Contagion’s Hidden Networks: Mapping Volatility Spillovers with Machine Learning

New research reveals a surprisingly limited scope of volatility transmission between financial markets, defying expectations of widespread contagion.

New research reveals a surprisingly limited scope of volatility transmission between financial markets, defying expectations of widespread contagion.
Researchers have developed a unified artificial intelligence capable of forecasting both individual stock performance and broader financial system vulnerabilities.

A new framework accurately forecasts deep learning model performance by separating data difficulty from model architecture, paving the way for smarter resource allocation.

A new multi-agent system harnesses the power of artificial intelligence to rapidly integrate and analyze data from disparate sources, enabling more effective real-time disease surveillance.

A new deep learning approach dramatically speeds up full waveform inversion by intelligently focusing on the most informative seismic data.
New research reveals that large language models aren’t just vulnerable to code-based attacks, but also inherit predictable psychological flaws from the humans who created them.

A new analysis reveals that fragmented definitions of the same event across prediction markets lead to price discrepancies and limit their effectiveness as global information aggregators.

A new deep learning model leverages advanced image analysis to improve the accuracy and interpretability of skin lesion diagnosis.
Traditional statistical methods fall short when evaluating adaptive AI in healthcare, necessitating a shift towards quantifying and managing the inherent risks of these systems.
New research reveals that artificial intelligence systems demonstrate a clear preference for companies with strong environmental, social, and governance practices, potentially influencing financial markets.