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Cross-section without factors: a string model for expected returns.

Walter Distaso1, Antonio Mele2, Grigory Vilkov3

  • 1Imperial College, South Kensington Campus, London SW7 2AZ, United Kingdom.

Quantitative Finance
|January 20, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new asset pricing model where returns are driven by asset correlations, not just common factors. Big stocks act as hedges, reducing risk and lowering the correlation premium.

Keywords:
Arbitrage pricingBig stocksCorrelation premiumCross-section of returnsImplied correlationPremium for correlation riskString models

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Area of Science:

  • Quantitative Finance
  • Asset Pricing Theory
  • Financial Econometrics

Background:

  • Traditional asset pricing models often rely on common factors to explain expected returns.
  • The need for alternative models that capture complex inter-asset relationships is growing.
  • Existing models may not fully account for the interconnectedness of asset returns.

Purpose of the Study:

  • To develop a novel asset pricing model based on a "string" concept, linking asset returns through correlations.
  • To investigate the role of granular exposure and correlation premiums in asset pricing.
  • To identify unique properties of large stocks within this new framework.

Main Methods:

  • Formulation of a new asset pricing model incorporating a "string" of asset returns.
  • Application of no-arbitrage restrictions to define expected returns based on cross-asset exposures.
  • Analysis of the model's predictions for large stocks and their hedging properties.

Main Results:

  • The proposed "string" model posits that expected returns are influenced by an asset's exposure to all other asset returns, termed a correlation premium.
  • Large stocks exhibit higher connectivity during market downturns.
  • These large stocks function as correlation hedges, negatively contributing to the correlation premium.

Conclusions:

  • The "string" model offers a new perspective on asset pricing, emphasizing inter-asset correlations.
  • Large stocks play a crucial role as hedges, potentially reducing portfolio risk.
  • The model demonstrates competitive performance compared to established linear factor models.