foxhunt/services/backtesting_service/tests/performance_metrics.rs

//! Comprehensive tests for performance metrics calculation
//!
//! Target Coverage: 70%+ for Sharpe ratio, drawdown, win rate, and all performance metrics

use anyhow::Result;
use chrono::{Duration, Utc};
use rust_decimal::Decimal;

mod mock_repositories;

use backtesting_service::performance::{PerformanceAnalyzer, PerformanceMetrics};
use backtesting_service::strategy_engine::{BacktestTrade, TradeSide};
use config::structures::BacktestingPerformanceConfig;

/// Helper to create a sample trade
fn create_trade(
    id: u32,
    symbol: &str,
    side: TradeSide,
    quantity: f64,
    entry_price: f64,
    exit_price: f64,
    entry_offset_days: i64,
    exit_offset_days: i64,
) -> BacktestTrade {
    let base_time = Utc::now() - Duration::days(100);
    let entry_time = base_time + Duration::days(entry_offset_days);
    let exit_time = base_time + Duration::days(exit_offset_days);

    let pnl = (exit_price - entry_price) * quantity;
    let return_percent = pnl / (entry_price * quantity);

    BacktestTrade {
        trade_id: format!("trade_{}", id),
        symbol: symbol.to_string(),
        side,
        quantity: Decimal::from_f64_retain(quantity).unwrap_or(Decimal::ZERO),
        entry_price: Decimal::from_f64_retain(entry_price).unwrap_or(Decimal::ZERO),
        exit_price: Decimal::from_f64_retain(exit_price).unwrap_or(Decimal::ZERO),
        entry_time,
        exit_time,
        pnl: Decimal::from_f64_retain(pnl).unwrap_or(Decimal::ZERO),
        return_percent: Decimal::from_f64_retain(return_percent).unwrap_or(Decimal::ZERO),
        entry_signal: "buy_signal".to_string(),
        exit_signal: "sell_signal".to_string(),
    }
}

/// Test basic performance metrics calculation
#[test]
fn test_basic_performance_metrics() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 150.0, 155.0, 0, 10), // +$500
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 155.0, 160.0, 10, 20), // +$500
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 160.0, 158.0, 20, 30), // -$200
    ];

    let initial_capital = 100000.0;
    let metrics = analyzer.calculate_metrics(&trades, initial_capital);

    // Total PnL should be $800
    assert!((metrics.total_return - 0.8).abs() < 0.01, "Total return should be 0.8%");
    
    // Should have 3 total trades
    assert_eq!(metrics.total_trades, 3);
    
    // Win rate should be 66.67% (2 wins, 1 loss)
    assert!((metrics.win_rate - 66.67).abs() < 0.1);
    
    // 2 winning trades, 1 losing trade
    assert_eq!(metrics.winning_trades, 2);
    assert_eq!(metrics.losing_trades, 1);

    Ok(())
}

/// Test Sharpe ratio calculation
#[test]
fn test_sharpe_ratio_calculation() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    // Create trades with consistent positive returns
    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 0, 1),   // +5%
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 1, 2),   // +5%
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 2, 3),   // +5%
        create_trade(4, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 3, 4),   // +5%
        create_trade(5, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 4, 5),   // +5%
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    // Sharpe ratio should be positive for consistent positive returns
    assert!(metrics.sharpe_ratio > 0.0, "Sharpe ratio should be positive");

    Ok(())
}

/// Test Sortino ratio calculation
#[test]
fn test_sortino_ratio_calculation() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    // Mix of wins and losses
    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 110.0, 0, 5),   // +10%
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 95.0, 5, 10),   // -5%
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 108.0, 10, 15), // +8%
        create_trade(4, "AAPL", TradeSide::Buy, 100.0, 100.0, 92.0, 15, 20),  // -8%
        create_trade(5, "AAPL", TradeSide::Buy, 100.0, 100.0, 112.0, 20, 25), // +12%
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    // Sortino ratio should be calculated (can be positive or negative depending on downside)
    assert!(metrics.sortino_ratio.is_finite(), "Sortino ratio should be finite");

    Ok(())
}

/// Test maximum drawdown calculation
#[test]
fn test_maximum_drawdown() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    // Trades that create a significant drawdown
    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 120.0, 0, 5),   // +20% (peak)
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 120.0, 110.0, 5, 10),  // -10%
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 110.0, 90.0, 10, 15),  // -20% (trough)
        create_trade(4, "AAPL", TradeSide::Buy, 100.0, 90.0, 115.0, 15, 20),  // +25% (recovery)
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    // Max drawdown should be significant
    assert!(metrics.max_drawdown > 0.0, "Max drawdown should be positive");
    assert!(metrics.max_drawdown < 100.0, "Max drawdown should be less than 100%");

