Model-Free Market Risk Hedging Using Crowding Networks
通过基金持仓网络分析股票拥挤度，构建无成本多空组合，该组合与市场负相关且具有正凸性，能对冲大小市场波动和尾部风险，无需期权或复杂优化。
Crowding is widely regarded as one of the most important risk factors in designing portfolio strategies. In this article, the authors analyze stock crowding using network analysis of fund holdings, which is used to compute crowding scores for stocks. These scores are used to construct costless long–short portfolios, computed in a distribution-free (model-free) way and without using any numerical optimization, with desirable properties of hedge portfolios. More specifically, these long–short portfolios provide protection for both small and large market price fluctuations because of their negative correlation with the market and positive convexity as a function of market returns. By adding their long–short portfolio to a baseline portfolio such as a traditional 60/40 portfolio, the authors show that their method provides an alternative way to hedge portfolio risk including tail risk, which does not require costly option-based strategies or complex numerical optimization. The total cost of such hedging amounts to the total cost of rebalancing the hedge portfolio.