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The Financial Connectome: A Brain-Inspired Framework for Modeling Latent Market Dynamics
Yuda Bi, Vince D Calhoun
https://arxiv.org/abs/2508.02012 https://…

The Financial Connectome: A Brain-Inspired Framework for Modeling Latent Market Dynamics
We propose the Financial Connectome, a new scientific discipline that models financial markets through the lens of brain functional architecture. Inspired by the foundational work of group independent component analysis (groupICA) in neuroscience, we reimagine markets not as collections of assets, but as high-dimensional dynamic systems composed of latent market modules. Treating stocks as functional nodes and their co-fluctuations as expressions of collective cognition, we introduce dynamic Ma…

Signal from Noise Signal from Noise: A Neural Network-Based Denoising Approach for Measuring Global Financial Spillovers
Abdullah Karasan, \"Ozge Sezgin Alp
https://arxiv.org/abs/2509.01156

Signal from Noise Signal from Noise: A Neural Network-Based Denoising Approach for Measuring Global Financial Spillovers
Filtering signal from noise is fundamental to accurately assessing spillover effects in financial markets. This study investigates denoised return and volatility spillovers across a diversified set of markets, spanning developed and developing economies as well as key asset classes, using a neural network-based denoising architecture. By applying denoising to the covariance matrices prior to spillover estimation, we disentangle signal from noise. Our analysis covers the period from late 2014 to…