Milena Vuletić has been recognized as a Rising Star in quant finance for her groundbreaking work on a machine learning-based volatility model named VolGan. This model predicts next-day movements in option implied volatility surfaces, showcasing a significant advancement in the field. Initially, Vuletić faced skepticism from her PhD supervisor, Rama Cont, who favored a traditional factor model approach. However, her expertise in generative adversarial networks (GANs) allowed her to develop a novel method that ultimately outperformed classical models during testing phases, particularly in volatile periods such as early 2019 and the onset of the Covid pandemic.
Vuletić's innovative approach not only highlights the potential of machine learning in finance but also reflects a broader trend of integrating advanced technology into quantitative trading strategies. As she prepares to submit her PhD thesis in 2025, Vuletić remains undecided about her future career path, leaving open the possibility of further contributions to the field of quantitative finance. Her recognition comes at a time when the industry is increasingly valuing the intersection of technology and finance, particularly in the context of evolving market dynamics and the need for sophisticated risk management tools. [e0b7245a]