论文标题
改进了解决风险平价投资组合的迭代方法
Improved iterative methods for solving risk parity portfolio
论文作者
论文摘要
风险奇偶校验，也称为同等风险贡献，最近作为投资组合分配方法引起了人们的关注。但是，解决投资组合权重必须采用数值方法，因为没有分析解决方案。这项研究改善了两种现有的迭代方法：周期性坐标下降（CCD）和牛顿方法。我们通过使用相关矩阵简化公式并施加额外的重新缩放步骤来增强CCD方法。我们还建议通过牛顿方法的CCD方法启发的改进的初始猜测。数值实验表明，改进的CCD方法的表现最好，并且比原始CCD方法快三倍，节省了超过40％的迭代。
Risk parity, also known as equal risk contribution, has recently gained increasing attention as a portfolio allocation method. However, solving portfolio weights must resort to numerical methods as the analytic solution is not available. This study improves two existing iterative methods: the cyclical coordinate descent (CCD) and Newton methods. We enhance the CCD method by simplifying the formulation using a correlation matrix and imposing an additional rescaling step. We also suggest an improved initial guess inspired by the CCD method for the Newton method. Numerical experiments show that the improved CCD method performs the best and is approximately three times faster than the original CCD method, saving more than 40% of the iterations.
