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Coding Black Females - Trading Algorithm Project by Toluwanimi Oladejo
This project showcases a trading algorithm designed to analyse market data, execute trades based on a Simple Moving Average (SMA), and manage risk with a stop-loss mechanism. The algorithm is structured to adapt to varied market conditions, ensuring stability and profitability.
Key Achievements
- SMA Calculation: Uses recent bid prices to determine optimal trade conditions.
- Buy and Sell Logic: Executes buy orders when conditions are favourable and sells to meet profit targets.
- Risk Management: Incorporates a stop-loss feature to mitigate losses.
- Exit Control: Limits orders to maintain system stability.
Features and Functionality
- SMA-Based Trading: Calculates SMA for decision-making.
- Order Management: Implements buy, sell, and stop-loss mechanisms.
- Backtesting: Validates performance under simulated market conditions.
- Performance Logging: Tracks execution times for ongoing optimisation.
UI Front-End Exercise
I developed a Depth of Market (DOM) UI view using React and TypeScript, enhancing market data visualisation. Although not yet integrated with the trading algo itself, this component lays the groundwork for a dynamic interface.
Future Improvements
- Unit test refinements for sell and stop-loss logic.
- UI integration with the algorithm for real-time monitoring.
- Fine-tuning of thresholds for improved performance.
Link to Full Project README
(https://github.com/Loiseu8/trading-algorithm-assessment/blob/main/algo-exercise/README.md)
