Beta Hedging with Regression and Market Neutral Portfolios

Summary

This overview explains beta as an asset’s estimated sensitivity to one or more return factors, usually a market index, using linear regression. It describes hedging as taking offsetting positions to reduce an identified risk exposure, then outlines arbitrage, alpha, and market neutral approaches. For a portfolio with market exposure, it proposes an index short sized in proportion to the portfolio’s beta and value, with the aim of leaving returns driven primarily by alpha.

The discussion gives conceptual examples involving individual stocks and benchmark indices, but the formulas and empirical illustrations are omitted from the text. It does not provide evidence that a hedge will eliminate market risk or that a neutral strategy will produce stable returns. Its main caveat is that estimated beta changes over time, so a hedge based on past regression estimates may be imperfect and may not materially reduce exposure in practice.

Key ideas

• Regression estimates an asset’s exposure to market or other return factors.
• Beta commonly refers to sensitivity to a chosen benchmark index.
• A market hedge can use a short index position sized to offset the portfolio’s estimated beta exposure.
• Market neutral portfolios seek returns from selection alpha while reducing market direction exposure.
• Beta estimates can shift over time, making hedges imperfect.

Tags

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