Cornell Master in Financial Engineering Students Named Winners in the Society of Quantitative Analysts' (SQA) Alphathon 2024 Competition
A team of five Cornell MFE students and one NYU graduate student proposed a winning solution in competition with 77 other teams. Their topic was sponsored by AllianceBernstein, and they were tasked with answering the question, "Can We Use LLMs and Alternative Data to Outperform the S&P500?" The students had three weeks to submit a five-page paper detailing their approach in applying Large Language Models to the analysis of market regimes. The data sources came from Eagle Alpha, Quant Connect, Data Bento, and more. Expounding upon their winning research, Shun Wang (MFE '24) noted, "This... Read more