    Ok(())
}

/// Test win rate calculation
#[test]
fn test_win_rate_calculation() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    // 7 wins, 3 losses = 70% win rate
    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 0, 1),   // Win
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 103.0, 1, 2),   // Win
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 95.0, 2, 3),    // Loss
        create_trade(4, "AAPL", TradeSide::Buy, 100.0, 100.0, 107.0, 3, 4),   // Win
        create_trade(5, "AAPL", TradeSide::Buy, 100.0, 100.0, 106.0, 4, 5),   // Win
        create_trade(6, "AAPL", TradeSide::Buy, 100.0, 100.0, 98.0, 5, 6),    // Loss
        create_trade(7, "AAPL", TradeSide::Buy, 100.0, 100.0, 104.0, 6, 7),   // Win
        create_trade(8, "AAPL", TradeSide::Buy, 100.0, 100.0, 102.0, 7, 8),   // Win
        create_trade(9, "AAPL", TradeSide::Buy, 100.0, 100.0, 97.0, 8, 9),    // Loss
        create_trade(10, "AAPL", TradeSide::Buy, 100.0, 100.0, 108.0, 9, 10), // Win
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    assert_eq!(metrics.total_trades, 10);
    assert_eq!(metrics.winning_trades, 7);
    assert_eq!(metrics.losing_trades, 3);
    assert!((metrics.win_rate - 70.0).abs() < 0.1, "Win rate should be 70%");

    Ok(())
}

/// Test profit factor calculation
#[test]
fn test_profit_factor() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    // Gross profit: $1000, Gross loss: $300 -> Profit factor: 3.33
    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 110.0, 0, 5),  // +$1000
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 97.0, 5, 10),  // -$300
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    assert!(metrics.profit_factor > 3.0 && metrics.profit_factor < 3.5, 
            "Profit factor should be ~3.33");

    Ok(())
}

/// Test average win and loss calculation
#[test]
fn test_average_win_loss() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 110.0, 0, 1),  // +$1000
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 106.0, 1, 2),  // +$600
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 95.0, 2, 3),   // -$500
        create_trade(4, "AAPL", TradeSide::Buy, 100.0, 100.0, 92.0, 3, 4),   // -$800
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    // Average win: ($1000 + $600) / 2 = $800
    assert!((metrics.avg_win - 800.0).abs() < 1.0, "Average win should be $800");
    
    // Average loss: -($500 + $800) / 2 = -$650
    assert!((metrics.avg_loss + 650.0).abs() < 1.0, "Average loss should be -$650");

    Ok(())
}

/// Test largest win and loss tracking
#[test]
fn test_largest_win_loss() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 0, 1),  // +$500
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 115.0, 1, 2),  // +$1500 (largest win)
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 95.0, 2, 3),   // -$500
        create_trade(4, "AAPL", TradeSide::Buy, 100.0, 100.0, 88.0, 3, 4),   // -$1200 (largest loss)
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    assert!((metrics.largest_win - 1500.0).abs() < 1.0, "Largest win should be $1500");
    assert!((metrics.largest_loss + 1200.0).abs() < 1.0, "Largest loss should be -$1200");

    Ok(())
}

/// Test Calmar ratio calculation
#[test]
fn test_calmar_ratio() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    // Create trades over a year with known drawdown
    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 120.0, 0, 90),   // +20%
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 120.0, 110.0, 90, 180), // -10%
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 110.0, 130.0, 180, 365), // +20%
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    // Calmar = Annualized Return / Max Drawdown
    assert!(metrics.calmar_ratio > 0.0, "Calmar ratio should be positive");

    Ok(())
}

/// Test VaR (Value at Risk) calculation
#[test]
fn test_var_calculation() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    // Mix of returns for VaR calculation
    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 0, 1),
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 103.0, 1, 2),
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 98.0, 2, 3),
        create_trade(4, "AAPL", TradeSide::Buy, 100.0, 100.0, 107.0, 3, 4),
        create_trade(5, "AAPL", TradeSide::Buy, 100.0, 100.0, 95.0, 4, 5),
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    assert!(metrics.var_95.is_some(), "VaR should be calculated");
    let var = metrics.var_95.unwrap();
    assert!(var < 0.0, "VaR should be negative (potential loss)");

