import { PortfolioOptimizationOptions } from '../schemas/PortfolioOptimizationOptionsSchema';
import { PortfolioOptimizationResult } from '../schemas/PortfolioOptimizationResultSchema';
/**
 * Calculate Markowitz Mean-Variance Portfolio Optimization
 *
 * Implements the classic Markowitz portfolio theory for optimal asset allocation.
 * Supports three optimization objectives:
 * 1. Minimum Variance Portfolio
 * 2. Maximum Sharpe Ratio Portfolio
 * 3. Target Return Portfolio
 *
 * Mathematical Framework:
 * - Objective: min w^T Σ w (variance) or max (w^T μ - rf) / √(w^T Σ w) (Sharpe)
 * - Constraints: w^T 1 = 1 (weights sum to 1), w_min ≤ w ≤ w_max
 *
 * @param options - Expected returns, covariance matrix, constraints, and optimization target
 * @returns Optimal portfolio weights and performance metrics
 *
 * @example
 * ```typescript
 * const result = calculatePortfolioOptimization({
 *   expectedReturns: [0.08, 0.12, 0.06],
 *   covarianceMatrix: [
 *     [0.04, 0.02, 0.01],
 *     [0.02, 0.09, 0.03],
 *     [0.01, 0.03, 0.02]
 *   ],
 *   riskFreeRate: 0.03,
 *   method: 'maximumSharpe'
 * });
 * ```
 */
export declare function calculatePortfolioOptimization(options: PortfolioOptimizationOptions): PortfolioOptimizationResult;