Model-Free Market Risk Hedging Using Crowding Networks

ArXiv ID: 2306.08105 “View on arXiv”

Authors: Unknown

Abstract

Crowding is widely regarded as one of the most important risk factors in designing portfolio strategies. In this paper, we 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, due to their negative correlation with the market and positive convexity as a function of market returns. By adding our long-short portfolio to a baseline portfolio such as a traditional 60/40 portfolio, our 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.

Keywords: Crowding, Network Analysis, Portfolio Hedging, Risk Factors, Long-Short Strategy, Equities

Complexity vs Empirical Score

• Math Complexity: 4.0/10
• Empirical Rigor: 8.0/10
• Quadrant: Street Traders
• Why: The paper focuses on practical network analysis and portfolio construction with empirical backtesting on real data, but the mathematics (primarily graph centrality measures and regression) is relatively accessible compared to advanced stochastic calculus or machine learning papers.

  flowchart TD
    A["Research Goal: Model-Free Hedge for Market Risk<br>Using Crowding Networks"] --> B{"Methodology"}
    B --> C["Data: Fund Holdings<br>Stock Prices"]
    C --> D["Network Construction"]
    D --> E["Crowding Score<br>Computation"]
    E --> F{"Portfolio Construction"}
    F --> G["Long-Short Hedge<br>Portfolio"]
    G --> H["Outcomes: Hedge added to 60/40<br>Model-free, No Options, Low Cost"]
    subgraph Computational Process
        direction LR
        D --> E --> F --> G
    end