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A Hybrid Framework for Stock Price Forecasting Using Metaheuristic Feature Selection Approaches and Transformer Models Enhanced by Temporal Embedding and Attention Pruning

open access: yesApplied AI Letters, Volume 7, Issue 1, February 2026.
Workflow of the proposed hybrid BWO‐Transformer framework for stock price prediction. ABSTRACT Accurately predicting stock prices remains a major challenge in financial analytics due to the complexity and noise inherent in market data. Feature selection plays a critical role in improving both computational efficiency and predictive performance. In this
Amirhossein Malakouti Semnani   +3 more
wiley   +1 more source

Speed of Adjustment in Digital Assets in a Decentralized Financial World

open access: yesJournal of Futures Markets, Volume 46, Issue 2, Page 320-333, February 2026.
ABSTRACT This paper investigates the stability and co‐movement of cryptocurrency assets in Decentralized Finance (DeFi), with a focus on the Speed of Adjustment (SA), the rate at which shocks dissipate, and prices revert to long‐run equilibrium. SA provides a critical measure of market efficiency and portfolio allocation in a highly volatile DeFi ...
Jeremy Eng‐Tuck Cheah   +3 more
wiley   +1 more source

Models in Decision‐Making Under Risk and Uncertainty

open access: yesJournal of Economic Surveys, Volume 40, Issue 1, Page 304-320, February 2026.
ABSTRACT This paper systematically compares dominant frameworks for modeling decision‐making under risk and uncertainty, evaluating their theoretical trade‐offs and practical relevance for economic research. We establish key criteria for model selection—including predictive accuracy, descriptive realism, computational tractability, and ecological ...
Martin Höppner
wiley   +1 more source

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