Post Graduate Program in Algorithmic Trading (0-30 yrs)

Training on industry-leading Algorithmic Trading Platforms

Course Snapshot
  • FeeINR 85,000 (Tax Inclusive)
  • Work Experience0 - 30 Years
  • Duration6 Months
  • Delivery MethodLive Interactive Online Lectures
Course Detail

The Financial Markets the world over have seen a major paradigm shift in how trading is done. Trading done by computer programs known as Algorithmic Trading or Program Trading has existed for decades now, but over the recent years with the emergence of technologies, electronic markets, availability of high frequency data, faster networks, faster machines, better data analytics and more evolved theories, the domain of High Frequency Trading has emerged as a major mechanism as well as an end in itself. These algorithms depend on quantitative techniques for detection of profitable trade opportunities, generating trade signals, generating the trades and trade order execution. At each stage there is extensive use of technologies.

Algorithm Trading, both High-Frequency as well as Low Frequency, using Quantitative Methods is now a very lucrative career. A breed of traders known as the Algo-Traders or Quant-Traders has emerged who have certain skill-sets that are much sought after in the industry.

The PGPAT course, conducted by IIQF in association with Master Trust, a leading Financial Services Firm and Deltafin one of the most advanced technical analysis system available in India. The program is taught by highly qualified and experienced market practitioners is a job-oriented course that aims to produce industry-ready Algo-Traders, who can join trading desks of various financial institutions or setup their own independent algorithmic prop trading desks.

Course Highlights

- Highly qualified industry practitioner faculty
- Advanced Curriculum
- Learn machine learning based trading strategies
- Thorough hands-on training in programming algorithmic trading strategies in Python
- Training on industry leading algorithmic trading platforms OMNESYS
- Participants will get free access to Deltafin's EOD software named "Regel"

Learning Outcomes

- Carry out Statistical Analysis of Data using Statistical Packages for finding Algorithmic Trading Strategies
- Build, Back-test, Optimize and Implement Quantitative Algorithmic Trading Strategies
- Integrate the Algorithmic Trading Strategies with Algorithmic Trading Platforms

About IIQF

Indian Institute of Quantitative Finance (IIQF) is established as a center of learning in the field of Quantitative Finance and Financial Engineering. Founded by leading finance professionals and entrepreneurs with extensive global experience and expertise in specialized Quantitative Finance and Risk Management domains and educational background from the best of global institutions. It is the first institute of its kind in India that exclusively focuses on this extremely specialized field. IIQF conducts specialized courses and corporate training programs on advanced quantitative finance, risk management, financial modelling, simulations and econometrics for corporates and individuals. There are specialized courses tailored to the specific needs of investment banking and other finance verticals.

IIQF in partnership with HPC Links, a company specializing in High Performance and Parallel Computing technologies, develops Algorithmic Trading, Derivatives Valuations, Risk Analytics Solutions and Products using High Performance Computing technologies and infrastructure. It provides volatility trading strategy advisory service to derivatives trading desks of financial institutions.

It has conducted corporate training programs for banks like Bank of New York Mellon, CitiBank, Societe Generale, ING Vysya etc. In partnership with Thomson Reuters it conducts the most comprehensive course in Financial Engineering in India.

About Master Trust
Master Trust is one of the leading financial services group in India catering to retail as well as HNI client base across different products including equity trading, derivatives trading, commodity trading, currency derivatives trading, insurance, collateralized loans, portfolio management, financial planning and investment banking, directly and through its subsidiaries. Master Trust currently has over 100,000 clients spread across more than 700 points of presence (network of own branches and franchisees) across 22 states in India and a daily client trading volume of close to Rs.35 billion on all exchanges in India put together.

Master Trust has a strong belief in nurturing investment culture, attitude and inculcating a very strong approach towards value investing forms the central part of any sound investment philosophy. With an impeccable track record in client servicing of over two decades, Master Trust has now grown to 650+ strong employee organization. At Master Trust, the endeavor is to constantly meet every financial need of our esteemed clients.


Master Trust, a leading Financial Services group, offers 50% course fee refund in the form of brokerage credit for students successfully completing the course.

Course Schedule

Saturdays and Sundays

Desired Candidate Profile

- Fresh Graduates
- Management Students
- Finance Professionals
- Dealers
- Arbitrageurs
- Prop Traders
- Retail Traders


- Graduate degree in science / economics / commerce / engineering / management (with mathematics as one of the subjects)
- Prior knowledge of computer programming will be useful

Course Modules

Optional Primer(Free): Programming in Python
- For Participants not having knowledge of computer programming

Brief Curriculum

- Introduction to Algorithmic Trading
- Introduction to Quantitative Trading
- Trend following Strategies
- Momentum based Strategies
- Options Pricing
- Options Greeks
- Options Trading Strategies
- Market Neutral Strategies
- Bullish Strategies
- Bearish Strategies
- Arbitrage Strategies
- Cash Future Arbitrage
- Conversion Reversal / Put-Call Parity
- Strategy Development and Back-testing
- Architecture of a back-testing System
- Implementing a back-tester
- Parameter Optimization
- Money Management and Risk Management
- Algorithm Trading Infrastructure Setup
- Algorithmic System Design and Implementation
- Order Management
- Error Handling
- Risk Management
- Machine Learning for Quantitative Trading Using Python
- Simple Linear Regression
- Multiple Linear Regression
- Polynomial Regression
- Logistic Regression
- Support Vector Regression
- Decision Tree Regression
- Random Forest Regression
- Kernel Support Vector Machine
- Quantitative Directional Strategies
- Statistical Arbitrage Strategies
- Pairs Trading Strategies
- Arbitrage Strategies
- Index Arbitrage
- Spread Arbitrage
- Gamma Scalping
- Volatility Trading
- Risk Reversal / Volatility Skew Trading
- Dispersion Trading
- Electronic Market Making Strategies
- Working with Tick Data
- Market Microstructure and Concepts
- Order Book Dynamics
- Bid-Ask Spread
- Bid-Ask Bounce
- Latency Considerations
- Execution Algorithms