Applying Deep Learning to Predict M&A
Despite the global COVID-19 peak still to come, data indicates that animal spirits may be returning to M&A. A spate of deals announced in July, paired with a strong uptick in M&A searches across Refinitiv platforms, supports theories of revival.
With that, the opportunity for those able to predict deals, becomes ever greater.
Listen to this on-demand webinar to hear from our expert StarMine Quantitative Researchers on how we are developing a new quantitative prediction of M&A targets by analysing text and fundamental point-in-time data from Refinitiv and how then, to predict M&A deals.
Topics discussed:
- Technological transformation within investment banks: why now and what are the challenges?
- Introducing the StarMine M&A Prediction Model and how we apply deep learning to predict M&A activities
- Towards Interpretability: Explaining the Deep M&A Prediction Model
- Why interpretability
- Methodologies
- Future research ideas
Webinar info:
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Type
On-Demand -
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Duration
1 Hour -
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Speakers
Brenda Zhang, CFA Senior Quantitative Research Analyst - Refinitiv
Brenda Zhang is a Senior Quantitative Researcher in the Refinitiv StarMine Quantitative Research team. Her work includes research on alpha-generating equity models, fund selection and predictive models for deals intelligence. She previously worked as an investigative data analyst in the Persistent Analytics engineering team and specialized in analyzing quant models. Brenda received her M.S. in Quantitative and Computational Finance from Georgia Institute of Technology and a B.S. in Finance and Accounting from Zhejiang University. Brenda is a CFA Charter holder.Nelson Chin Director Data Science and Engineering - Refinitiv
Nelson Chin is the Director of Data Science and Engineering in the Refinitiv StarMine Quantitative Research team. His recent work includes applying deep learning to predict financial events and accelerating the path from research to production. He previously held various technical and management roles in data science and engineering with a specialisation in financial domain. Nelson received an MBA from San Jose State University, an M.S. in Computer Engineering from Santa Clara University and a B.S. in Electrical Engineering from the University of Southern California.Richard Goldman Global Head of Market Development, Quantitative Analytics - Refinitiv
Richard is the Global Head of Market Development for Refinitiv’s Quantitative Business, which includes real-time and historical data feeds, investment analytics, data management and open platforms, hosting and managed services. Prior to this, he ran Thomson Reuters’ Global Quantitative Consulting and Support division. Richard’s domain expertise in systematic and discretionary investment management was attained over a 30-year career as a Portfolio Manager and COO overseeing multi billion-dollar funds. Listen today
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