Algorithmic Trading Workshop
Session 1:
Different Components of Algorithmic Trading Systems – Increasing Profitability by Optimising systems
Presenter: Rajib Borah, Co-founder & CEO, iRage
By properly leveraging the power of technology, a trader can increase the profitability of an already profitable systematic trading strategy multi-fold. This talk will look at the evolution of algorithmic trading systems – and the efficiency introduced at each step. The talk will also try to introduce participants to the various technological complexities at exchanges – and opportunities that could exist because of the same. The aim will be to have an interactive discussion and understand the functional implications (for quantitative traders) of technological complexities.
Rajib Borah is the co-founder & CEO of iRage, one of India’s leading High-Frequency Trading firms, which potentially manages the broadest exchange-traded option portfolio book in India. He is also the co-founder and director of QuantInsti, an ‘Algorithmic and Quantitative Trading’ training and research institute which has trained thousands of professionals from over 130 countries. His prior experiences include high-frequency trading on all major US & European exchanges (Optiver, Amsterdam); data analytics technology (Oracle); business strategy for a trading firm & derivatives exchanges (Strategy Consulting, PwC).Rajibhas thrice represented India at the World Puzzle Championship. He was also a finalist at the Indian National Biology Olympiad (top 24 nationwide).Rajib holds an MBA from IIM Calcutta, a bachelor’s degree in Computer Engineering from NIT Surathkal; and has internship experiences with Bloomberg in New York (derivatives research) & Solutia’s EMEA strategy HQ in Belgium.
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.
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.
