Automated Trading Strategy

This long-term project involved defining and implementing a profitable automated trading strategy for NinjaTrader. Over the course of nearly a year, I dedicated significant time to researching, testing, and refining the approach, highlighting the complexity of creating a reliable, automatable system in the financial markets.

Overview

The project focused on developing a custom tool for strategy analysis and then automating a selected strategy. Starting with price data exported from TradingView, I created a Python-based analysis tool that allows users to define trading strategies and evaluate their performance through detailed statistics. After extensive iteration and review, I identified a strategy that met my criteria for profitability and automation. The final step was implementing this strategy in NinjaScript to enable fully automated execution in NinjaTrader.

Technologies Used

• Python for strategy analysis and backtesting
• TradingView for historical price data export
• NinjaScript (C# based) for strategy automation
• NinjaTrader platform for deployment and execution

Key Components

• Strategy Analysis Tool: A custom Python application where strategies can be defined and tested against historical data, generating performance metrics like win rate, risk-reward ratio, and drawdown.
• Data Processing: Importing and processing price data from TradingView to simulate real-market conditions.
• Strategy Refinement: Iterative testing and optimization based on statistical analysis to ensure robustness.
• Automation Implementation: Translating the refined strategy into NinjaScript code for live or simulated trading in NinjaTrader.

Key Outcomes

The project resulted in a fully automated trading strategy that performs consistently based on backtested data. It demonstrates my ability to handle complex data-driven problems, from analysis to implementation. Note: Trading involves significant risk, and this project is for personal use only. I am not a financial advisor, and no code or specific strategy details are shared to avoid any implication of financial advice.

For privacy and risk reasons, the code and detailed strategy are not publicly available.