Cited by Effects of the climate-related sentiment on agricultural spot prices: Insights from Wavelet Rényi Entropy analysis

Geopolitical risk and uncertainty in energy markets: Evidence from wavelet-based methods DOI

Ivan De Crescenzo,

Loretta Mastroeni,

Greta Quaresima

и другие.

Energy Economics, Год журнала: 2025, Номер unknown, С. 108281 - 108281

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

Wavelet and Deep Learning Framework for Predicting Commodity Prices Under Economic and Financial Uncertainty DOI

Lyubov Doroshenko, Loretta Mastroeni, Alessandro Mazzoccoli

и другие.

Mathematics, Год журнала: 2025, Номер 13(8), С. 1346 - 1346

Опубликована: Апрель 20, 2025

The analysis of commodity markets—particularly in the energy and metals sectors—is essential for understanding economic dynamics guiding decision-making. Financial uncertainty indices provide valuable insights that help reduce price uncertainty. This study employs wavelet analyses energy-based measures to investigate relationship between these prices across multiple time scales. approach captures complex, time-varying dependencies, offering a more nuanced how influence fluctuations. By integrating this with predictability measures, we assess enhance forecasting accuracy. We further incorporate deep learning models capable capturing sequential patterns financial series into our better evaluate their predictive potential. Our findings highlight varying impact on prices, showing while some offer information, others display strong correlations without significant power. These results underscore need tailored models, as different commodities react differently same conditions. combining wavelet-based machine techniques, presents comprehensive framework evaluating role markets. gained can support investors, policymakers, market analysts making informed decisions.

Язык: Английский

Процитировано

Enhancing ECG Images Using Wave Translation Algorithm with CWT—The Coronary Atherosclerosis Detection DOI