Corporate Material Event Sequences with LLMs
MP3•Epizód kép
Manage episode 466188211 series 2953248
A tartalmat a The Quant / Financial Engineering Podcast and Patrick J Zoro biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a The Quant / Financial Engineering Podcast and Patrick J Zoro vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
Professor zoro’s guests discussed the project they have been working on since 2024: Corporate Material Event Sequences with LLMs3 and associated sentiment scores (Historical and Real-Time with Forecasts). https://www.linkedin.com/in/patrick-z-08bb5b5a/ https://www.linkedin.com/company/lehigh-master-in-financial-engineering/ Lehigh MFEs shared their experience and views on LLMs and Deepseek with Professor Zoro who manages Lehigh MFE program: https://business.lehigh.edu/academics/graduate/masters-programs/ms-financial-engineering Fathmat Bakayoko is a MFE, working on extracting insights from SEC 8-K filings using language models and exploring crypto compliance. www.linkedin.com/in/fathmat-samira-bakayoko-30715024a." Nicholas Wagner is a MFE co-founded lab automation company Opentrons Labworks and works on blending quantitative finance with Natural Language Processing (NLP) and Large Language Models (LLMs). He sees these emerging technologies as catalysts for data-driven breakthroughs in capital markets. https://www.linkedin.com/in/nicholas-wagner-b7b743229/ Hariom Tastat is an MFE and Experienced quant and leader with expertise in the areas of quantitative research, financial AI/machine learning and derivative pricing. Co-author of the book “Machine Learning and Data Science Blueprints for Finance”. Website: https://htatsat.com/
…
continue reading
62 epizódok