Post Graduate Program in Algorithmic Trading offered by Indian Institute of Quantitative Finance
Post Graduate Program in Algorithmic Trading at Indian Institute of Quantitative Finance Overview
Duration | 8 months |
Start from | Start Now |
Total fee | ₹1.38 Lakh |
Mode of learning | Online |
Official Website | Go to Website |
Credential | Certificate |
Post Graduate Program in Algorithmic Trading at Indian Institute of Quantitative Finance Highlights
- Earn a certificate after completion of course from Indian Institute of Quantitative Finance
- Highly qualified industry practitioner faculty
- Thoroughly hands-on training in programming algorithmic trading strategies in Python
- Interest Free EMI payment option is available through our NBFC partners
Post Graduate Program in Algorithmic Trading at Indian Institute of Quantitative Finance Course details
Fresh Graduates
Management Students
Finance Professionals
Dealers
Prop Traders
Arbitrageurs
Retail Traders
Understand the structure and functioning of financial markets, including stocks, bonds, and derivatives
Learn the basics of algorithmic trading, including market microstructure, order types, and execution strategies
Develop skills in programming languages commonly used in finance, such as Python and R, for data analysis and algorithm development
The PGPAT course or Post graduate program in Algorithmic trading online conducted by IIQF is taught by highly qualified and experienced market practitioners and is a job-oriented Masters in Algorithm Trading online course
It 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
Algorithmic Trading (abv. Algo Trading) also known as Program Trading or Automated Trading, essentially implies that the trading is done by computer programs
Program Schedule
Saturdays and Sundays
Program Timing
10:00 AM to 1:00 PM IST (UTC +5:30)
Post Graduate Program in Algorithmic Trading at Indian Institute of Quantitative Finance Curriculum
Part 1
Introduction to Algorithmic and Quantitative Trading
What is "Algorithmic" Trading?
Market Structures
Evolution: Algorithmic Trading trends and their impact on the markets
Technical Trading Strategies
Overview of Systematic Trading indicators in Technical Analysis
Trend following Strategies
Momentum based Strategies
Strategy Development and Back-testing
Ideation and Strategy Creation
Architecture of a back-testing System
Common Pitfalls (Look-ahead bias, survivorship bias etc.)
Money Management and Risk Management
Optimal Capital Allocation
Risk Management
Algorithm Trading Infrastructure Setup
Algorithm Trading Mechanics
Architectural design
Basic platform design and architectural setup
Algorithmic System Design and Implementation
Implementing Strategies
Order Management
Risk Management
Part 2
Options Trading Strategies
Options Pricing
Options Greeks
Options Trading Strategies
Machine Learning for Quantitative Trading Using Python
Introduction to Machine Learning
Regression Models
Optimization Methods
Analytical vs Numerical Optimization
Cost Functions for Regression
Cost Functions for Classification
Time Series Analysis Using Python
Auto Regressive Models (AR)
Moving Average Models (MA)
MA as basic model for stock data predictions
Deep Learning for Quantitative Trading Using Python
Introduction to Deep Learning – Artificial Neural Networks (ANN)
Feed Forward Neural Network (FFN)
Recurrent Neural Network (RNN)
Quantitative Trading Strategies
Introduction to Quantitative Trading
Quantitative Directional Strategies
Statistical Arbitrage Strategies
Algorithmic Execution Strategies
Execution Algorithms
Percentage of Volume (POV)
Volume Weighted Average Price (VWAP)
Time Weighted Average Price (TWAP)