Description
For aspiring Quant Traders looking to develop institutional-grade algorithmic trading strategies and build a career in quantitative trading.
- Trading Desk-Oriented Learning: Gain comprehensive, end-to-end exposure to market microstructure, strategy design, signal generation, execution algorithms, and trade performance analytics.
- Full-Stack Algorithmic Trading Development: Master the complete strategy development lifecycle — from ideation and programming to simulation and deployment — using industry-standard platforms and Python, complemented by intensive hands-on simulation labs.
Course Overview
The PGPAT program is structured into two parts, covering the fundamentals of algorithmic trading through to advanced quantitative trading, machine learning, and high-frequency trading.
Part 1 – Algorithmic Trading Fundamentals (Modules 301–311)
- Introduction to Algorithmic Trading: Trading concepts, market evolution, trading strategies, HFT/LFT, regulations, and ethical considerations.
- Algorithmic Trading Systems: Market dynamics, market microstructure, electronic trading, system architecture, and lifecycle.
- Understanding Financial Data: Financial data types, market data, OHLC prices, trading volumes, and market indices.
- Technical Trading Strategies: Technical indicators, trend-following, momentum, and mean-reversion strategies.
- Financial Data Handling: Financial data sources, APIs, data processing, and technical indicator calculations using Python.
- Algorithmic Trading System Development I: Backtesting architecture, performance evaluation, and best practices.
- Optimization Methods I: Fundamentals of deterministic and heuristic optimization techniques.
- Algorithmic Trading System Development II: Strategy optimization and performance improvement.
- Risk & Money Management: Financial and market risk, capital allocation, portfolio optimization, and Kelly Criterion.
- Algorithmic Trading System Development III: Live trading systems, order management, and error handling.
- Algorithmic Trading Infrastructure: Hardware, software, databases, market data feeds, exchange connectivity, and backup systems.
Part 2 – Advanced Quantitative Trading (Modules 312–320)
- Options Trading Strategies: Options fundamentals, pricing, Greeks, and market-neutral, directional, and arbitrage strategies.
- Optimization Methods II: Advanced deterministic and heuristic optimization techniques.
- Time Series Analysis for Trading: AR, MA, ARMA, ARIMA, EWMA, GARCH, HAR-RV, feature engineering, and walk-forward validation.
- Quantitative Trading Strategies: Directional trading, statistical arbitrage, pairs trading, index arbitrage, delta-neutral, and volatility strategies.
- Machine Learning for Trading: Supervised and unsupervised learning, regression, classification, and financial feature engineering.
- Deep Learning for Trading: ANN, CNN, RNN, LSTM, GRU, attention mechanisms, and hybrid models for financial forecasting.
- Reinforcement Learning for Trading: Q-Learning, DQN, policy gradient methods, and portfolio optimization using reinforcement learning.
- Sentiment Analysis for Trading: NLP, news and social media analysis, sentiment indicators, and trading signal integration.
- High-Frequency Trading & Execution Strategies: HFT concepts, execution algorithms (POV, VWAP, TWAP), and electronic market making.
Program Learning Outcome: Develop end-to-end algorithmic and quantitative trading capabilities, from financial data processing and strategy development to backtesting, optimization, risk management, and live deployment using advanced quantitative and AI-driven techniques.
The Post Graduate Program in Algorithmic Trading (PGPAT) by IIQF® is a career-oriented program designed to develop industry-ready Quant and Algo Traders. Led by experienced market practitioners, the program equips learners with practical skills to join financial institutions or establish independent proprietary trading desks.
As financial markets increasingly adopt automation, Algorithmic Trading uses computer programs, quantitative models, and mathematical techniques to identify profitable opportunities, develop trading strategies, and execute trades efficiently.
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