DiffSTOCK: Probabilistic relational Stock Market Predictions using Diffusion Models

arXiv:2403.14063v1 Announce Type: new
Abstract: In this work, we propose an approach to generalize denoising diffusion probabilistic models for stock market predictions and portfolio management. Present works have demonstrated the efficacy of modeling interstock relations for market time-series forecasting and utilized Graph-based learning models for value prediction and portfolio management. Though convincing, these deterministic approaches still fall short of handling uncertainties i.e., due to the low signal-to-noise ratio of the financial data, it is quite challenging to learn effective deterministic …

abstract arxiv cs.ce cs.lg denoising diffusion diffusion models forecasting graph graph-based management market market predictions modeling portfolio prediction predictions q-fin.cp q-fin.pm relational relations series stock type value work