Results 41 to 50 of about 2,617 (208)

On Short‐Term Behavior of Implied Volatility for Index Options

Mathematical Finance, EarlyView.
ABSTRACT This paper investigates short‐term behavior of implied volatility of derivatives written on a market index when the index is constructed using a ranking procedure. Even when stock prices follow geometric Brownian motion dynamics, the ranking mechanism can lead to the observed term structure of at‐the‐money (ATM) implied volatility skew for ...
Huy N. Chau, Duy Nguyen, Thai Nguyen
wiley   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, Volume 45, Issue 7, Page 3170-3190, November 2026.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

Advancing Long‐Term Energy Demand Forecasting: A PRISMA‐Guided Systematic Review of AI and Econometric Models

Applied Research, Volume 5, Issue 5, October 2026.
Through a PRISMA‐guided review of 42 studies, this work compares deep learning, ensemble machine learning, and statistical/econometric models for long‐term energy demand forecasting, showing that model choice should balance accuracy, interpretability, data availability, and policy relevance.
Nor Afiza Mohd Noor, Mohamad Fani Sulaima, Mohd Khairil Rahmat, Norhafiza Mohamad, Hazlie Mokhlis   +4 more
wiley   +1 more source

Forecasting energy futures volatility based on the unbiased extreme value volatility estimator

IIMB Management Review, 2017
This paper uses the opening, high, low, and closing prices of five energy futures to estimate and model volatility based on the unbiased extreme value volatility estimator (the Add RS estimator).
Dilip Kumar
doaj   +1 more source

Forecasting and Explaining Ethanol Price Through Shapley Additive Explanations: Evidence From Two Decades of Panel Agroeconomic Data in Brazil

GCB Bioenergy, Volume 18, Issue 10, October 2026.
Explainable AI reveals how biological feedstock quality, energy markets, and policy factors jointly shape ethanol price dynamics. Deep learning improves forecasting accuracy while identifying sugarcane quality (TRS), gasoline prices, taxation, and macroeconomic variables as key drivers in a major bioenergy system.
Marilaine Colnago, Lucas A. B. de Matos, José Nuno Fidalgo, Rogério G. Negri, Wallace Casaca   +4 more
wiley   +1 more source

On the Efficacy of ARFIMA, ARTFIMA, and MARFIMA Models in Forecasting Nigerian Crude Oil Prices

UMYU Scientifica Journal
This study presents a comprehensive evaluation of three advanced long-memory time series models— the Autoregressive Fractionally Integrated Moving Average (ARFIMA), the Autoregressive Tempered Fractionally Integrated Moving Average (ARTFIMA), and the ...
Musa Tasi’u, Abubakar Bello, Hussaini Dikko Garba, Baba Alhaji Bukar   +3 more
doaj   +1 more source

İKİLİ UZUN HAFIZADA ASİMETRİ ETKİSİ: BİST BANKA ÖRNEĞİ

Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 2019
Çalışmanın amacı, Türk bankacılık sektör endeksiningetiri ve volatilitesinde ikili uzun hafıza özelliğini ARFIMA-FIGARCH veARFIMA-FIEGARCH modeli ile inceleyerek etkin piyasalar hipotezini testetmektir. Bu amaçla modelde veri seti olarak 2008-2017 dönemi
Harun Kaya, İsmail Çelik
doaj   +1 more source

Quantile‐Dependent Volatility Interconnectedness Between Commodity Markets, Oil Price Uncertainty, and Global Supply Chain Pressure

Australian Economic Papers, Volume 65, Issue 3, Page 222-260, September 2026.
ABSTRACT This study examines volatility interconnectedness among selected agricultural commodities and precious/industrial metals, together with oil price uncertainty and global supply chain pressure, over the period January 1998 to June 2024 using a Quantile‐on‐Quantile connectedness framework.
Muhammed Benli, Halil Altıntaş
wiley   +1 more source

Modelling Short- and Long-Term Dependencies of Clustered High-Threshold Exceedances in Significant Wave Heights

Mathematics, 2021
The peaks-over-threshold (POT) method has a long tradition in modelling extremes in environmental variables. However, it has originally been introduced under the assumption of independently and identically distributed (iid) data. Since environmental data
Pushpa Dissanayake, Teresa Flock, Johanna Meier, Philipp Sibbertsen   +3 more
doaj   +1 more source

A Comparison of Realized Measures of Integrated Volatility: Price Duration‐ vs. Return‐Based Approaches

Journal of Forecasting, Volume 45, Issue 4, Page 1579-1600, July 2026.
ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann, Mawuli Segnon, Timo Wiedemann   +2 more
wiley   +1 more source