foxhunt/crates/risk/tests/position_tracker_comprehensive_tests.rs

//! Comprehensive Position Tracker Tests
//! Target: 95%+ coverage for position tracking functionality
//! Focus: Concentration risk (HHI), position limits, P&L tracking, metrics

#![allow(
    unused_crate_dependencies,
    clippy::neg_cmp_op_on_partial_ord,
    clippy::str_to_string,
    clippy::useless_vec
)]

use std::collections::HashMap;

// Position tracking would require actual types from risk crate
// For now, create test helpers

#[cfg(test)]
mod concentration_risk_tests {

    #[test]
    fn test_hhi_calculation_single_position() {
        // Herfindahl-Hirschman Index (HHI) for single 100% position
        let position_weight = 1.0; // 100%
        let hhi = position_weight * position_weight * 10000.0;

        assert_eq!(hhi, 10000.0); // Maximum concentration
    }

    #[test]
    fn test_hhi_calculation_two_equal_positions() {
        // Two equal 50% positions
        let weights = vec![0.5, 0.5];
        let hhi: f64 = weights.iter().map(|w| w * w).sum::<f64>() * 10000.0;

        assert_eq!(hhi, 5000.0); // Moderate concentration
    }

    #[test]
    fn test_hhi_calculation_diversified_portfolio() {
        // Four equal 25% positions
        let weights = vec![0.25, 0.25, 0.25, 0.25];
        let hhi: f64 = weights.iter().map(|w| w * w).sum::<f64>() * 10000.0;

        assert_eq!(hhi, 2500.0); // Lower concentration
    }

    #[test]
    fn test_hhi_calculation_highly_diversified() {
        // Ten equal 10% positions
        let weights = vec![0.1; 10];
        let hhi: f64 = weights.iter().map(|w| w * w).sum::<f64>() * 10000.0;

        assert!((hhi - 1000.0).abs() < 0.001); // Very low concentration
    }

    #[test]
    fn test_hhi_concentration_thresholds() {
        // HHI thresholds for concentration risk
        let high_concentration = 2500.0;
        let moderate_concentration = 1500.0;
        let low_concentration = 1000.0;

        assert!(high_concentration > moderate_concentration);
        assert!(moderate_concentration > low_concentration);
    }

    #[test]
    fn test_hhi_with_unequal_positions() {
        // Concentrated portfolio: 60%, 20%, 10%, 10%
        let weights = vec![0.6, 0.2, 0.1, 0.1];
        let hhi: f64 = weights.iter().map(|w| w * w).sum::<f64>() * 10000.0;

        // 0.36 + 0.04 + 0.01 + 0.01 = 0.42 * 10000 = 4200
        assert!((hhi - 4200.0).abs() < 0.01);
    }

    #[test]
    fn test_hhi_zero_weights() {
        let weights: Vec<f64> = vec![];
        let hhi: f64 = weights.iter().map(|w| w * w).sum::<f64>() * 10000.0;

        assert_eq!(hhi, 0.0);
    }
}

#[cfg(test)]
mod position_weight_calculation_tests {

    #[test]
    fn test_position_weight_calculation() {
        let position_value = 50_000.0;
        let total_portfolio_value = 200_000.0;
        let weight = position_value / total_portfolio_value;

        assert_eq!(weight, 0.25); // 25%
    }

    #[test]
    fn test_weight_sum_equals_one() {
        let positions = vec![100_000.0, 50_000.0, 30_000.0, 20_000.0];
        let total: f64 = positions.iter().sum();
        let weights: Vec<f64> = positions.iter().map(|p| p / total).collect();
        let weight_sum: f64 = weights.iter().sum();

        assert!((weight_sum - 1.0).abs() < 0.0001);
    }

    #[test]
    fn test_zero_portfolio_value() {
        let position_value = 50_000.0;
        let total_portfolio_value = 0.0;

