AI RESEARCH
High-Quality Synthetic Financial Time-Series using a GAN-Diffusion Framework
arXiv CS.AI
•
ArXi:2605.27113v1 Announce Type: cross In recent years, financial institutions and firms have increasingly adopted synthetic data to address data scarcity and to generate counterfactual market scenarios. However, reproducing all the statistical properties of financial time series, commonly known as stylized facts, remains an open challenge for many existing general-purpose architectures.