Results 181 to 190 of about 72,155 (291)

When the Tail Wags the Dog: A Time‐Varying FCVAR Analysis of Bitcoin Market

Journal of Futures Markets, Volume 46, Issue 3, Page 529-544, March 2026.
ABSTRACT This paper examines how the relationship between Bitcoin spot and futures markets has evolved using a time‐varying Fractionally Cointegrated Vector Autoregressive (FCVAR) model. We are the first to apply this methodology dynamically to cryptocurrency markets, allowing us to simultaneously analyze long‐run equilibrium, pricing patterns, market ...
Filippo di Pietro, Antonio A. Golpe, Jose Carlos Vides   +2 more
wiley   +1 more source

STAGE framework: A stock dynamic anomaly detection and trend prediction model based on graph attention network and sparse spatiotemporal convolutional network. [PDF]

PLoS One
Shi M, Mohamad Rasli R, Wang SL.
europepmc   +1 more source

For the Times They Are A‐Changin': Towards a ‘Homeland Economics’ Paradigm of the European Union?

JCMS: Journal of Common Market Studies, Volume 64, Issue 2, Page 467-490, March 2026.
Abstract There is an ongoing academic debate on whether geopolitical aspirations are reshaping the paradigm of the EU's neoliberal industrial and trade policy. The scrutiny has intensified with China's new economic power, the Trump and Biden administrations, Covid‐19 and Russia's invasion of Ukraine. However, the theory of paradigm changes expects that
Henrik Brockenhuus‐Schack, Peter Nedergaard   +1 more
wiley   +1 more source

Revisiting the excess volatility puzzle through the lens of the Chiarella model. [PDF]

PLoS One
Kurth JG, Majewski AA, Bouchaud JP.
europepmc   +1 more source

How to measure earnings surprises: Based on revised market reaction. [PDF]

PLoS One, 2023
Pan Q, Huang K.
europepmc   +1 more source

Extreme‐weather risk and the cross‐section of stock returns

Journal of Risk and Insurance, Volume 93, Issue 1, Page 163-198, March 2026.
Abstract We document an extreme‐weather risk premium in the cross‐section of stock returns. Between 1995 and 2019, stocks of domestic U.S. firms with the most negative sensitivity to aggregate storm losses earned an annual excess‐return spread of more than 6 percentage points relative to those with the most positive sensitivity, a difference not ...
Alexander Braun, Julia Braun, Florian Weigert   +2 more
wiley   +1 more source

TIC-FusionNet: A multimodal deep learning framework with temporal decomposition and attention-based fusion for time series forecasting. [PDF]

PLoS One
Chen L, Fan X.
europepmc   +1 more source

Unlocking IIoT Potential: A Systematic Review of AI Applications, Adoption Drivers, and Implementation Barriers

Applied AI Letters, Volume 7, Issue 1, February 2026.
Unlocking IIoT Potential with AI. ABSTRACT Artificial Intelligence (AI) is playing an increasingly vital role in the Industrial Internet of Things (IIoT), enabling predictive analytics, real‐time monitoring, and autonomous operations across industries such as manufacturing, logistics, and energy.
Tinashe Magara, Mampilo Phahlane
wiley   +1 more source

Financial trading decision model based on deep reinforcement learning for smart agricultural management. [PDF]

PeerJ Comput Sci
Fan D, Ab Razak NH, Soh WN.
europepmc   +1 more source

Board Characteristics and Climate Commitment: A Comprehensive Analysis Unraveling Linear and Nonlinear Relationships

Business Strategy and the Environment, Volume 35, Issue 2, Page 2243-2265, February 2026.
ABSTRACT In an era of increasing environmental awareness, this study analyzes the relationship between board characteristics and corporate climate commitment across various industries. Our empirical analysis examines a comprehensive dataset that includes 4027 firms from the United States and Canada over the period from 2010 to 2022 and employs panel ...
Ines Ben Mehrez, Aymen Ajina, Amel Farhat   +2 more
wiley   +1 more source