import { BacktestEngine } from '@neural-trader/backtesting';
import type { BacktestConfig, Signal } from '@neural-trader/core';

// Configure backtest
const config: BacktestConfig = {
  initialCapital: 100000,
  startDate: '2024-01-01',
  endDate: '2024-12-31',
  commission: 0.001,        // 0.1% per trade
  slippage: 0.0005,         // 0.05% slippage
  useMarkToMarket: true
};

// Create engine
const engine = new BacktestEngine(config);

// Generate signals (from your strategy)
const signals: Signal[] = [
  {
    id: '1',
    strategyId: 'momentum-1',
    symbol: 'AAPL',
    direction: 'long',
    confidence: 0.85,
    entryPrice: 150.00,
    stopLoss: 145.00,
    takeProfit: 160.00,
    reasoning: 'Strong momentum breakout',
    timestampNs: Date.now() * 1_000_000
  }
  // ... more signals
];

// Run backtest
const result = await engine.run(signals, 'path/to/market-data.csv');

// Analyze results
console.log('Performance Metrics:');
console.log(`Total Return: ${(result.metrics.totalReturn * 100).toFixed(2)}%`);
console.log(`Sharpe Ratio: ${result.metrics.sharpeRatio.toFixed(2)}`);
console.log(`Max Drawdown: ${(result.metrics.maxDrawdown * 100).toFixed(2)}%`);
console.log(`Win Rate: ${(result.metrics.winRate * 100).toFixed(1)}%`);
console.log(`Profit Factor: ${result.metrics.profitFactor.toFixed(2)}`);
console.log(`Total Trades: ${result.metrics.totalTrades}`);

// Export trades to CSV
const csv = engine.exportTradesCsv(result.trades);

class BacktestEngine {
  constructor(config: BacktestConfig);

  // Run backtest with strategy signals and market data
  run(signals: Signal[], marketDataPath: string): Promise<BacktestResult>;

  // Calculate performance metrics from equity curve
  calculateMetrics(equityCurve: number[]): BacktestMetrics;

  // Export trades to CSV format
  exportTradesCsv(trades: Trade[]): string;
}

interface BacktestResult {
  metrics: BacktestMetrics;  // Performance statistics
  trades: Trade[];           // All executed trades
  equityCurve: number[];     // Portfolio value over time
  dates: string[];           // Corresponding timestamps
}

interface BacktestMetrics {
  totalReturn: number;       // Total return as decimal (0.15 = 15%)
  annualReturn: number;      // Annualized return
  sharpeRatio: number;       // Risk-adjusted return
  sortinoRatio: number;      // Downside risk-adjusted return
  maxDrawdown: number;       // Maximum drawdown
  winRate: number;           // Winning trades / total trades
  profitFactor: number;      // Gross profit / gross loss
  totalTrades: number;       // Number of trades
  winningTrades: number;     // Number of winning trades
  losingTrades: number;      // Number of losing trades
  avgWin: number;            // Average winning trade
  avgLoss: number;           // Average losing trade
  largestWin: number;        // Largest winning trade
  largestLoss: number;       // Largest losing trade
  finalEquity: number;       // Final portfolio value
}