About the Speaker
Yi Peng
Senior Quantitative Strategist
The economic significance of artificial intelligence (AI) is a fundamental question investors face. With the world’s top hedge funds using machine learning (ML) to find new investment opportunities, it is imperative for investors to know what kinds of financial applications may be leveraged by this constantly evolving technology. With the exponential growth in data, AI is arguably the best tool to ingest, decipher and learn the patterns of the financial markets.
In the first part of the programme, we will examine the various ways in which artificial intelligence could be used to improve investment outcomes by enhancing investor insights. The focus will be on how AI is being applied in major financial institutions and funds.
We start with the fundamentals of machine/deep learning so that the participant will have a strong foundation to understand how neural networks work and be able to extrapolate to more complicated use cases. As deep learning systems become increasingly complex, this will require a greater emphasis on the understanding of how the underlying algorithms work.
We then cover case studies using papers/books written by the top hedge funds and sell side banks. We will peek into how the world’s smartest minds in finance are modelling the financial markets, which is notoriously hard to mine due to their low signal to noise ratio.
This programme is designed to provide participants with an introduction and thematic discussion on the application of AI and ML techniques in trading and its other significant use in the capital market.
Live Webinar
Upon completion of the programme, participants will be able to:
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8.30 pm – 10.30 pm | Introduction to AI and Machine Learning
Different ML methods
Application of Machine Learning in Capital Markets
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Senior Quantitative Strategist
10:00:00 AM - 11:30:00 AM
Online Remote Proctoring
10:00:00 AM - 11:30:00 AM
Online Remote Proctoring
02:30:00 PM - 05:00:00 PM
Online Remote Proctoring
02:30:00 PM - 05:00:00 PM
Online Remote Proctoring
10:00:00 AM - 11:30:00 AM
Online Remote Proctoring
10:00:00 AM - 11:30:00 AM
Online Remote Proctoring