24 June 2019, London
How Machine Learning Adds Value to the Investment Process
Presenter: Ernie Chan, QTS Capital, Management, LLC
♦ Pros and cons of applying ML to investing
♦ Importance of features selection
♦ Subtleties of applying ML to investing
♦ Meta-labelling as the conservative choice
♦ Where to start?
Ernie Chan is the Managing Member of QTS Capital Management, LLC., a commodity pool operator and trading advisor. Ernie has worked for various investment banks (Morgan Stanley, Credit Suisse, Maple) and hedge funds (Mapleridge, Millennium Partners, MANE) since 1997. He received his Ph.D. in physics from Cornell University and was a member of IBM’s Human Language Technologies group before joining the financial industry. He is the author of “Quantitative Trading: How to Build Your Own Algorithmic Trading Business”, “Algorithmic Trading: Winning Strategies and Their Rationale”, and “Machine Trading: Deploying Computer Algorithms to Conquer the Markets”.
Applying Machine Learning to Algorithmic Trading Strategies
Presenter: Humberto Brandão, Head of R&D Lab, Federal University of Alfenas
The objective of this session is to show you how to create databases from your own strategies and adapt them for Machine Learning Methods. Besides presenting different generic algorithmic trading strategies, some machine learning methods are also explained with a discussion about different kinds of validation processes. This section comprises 2 parts; each 1.5 hours duration.
Humberto Brandão is the Head of the Research & Development Lab (R&D Lab) at Federal University of Alfenas (Brazil), where he is also a Professor. He has been working on Algorithmic Trading using Machine Learning since 2009. During this period, he created a realistic simulator, which has been used for High-Frequency Trading in Brazil. As a consultant for hedge funds, Humberto has been applying different techniques in order to improve their return and risk over different kind of strategies. Recently, Humberto won several important prizes in competitions related to Algorithmic Trading and Data Science.
Workshop ticket price
- Very Super Early Bird until 21 December 2018 – £195+VAT
- Super Early Bird until 16 February 2019 – £300+VAT
- Early Bird until 15 March 2019 – £400+VAT
- Standard Price – £550+VAT
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