    Ok(())
}

/// Test expected shortfall calculation
#[test]
fn test_expected_shortfall() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 0, 1),
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 92.0, 1, 2),
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 108.0, 2, 3),
        create_trade(4, "AAPL", TradeSide::Buy, 100.0, 100.0, 90.0, 3, 4),
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    assert!(metrics.expected_shortfall.is_some(), "Expected shortfall should be calculated");

    Ok(())
}

/// Test annualized return calculation
#[test]
fn test_annualized_return() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    // Trades over 6 months with 10% total return
    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 110.0, 0, 180), // +10% over 6 months
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    // Annualized return should be higher than 10% (compound effect)
    assert!(metrics.annualized_return > 10.0, "Annualized return should be > 10%");

    Ok(())
}

/// Test volatility calculation
#[test]
fn test_volatility_calculation() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    // High volatility trades
    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 120.0, 0, 1),  // +20%
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 85.0, 1, 2),   // -15%
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 115.0, 2, 3),  // +15%
        create_trade(4, "AAPL", TradeSide::Buy, 100.0, 100.0, 90.0, 3, 4),   // -10%
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    assert!(metrics.volatility > 0.0, "Volatility should be positive");

    Ok(())
}

/// Test edge case: no trades
#[test]
fn test_no_trades() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    let trades: Vec<BacktestTrade> = vec![];
    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    assert_eq!(metrics.total_trades, 0);
    assert_eq!(metrics.total_return, 0.0);
    assert_eq!(metrics.win_rate, 0.0);
    assert_eq!(metrics.sharpe_ratio, 0.0);

    Ok(())
}

/// Test edge case: all winning trades
#[test]
fn test_all_winning_trades() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 0, 1),
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 103.0, 1, 2),
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 107.0, 2, 3),
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    assert_eq!(metrics.win_rate, 100.0);
    assert_eq!(metrics.winning_trades, 3);
    assert_eq!(metrics.losing_trades, 0);
    assert!(metrics.profit_factor.is_infinite(), "Profit factor should be infinite with no losses");

    Ok(())
}

/// Test edge case: all losing trades
#[test]
fn test_all_losing_trades() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 95.0, 0, 1),
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 93.0, 1, 2),
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 92.0, 2, 3),
    ];

    let metrics = analyzer.calculate_metrics(&trades, 100000.0);

    assert_eq!(metrics.win_rate, 0.0);
    assert_eq!(metrics.winning_trades, 0);
    assert_eq!(metrics.losing_trades, 3);
    assert_eq!(metrics.profit_factor, 0.0, "Profit factor should be 0 with no wins");

    Ok(())
}

/// Test equity curve generation
#[test]
fn test_equity_curve_generation() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 0, 1),
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 110.0, 1, 2),
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 108.0, 2, 3),
    ];

    let initial_capital = 100000.0;
    let equity_curve = analyzer.generate_equity_curve(&trades, initial_capital);

    // Should have points for each trade + initial
    assert!(equity_curve.len() >= 4, "Equity curve should have at least 4 points");
    
    // First point should be initial capital
    assert!((equity_curve[0].equity - initial_capital).abs() < 0.01);
    
    // Drawdown at start should be 0
    assert_eq!(equity_curve[0].drawdown, 0.0);

    Ok(())
}

/// Test rolling metrics calculation
#[test]
fn test_rolling_metrics() -> Result<()> {
    let config = BacktestingPerformanceConfig::default();
    let analyzer = PerformanceAnalyzer::new(&config)?;

    let trades = vec![
        create_trade(1, "AAPL", TradeSide::Buy, 100.0, 100.0, 105.0, 0, 5),
        create_trade(2, "AAPL", TradeSide::Buy, 100.0, 100.0, 103.0, 5, 10),
        create_trade(3, "AAPL", TradeSide::Buy, 100.0, 100.0, 107.0, 10, 15),
        create_trade(4, "AAPL", TradeSide::Buy, 100.0, 100.0, 102.0, 15, 20),
        create_trade(5, "AAPL", TradeSide::Buy, 100.0, 100.0, 108.0, 20, 25),
    ];

    let rolling = analyzer.calculate_rolling_metrics(&trades, 10);

    assert!(!rolling.rolling_sharpe.is_empty(), "Rolling Sharpe should be calculated");
    assert!(!rolling.rolling_volatility.is_empty(), "Rolling volatility should be calculated");
    assert!(!rolling.rolling_returns.is_empty(), "Rolling returns should be calculated");

    Ok(())
}