STOCK-JEPA: Prior-Anchored Latent Revision Representation Learning in Equity Markets

Excerpt

arXiv:2610.07006v1 Announce Type: new Abstract: Learning effective representations helps characterize the structure and dynamics of equity markets from financial data with a low signal-to-noise ratio. Black-box deep models can capture complex patterns but may overfit sample noise and lack explicit economic structure. Meanwhile, classic linear financial models provide interpretable references, but their oversimplified assumptions leave non-linear signals uncaptured. To combine the strengths of th