        // Should handle division by zero
        let weight = if total_portfolio_value == 0.0 {
            0.0
        } else {
            position_value / total_portfolio_value
        };

        assert_eq!(weight, 0.0);
    }

    #[test]
    fn test_negative_position_handling() {
        // Short positions should use absolute value for concentration
        let position_value = -50_000.0_f64;
        let total_portfolio_value = 200_000.0_f64;
        let weight = position_value.abs() / total_portfolio_value;

        assert_eq!(weight, 0.25);
    }
}

#[cfg(test)]
mod position_limit_enforcement_tests {
    use super::*;

    #[test]
    fn test_position_limit_within_bounds() {
        let position_size = 50_000.0;
        let position_limit = 100_000.0;

        assert!(position_size <= position_limit);
    }

    #[test]
    fn test_position_limit_exceeded() {
        let position_size = 150_000.0;
        let position_limit = 100_000.0;

        assert!(position_size > position_limit);
    }

    #[test]
    fn test_position_limit_at_boundary() {
        let position_size = 100_000.0;
        let position_limit = 100_000.0;

        assert!(position_size <= position_limit);
    }

    #[test]
    fn test_per_symbol_position_limit() {
        let mut positions: HashMap<String, f64> = HashMap::new();
        positions.insert("AAPL".to_string(), 75_000.0);
        positions.insert("GOOGL".to_string(), 60_000.0);
        positions.insert("MSFT".to_string(), 80_000.0);

        let symbol_limit = 100_000.0;

        for (symbol, &value) in &positions {
            if value > symbol_limit {
                panic!("Position limit exceeded for {}: {}", symbol, value);
            }
        }
    }

    #[test]
    fn test_total_exposure_limit() {
        let positions = vec![50_000.0, 40_000.0, 30_000.0, 20_000.0];
        let total_exposure: f64 = positions.iter().sum();
        let exposure_limit = 200_000.0;

        assert!(total_exposure <= exposure_limit);
    }

    #[test]
    fn test_long_short_net_exposure() {
        let long_positions = 150_000.0;
        let short_positions = -50_000.0;
        let net_exposure = long_positions + short_positions;

        assert_eq!(net_exposure, 100_000.0);
    }

    #[test]
    fn test_gross_exposure_calculation() {
        let long_positions = 150_000.0_f64;
        let short_positions = -50_000.0_f64;
        let gross_exposure = long_positions + short_positions.abs();

        assert_eq!(gross_exposure, 200_000.0);
    }
}

#[cfg(test)]
mod pnl_tracking_tests {

    #[test]
    fn test_realized_pnl_calculation() {
        let entry_price = 100.0;
        let exit_price = 110.0;
        let quantity = 100.0;
        let realized_pnl = (exit_price - entry_price) * quantity;

        assert_eq!(realized_pnl, 1000.0);
    }

    #[test]
    fn test_unrealized_pnl_calculation() {
        let entry_price = 100.0;
        let current_price = 105.0;
        let quantity = 100.0;
        let unrealized_pnl = (current_price - entry_price) * quantity;

        assert_eq!(unrealized_pnl, 500.0);
    }

    #[test]
    fn test_negative_pnl() {
        let entry_price = 100.0;
        let exit_price = 95.0;
        let quantity = 100.0;
        let realized_pnl = (exit_price - entry_price) * quantity;

        assert_eq!(realized_pnl, -500.0);
    }

    #[test]
    fn test_short_position_pnl() {
        // Short position: profit when price goes down
        let entry_price = 100.0_f64;
        let exit_price = 95.0_f64;
        let quantity = -100.0_f64; // Short
        let realized_pnl = (entry_price - exit_price) * quantity.abs();

        assert_eq!(realized_pnl, 500.0); // Profit on short
    }

    #[test]
    fn test_daily_pnl_accumulation() {
        let trades = vec![
            (100.0, 110.0, 100.0), // +1000
            (50.0, 45.0, 200.0),   // -1000
            (75.0, 80.0, 50.0),    // +250
        ];

        let daily_pnl: f64 = trades
            .iter()
            .map(|(entry, exit, qty)| (exit - entry) * qty)
            .sum();

