TY - JOUR T1 - Efficient Algorithms for Computing Risk<br/>Parity Portfolio Weights JF - The Journal of Investing SP - 150 LP - 163 DO - 10.3905/joi.2012.21.3.150 VL - 21 IS - 3 AU - Denis Chaves AU - Jason Hsu AU - Feifei Li AU - Omid Shakernia Y1 - 2012/08/31 UR - https://pm-research.com/content/21/3/150.abstract N2 - This article presents two simple algorithms to calculate the portfolio weights for a risk parity strategy, where asset class covariance information is appropriately taken into consideration to achieve “true” equal risk contribution. Previous implementations of risk parity either used a naïve 1/vol solution, which ignores asset class correlations, or computed “true” risk parity weights using relatively complicated optimizations to solve a quadratic minimization program with nonlinear constraints.The two iterative algorithms presented require only simple computations and quickly converge to the optimal solution. In addition to the technical contribution, the authors compute the parity in portfolio “risk allocation” using the Gini coefficient, and confirm that portfolio strategies with parity in “asset class allocation” can actually have high concentration in its “risk allocation.”TOPICS: Portfolio theory, statistical methods, portfolio theory ER -