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last update : 22/05/2018

Techniques and Strategies for Intraday Trading



Part I : Market Microstructure and Algorithmic Trading

Title 1: Different Components of Algorithmic Trading Systems - increasing profitability by optimising systems.

Rajib Ranjan Borah, CEO, iRage Capital

Summary: 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 - the efficiency introduced at each step, and the implication for a trader looking at automating their trading strategies. 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.  

Title 2: Applying Machine Learning to Algorithmic Trading Strategies

Humberto Brandao, Professor, Federal University of Alfenas & Douglas Castilho, PhD candidate, University of São Paolo

Summary: The objective of this presentation is to show you how to create databases from your own strategies and adapt them for Machine Learning methods. Besides showcasing different generic algorithmic trading strategies, some machine learning methods are also explained with a discussion about different kinds of validation processes. This presentation comprises of 2 parts; each 1.5 hours long with coding sessions using R incorporated into the programme. 

Part II : Option Portfolio Management

Rajib Ranjan Borah, CEO, iRage Capital

Summary: This discussion will aim to demystify the world of option trading. To be able to manage option portfolios better, a strong understanding of the way Option Greeks behave in various market conditions is critical. In this talk, not only are the first order derivatives discussed, but higher order derivatives will also be explained and simplified. New option trading methodologies, such as Forward Volatility, will be introduced. 

Understanding the Greeks 
♦ Simple Option Greeks: Delta, Vega, Gamma, Theta and their behaviour. How different market characteristics affect these Greeks. 
♦ Simplification of higher order Greeks: Vanna, Charm, Color, Speed, Zomma, Vomma & Veta. 

Some practical aspects 
♦ Trading forward volatility 
♦ Managing dividend risks and handling stock borrowing risks 
♦ How to analyse option positions spread across a multitude of instruments and underlyings.


Rajib Ranjan Borah  is the co-founder & CEO of iRage, one of India’s leading High-Frequency Trading firms, which manages potentially the broadest 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). Rajib has 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.

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.


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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