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last update : 10/05/2019

Algorithmic Trading Workshop

Event Date Country City Days Price  
Mon , 24 Jun 2019 United Kingdom London 1 £ 550.00 +VAT
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Session 1:

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? 

Presenter:

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”.

 

Session 2:

Applying Machine Learning to Algorithmic Trading Strategies

Presenter: Douglas Castilho, PhD Candidate, University of São Paolo

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.

Presenter:

Douglas is a PhD student in Computer Science and Computational Mathematics at the University of São Paulo (Brazil) and visiting researcher in University of Porto (Portugal). He obtained his MSc degree in Computer Science in 2014 from the Federal University of Minas Gerais – Brazil. He is researcher and professor at Federal Institute of Education, Science and Technology of South of Minas Gerais. During his career, he was awarded with Outstanding Student prize in 2012, granted by the Brazilian Society of Computing. He has been working with machine learning and financial market since 2010. Recently, he participated as finalist in Data Science Game 2017, an international competition for students held in Paris, France. He researches in areas of Computational Intelligence, Online Social Networks, Deep Learning and Financial Market, with emphasis on High Frequency Trading and Algotrading Improvement Techniques.

 

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Session 1:

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? 

Presenter:

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”.

 

Session 2:

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.

Presenter:

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.

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