On April 9, QuantInsti hosted a highly anticipated live workshop focused on moving from discretionary ideas to systematic, rule-based decision-making.If you missed the live session or just want to re-watch the deep dive into how professionals build institutional-level trading systems you can watch the full recording below.
[INSERT YOUTUBE/VIDEO PLAYER HERE]
Here is a quick breakdown of what our expert panel covered during the two-hour intensive session.
Part 1: Python for Trading Using AI
The first half of the workshop explored how coding, data, and automation come together to power algorithmic trading systems used by professionals.Key highlights included:
- Vibe Coding & Prompt Engineering: How modern traders are using AI tools and prompt engineering to generate, refine, and drastically accelerate Python code development for trading strategies.
- The Industry Standard: Why Python has cemented itself as the essential tool for quantitative trading, and how even basic Python knowledge unlocks powerful capabilities.
- The Complete Algo Trading Pipeline: A walkthrough of the full journey of a strategy from idea generation and strategy logic to backtesting, optimization, and live trade execution.
Part 2: Risk Management for Options TradingMost retail traders focus entirely on finding the perfect strategy, but professionals know that structure, data, and risk are what actually matter.The second session tackled this critical component:
- How professional traders systematically structure options strategies.
- The most common pitfalls in options trading and how to avoid them.
- Why risk management is the real edge in algorithmic trading.Insights from Industry ExpertsThe session was led by three veteran quantitative practitioners who shared live insights and examples from their institutional trading experience:
- Dr. Gaurav Raizada (Co-Founder, iRage & EPAT Faculty) shared his deep expertise in market microstructure and building robust, high-frequency trading systems.
- Vivek Krishnamoorthy (Head of Content & Research, QuantInsti) broke down the essentials of Python for data analysis, time-series analysis, and backtesting.
- Dr. Kelvin Foo (Founder & Managing Partner, Elemen79) brought in his extensive background in quant methods, risk management, and AI applications in financial markets.
Ready to Take the Next Step?
This workshop provided a practical introduction to the core concepts taught in QuantInsti’s flagship Executive Programme In Algorithmic Trading (EPAT).
If you are serious about building a career or long-term expertise in systematic trading, EPAT provides the comprehensive roadmap. You will learn to develop and deploy automated strategies, work with advanced statistical models, and earn a globally recognised certification.
[Link to explore the EPAT Programme]