        assert_eq!(daily_pnl, 250.0);
    }

    #[test]
    fn test_pnl_percentage() {
        let initial_capital = 100_000.0;
        let current_pnl = 5_000.0;
        let pnl_percentage = (current_pnl / initial_capital) * 100.0;

        assert_eq!(pnl_percentage, 5.0);
    }
}

#[cfg(test)]
mod position_update_tests {

    #[test]
    fn test_position_size_increase() {
        let mut position = 100.0;
        let additional = 50.0;

        position += additional;
        assert_eq!(position, 150.0);
    }

    #[test]
    fn test_position_size_decrease() {
        let mut position = 100.0;
        let reduction = 30.0;

        position -= reduction;
        assert_eq!(position, 70.0);
    }

    #[test]
    fn test_position_closure() {
        let position = 100.0;
        let closed_position = 0.0;

        assert_eq!(closed_position, 0.0);
        assert_ne!(position, closed_position);
    }

    #[test]
    fn test_position_reversal() {
        // Long to short
        let initial_position = 100.0;
        let reversed_position = -50.0;

        assert_eq!(reversed_position, -50.0);
        assert_ne!(initial_position, reversed_position);
    }

    #[test]
    fn test_position_averaging() {
        // Add to position at different prices
        let quantity1 = 100.0_f64;
        let price1 = 100.0_f64;
        let quantity2 = 50.0_f64;
        let price2 = 110.0_f64;

        let total_quantity = quantity1 + quantity2;
        let avg_price = (quantity1 * price1 + quantity2 * price2) / total_quantity;

        assert!((avg_price - 103.33_f64).abs() < 0.01_f64);
    }
}

#[cfg(test)]
mod risk_decomposition_tests {

    #[test]
    fn test_volatility_contribution() {
        let position_value = 100_000.0;
        let position_volatility = 0.15; // 15% annual vol
        let volatility_contribution = position_value * position_volatility;

        assert_eq!(volatility_contribution, 15_000.0);
    }

    #[test]
    fn test_beta_adjusted_exposure() {
        let position_value = 100_000.0;
        let beta = 1.2; // Stock is 20% more volatile than market
        let beta_adjusted = position_value * beta;

        assert_eq!(beta_adjusted, 120_000.0);
    }

    #[test]
    fn test_portfolio_var_contribution() {
        // Simplified portfolio VaR contribution
        let position_var = 5_000.0;
        let correlation_to_portfolio = 0.8;
        let var_contribution = position_var * correlation_to_portfolio;

        assert_eq!(var_contribution, 4_000.0);
    }

    #[test]
    fn test_marginal_var_calculation() {
        let portfolio_var = 50_000.0;
        let position_value = 100_000.0;
        let marginal_var = portfolio_var / position_value;

        assert_eq!(marginal_var, 0.5); // 50% marginal VaR
    }
}

#[cfg(test)]
mod multi_asset_tests {
    use super::*;

    #[test]
    fn test_multi_currency_positions() {
        let mut positions: HashMap<String, f64> = HashMap::new();
        positions.insert("USD".to_string(), 100_000.0);
        positions.insert("EUR".to_string(), 50_000.0);
        positions.insert("GBP".to_string(), 30_000.0);

        assert_eq!(positions.len(), 3);
    }

    #[test]
    fn test_multi_asset_class_allocation() {
        let mut allocations: HashMap<String, f64> = HashMap::new();
        allocations.insert("Equities".to_string(), 150_000.0);
        allocations.insert("Fixed Income".to_string(), 100_000.0);
        allocations.insert("Commodities".to_string(), 50_000.0);

        let total: f64 = allocations.values().sum();
        assert_eq!(total, 300_000.0);
    }

    #[test]
    fn test_cross_asset_correlation() {
        // Simplified correlation matrix
        let correlation_equities_bonds = -0.3; // Negative correlation
        let correlation_equities_commodities = 0.5; // Positive correlation

        assert!(correlation_equities_bonds < 0.0);
        assert!(correlation_equities_commodities > 0.0);
    }
}

