Results 151 to 160 of about 83,082 (289)

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer   +3 more
wiley   +1 more source

Correction: G-bic: generating synthetic benchmarks for biclustering [PDF]

open access: gold
Eduardo N. Castanho   +3 more
openalex   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source

Ultraviolet Band High Resolution Detection Applications with Magnetic Dipole Quasi-Bic Resonant Dielectric Metasurfaces

open access: green, 2022
chen zhang   +7 more
openalex   +1 more source

Forecasting Count Data With Varying Dispersion: A Latent‐Variable Approach

open access: yesJournal of Forecasting, EarlyView.
ABSTRACT Count data, such as product sales and disease case counts, are common in business forecasting and many areas of science. Although the Poisson distribution is the best known model for such data, its use is severely limited by its assumption that the dispersion is a fixed function of the mean, which rarely holds in real‐world scenarios.
Easton Huch   +3 more
wiley   +1 more source

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