Overview
Evaluates trading strategies against live or simulated market data and generates order signals. Shares a common strategy framework with the Backtesting Engine.
Navigation
Architecture
- contains IStrategy Design
- contains MomentumStrategy Design
- contains SmaCrossoverStrategy Design
Contracts
- contains Strategy Interface Interface
Documents
Strategy Engine
Responsibilities
The Strategy Engine runs pluggable trading strategies against incoming market data and publishes trading signals.
- Subscribes to MarketTick events on the EventBus
- Runs all registered IStrategy implementations against each tick
- Publishes Signal events (BUY/SELL) when a strategy fires
- Supports backtest mode: feed ticks directly via
run_backtest(ticks)without publishing to the bus
Interface
| Method | Description |
|---|---|
add_strategy(strategy) |
Register a new IStrategy at runtime |
remove_strategy(strategy_id) |
Remove a strategy by ID |
run_backtest(ticks) |
Run all strategies against a tick sequence; returns list of Signals |
strategies |
List of registered strategy IDs |
signals |
All signals generated since creation |
Built-in Strategies
| Strategy | Logic |
|---|---|
MomentumStrategy |
BUY/SELL when last price deviates from rolling average by > threshold |
SmaCrossoverStrategy |
BUY when fast SMA crosses above slow SMA; SELL on cross below |
IStrategy Protocol
class IStrategy(Protocol):
@property
def strategy_id(self) -> str: ...
def evaluate(self, tick: MarketTick) -> Signal | None: ...Event Flow
MarketTick → StrategyEngine.on_tick() → IStrategy.evaluate() → Signal (published)Design Notes
- Strategies are stateful per-symbol (maintain rolling price windows)
- Multiple strategies can be registered simultaneously
- Backtest mode does not publish to the bus — safe for offline analysis
- Source:
src/components/strategy_engine.py