Function price_with_svi 

pub fn price_with_svi(
    params: SVIParams,
    market_data: Vec<MarketDataRow>,
    fixed_params: FixedParameters,
) -> Vec<PricingResult>

Price European options using calibrated SVI model parameters.

This function takes pre-calibrated SVI parameters and applies them to price a set of options using the Black-Scholes framework with SVI-derived implied volatilities. The pricing is efficient and suitable for real-time applications.

Arguments

• params - Calibrated SVI parameters containing the time to expiration and model coefficients
• market_data - Option contracts to price (can be same or different from calibration data)
• fixed_params - Market parameters including risk-free rate and dividend yield

Returns

Vector of PricingResult containing option details, model prices, and implied volatilities. Results are sorted by strike price in ascending order.

Pricing Methodology

1. Log-moneyness calculation: k = ln(K/S) for each option
2. SVI implied volatility: σ(k) = sqrt(w(k)/t) where w(k) is SVI total variance
3. Black-Scholes pricing: European option price using SVI-derived volatility
4. Result compilation: Organized results with validation and error handling

Example

use surface_lib::{
    price_with_svi, MarketDataRow, FixedParameters,
    models::svi::svi_model::SVIParams
};

// Create SVI parameters (typically from calibration)
let svi_params = SVIParams {
    t: 0.0274,      // ~10 days to expiration
    a: 0.04,        // Base variance
    b: 0.2,         // Slope factor
    rho: -0.3,      // Negative skew
    m: 0.0,         // ATM at log-moneyness 0
    sigma: 0.2,     // Curvature
};

// Market parameters
let fixed_params = FixedParameters {
    r: 0.02,        // 2% risk-free rate
    q: 0.0,         // No dividend yield
};

// Price options
let pricing_results = price_with_svi(svi_params, market_data, fixed_params);

for result in &pricing_results {
    println!("Strike {}: Price ${:.2}, IV {:.1}%",
             result.strike_price,
             result.model_price,
             result.model_iv * 100.0);
}

Error Handling

The function uses robust error handling:

• Invalid pricing results default to zero price and implied volatility
• Time mismatches between SVI parameters and market data are handled gracefully
• Non-finite or negative volatilities are caught and logged

Performance Notes

• Pricing scales linearly with the number of options
• Typical performance: 10,000+ options per second on modern hardware
• Memory usage is minimal with in-place calculations