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风险平价模型，使用Newton迭代法计算等风险贡献(ERC)组合与杠杆调整。适用于风险预算与组合风控的。权重计算为简化数值求解，未考虑资产相关性动态变化与杠杆约束，不适用于实盘风控，不构成投资建议。
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| name | risk-parity |
| description | 风险平价模型，使用Newton迭代法计算等风险贡献(ERC)组合与杠杆调整。适用于风险预算与组合风控的。权重计算为简化数值求解，未考虑资产相关性动态变化与杠杆约束，不适用于实盘风控，不构成投资建议。 |
| version | 1.0.0 |
| author | wangyi |
风险平价策略工具，计算等风险贡献（ERC）组合，使用 Newton 迭代法求解权重，仅使用 Python 标准库。
📌 说明：本工具基于简化模型实现，仅使用 Python 标准库。结果仅供学习参考，不构成投资建议。
portfolio_volatility(weights, cov_matrix)计算组合波动率。 必填: weights, cov_matrix
marginal_risk_contributions(weights, cov_matrix)计算各资产的边际风险贡献。 必填: weights, cov_matrix
risk_contributions(weights, cov_matrix)计算各资产的风险贡献。 必填: weights, cov_matrix
erc_objective(weights, cov_matrix)ERC目标函数：风险贡献差异的平方和。 必填: weights, cov_matrix
erc_gradient(weights, cov_matrix)计算ERC目标函数的数值梯度。 必填: weights, cov_matrix
solve_erc_newton(cov_matrix, max_iter=1000, tolerance=1e-10, initial_weights=None)使用Newton迭代法求解等风险贡献组合。 必填: cov_matrix
solve_erc_iterative(cov_matrix, max_iter=10000, tolerance=1e-08)使用迭代比例调整法求解ERC组合。 必填: cov_matrix
leverage_adjust(weights, cov_matrix, target_volatility)对风险平价组合进行杠杆调整以达到目标波动率。 必填: weights, cov_matrix, target_volatility
risk_pity_optimize(cov_matrix, method='newton', target_risk=None)统一风险平价优化接口。 必填: cov_matrix
python scripts/main.py \
--cov-matrix <cov_matrix> \
--method <method> \
--target-risk <target_risk> \
--initial-weights <initial_weights> \
--max-iter <max_iter> \
--target-volatility <target_volatility> \
--tolerance <tolerance> \
--weights <weights>