Betting against beta
PortfolioAdvanced
Betting against beta, from Frazzini and Pedersen, longs low-beta assets and shorts high-beta assets, with leverage on the low-beta side and deleveraging on the high-beta side so the two legs have similar beta. The idea is that leverage constraints push investors toward high-beta assets and leave low-beta assets with a better risk-adjusted profile. It is a portfolio construction, not a timing oscillator.
Not investment advice. Nothing here is a recommendation to buy or sell anything. Backtests and historical studies are not guarantees, and a rule that worked in one sample can fail in the next. Trading can lose money. Links are for education, not endorsements. Do your own research.
- Rules
- Each month, estimate beta for each stock against the market using a published window. Rank by beta. Short the high-beta leg and long the low-beta leg, scaling so the portfolio is roughly beta-neutral. Apply a price and liquidity floor. Rebalance monthly. Do not substitute a low-volatility sort and call it the same book without checking the holdings.
- Where AI fits
- AI can estimate beta on past returns only, scale the legs to a target beta, and show the overlap with a low-volatility portfolio. It should include borrow and a leverage cap. Fitting the beta window to the full sample flatters the neutral book.
- Markets
- Liquid individual stocks, and in other asset classes only with a separate test. Needs a way to short and a leverage policy.
- Timeframes
- Monthly.
- Risks
- Low beta is not low risk in a deleveraging event. The short high-beta leg can rise faster than the model. Leverage on the long leg magnifies gaps. Beta estimates are unstable. The strategy can lose money for years and still match the paper's design. No result here is a promised premium.