premium and macroeconomic volatilities in the UK [PDF]
, 2008 This paper uses the exponential GARCH-in-mean model to analyse the relationship between the equity risk premium and macroeconomic volatility. This premium depends upon conditional volatility, which is significantly affected by the long bond yield, acting
Kizys, Renatas, Spencer, P.
core
Evaluating the Resilience of ESG Investments in European Markets During Turmoil Periods
Corporate Social Responsibility and Environmental Management, Volume 32, Issue 4, Page 5006-5020, July 2025.ABSTRACT This study investigates the resilience of Environmental, Social, and Governance (ESG) investments during periods of financial instability, comparing them with traditional equity indices of the three largest economies in the European Union by gross domestic product: Germany, France, and Italy.
Barbara Iannone +2 more
wiley +1 more source
Extended Multivariate EGARCH Model: A Model for Zero‐Return and Negative Spillovers
Journal of Forecasting, Volume 44, Issue 4, Page 1266-1279, July 2025.ABSTRACT This paper introduces an extended multivariate EGARCH model that overcomes the zero‐return problem and allows for negative news and volatility spillover effects, making it an attractive tool for multivariate volatility modeling. Despite limitations, such as noninvertibility and unclear asymptotic properties of the QML estimator, our Monte ...
Yongdeng Xu
wiley +1 more source
THE DYNAMICS OF THE DOW JONES SUKUK VOLATILITY: EVIDENCE FROM EGARCH MODEL [PDF]
Business Excellence and Management, 2015 This paper aims to test the effect of asymmetric shocks on the volatility of the Dow Jones Sukuk. To this end, we applied the EGARCH model to give a clear idea of the effect of asymmetric shocks on the volatility of the sukuk.
Nadhem SELMI +2 more
doaj
A note on the determinants of non‐fungible tokens returns
International Journal of Finance &Economics, Volume 30, Issue 3, Page 3201-3211, July 2025.Abstract We aim to identify the determinants of non‐fungible tokens (NFTs) returns. The 10 most popular NFTs based on their price, trading volume, and market capitalisation are examined. Twenty‐three potential drivers of the returns of each NFT are considered.
Theodore Panagiotidis +1 more
wiley +1 more source
Forecasting Digital Asset Return: An Application of Machine Learning Model
International Journal of Finance &Economics, Volume 30, Issue 3, Page 3169-3186, July 2025.ABSTRACT In this study, we aim to identify the machine learning model that can overcome the limitations of traditional statistical modelling techniques in forecasting Bitcoin prices. Also, we outline the necessary conditions that make the model suitable.
Vito Ciciretti +4 more
wiley +1 more source