Scaling Conditional Autoencoders for Portfolio Optimization via Uncertainty-Aware Factor Selection

By Ryan Engel, Yu Chen, Pawel Polak, Ioana Boier

Published 2025-11-21

Everscope rating

1548.4

Relevance to quantitative trading

9 / 10

Implementation complexity

7 / 10

Reproducibility

3 / 5

About this paper

Methodology: Uncertainty-Aware Factor Selection with High-Dimensional Conditional Autoencoders. Problem types: Portfolio Optimization, Time Series Forecasting, Dimensionality Reduction, Zero-shot Learning, Optimization, Risk Management.

arXiv:2511.17462 · Paper rankings

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