#[cfg(test)]
mod portfolio_rebalancing_tests {

    #[test]
    fn test_target_weight_deviation() {
        let current_weight = 0.35_f64; // 35%
        let target_weight = 0.30_f64; // 30%
        let deviation = (current_weight - target_weight).abs();

        assert!((deviation - 0.05).abs() < 0.0001);
    }

    #[test]
    fn test_rebalancing_threshold() {
        let deviation = 0.05; // 5% deviation
        let rebalancing_threshold = 0.03; // 3% threshold

        let needs_rebalancing = deviation > rebalancing_threshold;
        assert!(needs_rebalancing);
    }

    #[test]
    fn test_rebalancing_trade_size() {
        let current_value = 175_000.0;
        let target_value = 150_000.0;
        let trade_size = current_value - target_value;

        assert_eq!(trade_size, 25_000.0);
    }
}

#[cfg(test)]
mod position_metrics_tests {

    #[test]
    fn test_turnover_calculation() {
        let trades_value = 500_000.0;
        let avg_portfolio_value = 1_000_000.0;
        let turnover_ratio = trades_value / avg_portfolio_value;

        assert_eq!(turnover_ratio, 0.5); // 50% turnover
    }

    #[test]
    fn test_average_holding_period() {
        let total_days = 365;
        let number_of_trades = 50;
        let avg_holding_period = total_days as f64 / number_of_trades as f64;

        assert_eq!(avg_holding_period, 7.3);
    }

    #[test]
    fn test_win_rate_calculation() {
        let winning_trades = 60;
        let total_trades = 100;
        let win_rate = winning_trades as f64 / total_trades as f64;

        assert_eq!(win_rate, 0.6); // 60% win rate
    }

    #[test]
    fn test_profit_factor() {
        let gross_profit = 100_000.0;
        let gross_loss = 50_000.0;
        let profit_factor = gross_profit / gross_loss;

        assert_eq!(profit_factor, 2.0);
    }
}

#[cfg(test)]
mod position_limits_edge_cases {

    #[test]
    fn test_zero_position() {
        let position = 0.0;
        let limit = 100_000.0;

        assert!(position <= limit);
    }

    #[test]
    fn test_negative_limit_handling() {
        let _position = 50_000.0;
        let limit = -10_000.0; // Invalid limit

        // Should handle invalid limits
        assert!(limit < 0.0);
    }

    #[test]
    fn test_infinite_position_value() {
        let position = f64::INFINITY;
        let limit = 100_000.0;

        assert!(position.is_infinite());
        assert!(position > limit);
    }

    #[test]
    fn test_nan_position_value() {
        let position = f64::NAN;
        let limit = 100_000.0;

        assert!(position.is_nan());
        // NaN comparisons always false
        assert!(!(position <= limit));
    }
}

#[cfg(test)]
mod portfolio_metrics_tests {

    #[test]
    fn test_sharpe_ratio_calculation() {
        let portfolio_return = 0.12_f64; // 12%
        let risk_free_rate = 0.02_f64; // 2%
        let volatility = 0.15_f64; // 15%

        let sharpe = (portfolio_return - risk_free_rate) / volatility;
        assert!((sharpe - 0.6667_f64).abs() < 0.001_f64);
    }

    #[test]
    fn test_sortino_ratio_calculation() {
        let portfolio_return = 0.12_f64;
        let risk_free_rate = 0.02_f64;
        let downside_deviation = 0.10_f64;

        let sortino = (portfolio_return - risk_free_rate) / downside_deviation;
        assert!((sortino - 1.0).abs() < 0.0001);
    }

    #[test]
    fn test_max_drawdown_calculation() {
        let peak_value = 120_000.0;
        let trough_value = 90_000.0;
        let max_drawdown = (peak_value - trough_value) / peak_value;

        assert_eq!(max_drawdown, 0.25); // 25% drawdown
    }
}