Winter Training Program: Jan - Mar 2019

Applications for winter program are now open. Apply here.


The quant training program is designed to offer insight into the quantitative trading strategy modeling. Through the program, you will get hands-on experience in developing mathematical or quantitative models using our python-based toolbox and web platform. The program will combine virtual training and assignments in developing alphas/trading models. By the end of this program, you will be able to design and backtest your own data driven quantitative trading strategies.

Completion Requirements

  1. You must complete a training module to receive access to the next module
  2. You must complete at least 75% of the course assignments to be eligible to participate in capstone project -  select strategies will be traded live with profit share opportunities upto Rs 1 lakh
  3. You must submit the capstone project to receive a certificate of completion


The program will include a mix of training videos, reading material, iPython notebooks, off-platform assignments and programming assignments. Details of every weeks tutorial content and assignment will be made available at the start of the week. Your submissions for the week will be due by 11:59 pm Sunday of that week.

Program Structure

Week 1 - Python

Introduction to Python Programming and commonly used Python libraries. This training will be conducted off the platform. You will be required to complete a Python training module and upload the certificate of completion back on our platform

Estimate time: 6 hours

Week 2 - Basic Math and Statistics

We will discuss basic math and stat concepts as applied to trading and continue to use our Python skills to solve assignments. You will be required to complete a series of Ipython notebooks and upload them back to the platform.

Estimate time: 6 hours

Week 3 - Time Series Basics and Financial Jargon

We will discuss some commonly used financial terms that you will be using for the rest of the course

Estimate time: 4 hours

Week 4 - Math and Statistics Continued - Time Series

We will delve deeper into probability and stats as applied to trading. You will be required to complete a series of Ipython notebooks and upload them back to the platform.

Estimate time: 6 hours

Week 5 - Writing a simple trading strategy

Use everything we’ve learnt so far to write a basic mean reversion trading strategy. You will work through an iPython notebook and make a submission of your basic strategy to the platform.

Estimate time: 8 hours

Week 6 - Improving Alphas

Learn the concept of “alpha” and how we can improve strategy performance. You are going to use your submission from the previous time and try to improve it’s alpha.

Estimate time: 8 hours

Week 7 - Statistical Arbitrage : Market Neutral Strategies and Hedging

We will talk about “hedging” - a very important concept in intraday and positional trading. Design and improve a simple market neutral trading strategy.

Estimate time: 10 hours

Week 8 - Long/Short Trading Strategies

We will extend our discussion from last week to design simple Long/Short Trading strategies.

Estimate time: 8 hours

Week 9 - Strategy Execution and Reducing Costs [Optional]

Trading costs are the nemesis of any trading strategies - they can turn a very profitable system completely useless. We will learn about different type of trading costs and how to optimize strategy execution to reduce costs.

Estimate time: 10 hours

Week 10 - Strategy Risk Management [Optional]

No trading system is complete without an inbuilt risk management to avoid catastrophic losses. We will talk about how to build in basic risk checks into our system.

Estimate time: 8 hours

Week 11 - Final Project [Optional]

You will work on an actual Hedge Fund problem posed by one of our trading partners and use everything we’ve learnt so far to develop an alpha.

Week 12 - Final Project [Optional]

Improve on Sharpe and risk metrics of project from previous week. Final submissions to be made by April 1.