System Design

Overview

An overview of the complete system and how each component interacts:

1. Strategy Editor: Allows users to create and modify trading strategies.
2. Backtesting Engine: Evaluate the performance of trading strategies using historical data.
3. Metrics Calculator: Provides performance metrics (and visualisations) to assess the effectiveness of strategies.
4. Trading Bots (Build-a-Bot): Executes trades in real-time based on the strategies.
5. Data Loader: Fetches historical and live market data

Components and Interactions

1. Strategy Editor

• Function: Allows users to define and modify trading strategies
• Output: Generate strategy configurations that can be used the backtesting engine and trading bots

2. Backtesting Engine

• Function: Simulates trades based on historical data to evaluate the performance of strategies
• Input: Accepts strategies from the strategy editor (or predefined/proprietary strategies offered by the editor)
• Output: Provides performance metrics and visualisations

3. Metrics Calculator (for both backtesting and paper/real live trading)

• Function: Calculates various performance metrics such as total return, Sharpe ratio, drawdown, etc
• Input: Receives trade and portfolio data from the backtesting engine
• Output: Provides a summary of performance metrics

4. Trading Bots (Build-a-Bot)

• Function: Executes trades in real-time using live market data
• Input: Accepts strategies from the strategy editor
• Output: Real-time trade execution and monitoring

5. Data Loader

• Function: Fetches historical data for backtesting and live data for trading bots
• Output: Provides data in a format suitable for strategies

Detailed Design

1. Strategy Editor Modules:

• User interface (UI) to define strategies (intuitive drag-and-drop interface and advanced code editor - maybe even write our own custom scripting language - great educational opportunity)
• Backend to save and export strategy configurations

2. Backtesting Engine Modules:

• Strategy Loader: Load strategy configurations
• Simulation Engine: Simulates trades based on historical data
• Metrics Calculator: Computes performance metrics
• Visualisation: Plots result

3. Metrics Calculator Modules (Embedded system of the backtesting engine)

• Performance Metrics: Calculates metrics like return, Sharpe ratio, etc
• Summary Report: Generates a report of performance metrics

4. Trading Bots Modules

• Live Data Loader: Fetches live market data
• Signal Generator: Generates buy/sell signals based on live data
• Trade Executor: Executes trade in real-time

5. Data Loader Modules

• Historical Data Loader: Fetches historical market data
• Live Data Loader: Fetches live market data

Integration Workflow

1. Create Strategy

• Users define strategies in the Strategy Editor
• Strategy configurations are saved and can be exported to the backtesting engine and trading bots

2. Backtest Strategy

• Strategy Loader loads the strategy configuration
• Data Loader fetches historical data
• Simulation Engine runs the strategy on historical data
• Metrics Calculator computes performance metrics
• Visualisation plots the backtest results
• Performance metrics and visualisations are presented to the user

3. Deploy Strategy to Trading Bot

• Strategy configuration is loaded to the trading bot
• Live Data Loader fetches real-time market data
• Signal Generator uses live data to generate buy/sell signals
• Trade Executor executes trades in real-time based on signals