Even though Data Science has become mainstream in recent years, the fact is that it has been used for decades in the world of Quantitative Finance. In this talk, we will cover how Data Science can be applied to create trading models, what are some of the best practices, and what are the different types of financial data available. We will also cover how NLP is being applied to unstructured financial content by going over some of the state-of-the-art models we are currently building at the Refinitiv Labs in Singapore.

Instructor's Bio

Kelvin Rocha PhD, Lead Data Scientist at the Refinitiv Labs

Kelvin Rocha is the Lead Data Scientist at the Refinitiv Labs where he and his research team applies the latest machine learning approaches to solve some of the most challenging problems in the financial sector. Before joining Refinitiv, he worked for five years as a quant researcher for a systematic stat arb hedge fund located in Vancouver, where he was focused on building equity trading models. Kelvin received the BS degree (Magna Cum Laude) in Electronics Engineering from the Pontificia Universidad Católica Madre y Maestra, Dominican Republic. He later attended the Georgia Institute of Technology in Atlanta, where he received an MS in Applied Mathematics, an MBA, and a Ph.D. in Electrical Engineering.

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    Leveraging Data Science for Capital Markets

    • Webinar recording