Corporate Material Event Sequences with LLMs
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תוכן מסופק על ידי The Quant / Financial Engineering Podcast and Patrick J Zoro. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי The Quant / Financial Engineering Podcast and Patrick J Zoro או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.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/
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