Insights Into Bloomberg’s Proprietary Dividend Projections (BDVD?
Join us for an exclusive session where we unveil the latest enhancements to Bloomberg’s proprietary dividend projection model (BDVD). With improved methodologies, advanced technology, and insights from our global team of analysts, BDVD now delivers even more precise and actionable dividend forecasts for companies and ETFs. Learn how these enhancements can help you stay ahead in dividend forecasting and investment decision-making.
Speakers
Dominick D'Angelo
Enterprise Data Product Manager
Bloomberg
Dominick oversees product development for Bloomberg's Enterprise Data solutions for Cash Equity and Entity Reference Data, as well as Economics. He joined Bloomberg's Analytics Department in 2009, where he managed Foreign Exchange, Commodities, and Structured Cash Flow Product teams. Dominick holds a Bachelor of Arts in Finance from Muhlenberg College, and a Masters in Business Administration from Fordham University.
Jessica Beatus
Dividend Projections Product Owner
Bloomberg Data
Jessica Beatus is a Global Data Product Manager at Bloomberg for the Dividend Forecasting and Supply Chain teams. Jessica is responsible for managing relationships and engagements with business, infrastructure and technology stakeholders plus coordinating with her counterparts globally. Before joining Bloomberg LP, Jessica spent 10 years as an income driven research analyst at boutique investment firm investing in credit and equities. Jessica received her MSF from Johns Hopkins Carey School of Business, and a BA in Economics and Spanish from Towson University in Baltimore Maryland.
Saher Esmeir
AI Manager Dividends & Agency Pricing
Bloomberg AI Engineering
Michael Beal
Head of Enterprise Data Science Specialists
Bloomberg
Michael Beal is the head of Data Science for Bloomberg Enterprise Data, North America. His team is responsible for helping define Bloomberg Enterprise Data’s A.I. Strategy, publishing data-driven research and prototyping new products and solutions for quantitative and A.I. workflows. Prior to joining Bloomberg, Michael was the co-founder of J.P. Morgan’s Intelligent Solutions group, where he led the build of the industry’s first machine learning approach to Collateral and Counterparty Risk Optimization for OTC derivative products. After J.P. Morgan, Michael spent 8 years leveraging proprietary cloud technologies and Generative A.I. to systematically manage U.S. equity portfolios for family offices. Michael graduated from Harvard College with Honors in Economics and Harvard Business School with distinction.