Course Overview: This course, led by trading systems expert Sujith S Nadig, focuses on the development and implementation of non-discretionary trading systems. Ideal for traders looking to remove emotional bias and enhance consistency, this course provides a step-by-step guide to building, testing, and deploying automated trading systems.

What the Course Offers:

1. Introduction to Non-Discretionary Trading:
   • Understanding the principles of non-discretionary trading.
   • Benefits of automated trading systems.
   • Differences between discretionary and non-discretionary trading approaches.
2. Foundations of Trading System Development:
   • Key components of a robust trading system.
   • Defining clear and objective trading rules.
   • Importance of data quality and accuracy in system development.
3. Selecting and Analyzing Market Data:
   • Types of data required for building trading systems.
   • Sources for reliable market data.
   • Techniques for data cleaning and preprocessing.
4. Designing Trading Algorithms:
   • Step-by-step guide to creating trading algorithms.
   • Incorporating technical indicators and signals.
   • Developing entry and exit rules based on quantitative analysis.
5. Backtesting Trading Systems:
   • Importance of backtesting in system development.
   • Setting up and running backtests using historical data.
   • Analyzing backtest results for system optimization.
6. Risk Management in Automated Trading:
   • Implementing risk management rules within the trading system.
   • Setting stop-loss, take-profit, and position-sizing parameters.
   • Techniques for managing drawdowns and maximizing returns.
7. Optimization and Robustness Testing:
   • Strategies for optimizing trading algorithms.
   • Avoiding overfitting and ensuring system robustness.
   • Conducting walk-forward analysis and Monte Carlo simulations.
8. Deploying and Monitoring Trading Systems:
   • Steps for deploying automated trading systems in live markets.
   • Tools and platforms for system deployment.
   • Monitoring and maintaining system performance over time.
9. Advanced System Development Techniques:
   • Integrating machine learning and AI into trading systems.
   • Developing multi-strategy and multi-asset systems.
   • Exploring high-frequency trading and low-latency execution.
10. Real-World Applications and Case Studies:
    • Practical examples of successful non-discretionary trading systems.
    • Detailed case studies highlighting system development and performance.
    • Lessons learned from real-world implementations.
11. Tools and Resources:
    • Introduction to software and platforms for building and testing trading systems.
    • Access to code libraries, frameworks, and other resources.
    • Recommendations for further learning and staying updated with industry trends.
12. Interactive Learning and Community Engagement:
    • Participation in live webinars and Q&A sessions with Sujith S Nadig.
    • Engaging with a community of traders and system developers for discussions and support.
    • Ongoing updates and supplementary materials based on market developments.

This course equips traders with the knowledge and skills to develop and implement non-discretionary trading systems, enhancing their trading consistency and performance through automation and objective decision-making.