Risk Parity: Inverse-Volatility Weights and Portfolio Trade-Offs

Summary

The document introduces risk parity as a portfolio allocation method that sets weights according to asset risk rather than equal capital or expected returns. Its basic procedure estimates each asset’s volatility, assigns larger weights to lower-volatility assets using inverse volatility, and normalizes the weights to fully allocate capital. A worked example using five stocks illustrates the calculation and contrasts it with equal weighting and mean-variance optimization. The article also names alternatives such as hierarchical risk parity, minimum variance, and maximum diversification.

The text reports a comparison of risk parity with an equal-weighted portfolio of Dow Jones 30 stocks, stating that the risk parity example had higher annualized return, lower volatility, a higher Sharpe ratio, and a smaller maximum drawdown. It cautions that the method relies on historical volatility, ignores correlations in its simple form, can overweight lower-risk assets, and may require costly rebalancing. The reported comparison is not enough to establish performance across other periods or markets, and the method may lag in directional markets favoring higher-risk assets.

Key ideas

• Risk parity aims to balance portfolio risk contributions rather than allocate equal amounts of capital.
• The basic inverse-volatility method gives higher weights to lower-volatility assets and normalizes weights to a full allocation.
• The document contrasts risk parity with equal weighting and mean-variance optimization and lists other allocation methods.
• Its Dow Jones 30 comparison reports stronger return and risk metrics for risk parity than equal weighting.
• Historical volatility, ignored correlations, rebalancing costs, and changing market conditions limit the method.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.