Files
foxhunt/services/backtesting_service
jgrusewski e05189d904 Multi-Symbol Integration Complete - 5 Asset Classes, 8/8 Tests Passing
**Summary**: Expanded real data coverage from 2 to 5 diverse symbols across equity, commodity, fixed income, and currency markets. All integration tests passing with zero data quality violations.

**Symbols Added**:
- GC (Gold Futures): 781 bars, 30 days, $0.00
- ZN.FUT (10-Year Treasury): 28,935 bars, 30 days, $0.11
- 6E.FUT (Euro FX): 29,937 bars, 30 days, $0.11

**Existing Symbols**:
- ES.FUT (S&P 500 E-mini): 1,674 bars, 1 day
- NQ.FUT (NASDAQ E-mini): 1,593 bars, 1 day

**Test Results**: 8/8 passing (100%)
- test_load_all_symbols
- test_multi_symbol_loading
- test_asset_class_price_ranges
- test_repository_multi_symbol
- test_data_availability_multi_symbol
- test_multi_symbol_quality
- test_cross_asset_correlation
- test_multi_symbol_performance

**Data Quality**: 62,920 bars validated, 0 OHLCV violations
**Performance**: <100ms for all symbols, 1,514 bars/ms throughput
**Production Ready**: 4/5 symbols (80%) - ES, NQ, ZN, 6E approved

**Budget Tracking**:
- Total spent: $0.62 of $125.00 (0.5%)
- Remaining: $124.38 (99.5%)

**Files Modified**:
- services/backtesting_service/tests/dbn_multi_symbol_tests.rs (+315 lines)
- services/backtesting_service/tests/mock_repositories.rs (+12 lines)
- MULTI_SYMBOL_INTEGRATION_COMPLETE.md (+415 lines)
- CLAUDE.md (updated with multi-symbol status)

**Next Steps**: Moving Average Crossover backtesting with multi-symbol data

🎯 Foxhunt Real Data Integration - Agent 24 Multi-Symbol Expansion
2025-10-13 11:08:09 +02:00
..

Backtesting Service

Overview

The backtesting_service offers an independent and isolated environment for rigorously testing and validating trading strategies against historical market data. It provides a robust platform for simulating trading performance, analyzing strategy efficacy, and generating comprehensive performance reports before live deployment.

Features

  • Independent Backtesting Service: Operates autonomously, allowing for parallel and isolated strategy evaluations.
  • gRPC API for Backtest Execution: Exposes a clear API for submitting and managing backtesting jobs.
  • Strategy Testing and Validation: Enables comprehensive testing of various trading strategies under different market conditions.
  • Performance Reporting: Generates detailed reports including metrics like P&L, Sharpe ratio, drawdown, and win rate.
  • Data Replay Engine: Accurately replays historical market data, simulating real-world order book dynamics and trade execution.
  • Results Persistence: Stores backtesting results and reports for historical analysis and comparison.

gRPC API

The backtesting_service exposes a gRPC API for initiating and retrieving backtest results. Key endpoints include:

  • RunBacktest - Submit backtest configuration and strategy
  • GetBacktestResults - Retrieve results for completed backtests
  • ListAvailableStrategies - List registered strategies
  • GetBacktestReport - Get detailed performance report

Running the service

To run the backtesting_service binary:

cargo run --bin backtesting_service

Data Requirements

The service requires historical market data in Parquet format:

  • Data should be stored in the configured data directory
  • Supports tick data, order book snapshots, and OHLCV candles
  • Data must include instrument, timestamp, and price/quantity fields

Testing

To run the tests for the backtesting_service crate:

cargo test --package backtesting_service

Documentation

Comprehensive API documentation is available at docs.rs/backtesting_service.