The equity risk premium refers to the excess return that investing in the stock market provides over a risk-free rate, typically represented by government bonds. It compensates investors for taking on the higher risk associated with equities. Estimating the equity risk premium is essential for asset allocation, valuation models, and long-term return expectations in portfolio management.
Reference [1] investigates the use of stock options to capitalize on the equity risk premium. It studied all the U.S. optionable stocks. The study first utilized a machine learning method to estimate expected stock returns (ESR). Then, each month, it sorted at-the-money call options by the ESR of the underlying stock and constructed a long-short portfolio: buying calls on high-ESR stocks and selling calls on low-ESR stocks, holding these positions to maturity. The authors pointed out,
We study via a simple test whether options are a useful tool to harvest the risk premia of the underlying stocks. We introduce a trading strategy that buys calls on stocks with high expected stock returns, and sells calls on stocks with low expected stock returns, and vice versa for puts. We find that these two trading strategies deliver surprisingly low returns, which do not even outperform a naive investment that simply buys all available call or put options, i.e., the “market”…
This finding has two important implications. First, it shows that options are not a useful tool to extract stock risk premia. Second, it implies that option prices are not independent of the underlying’s expected return—violating a central insight of option pricing theory. To corroborate our findings, we apply machine learning techniques to predict expected option returns and option prices. We find that variables predicting stock returns well, do barely predict option returns, but explain option prices well. Moreover, if we use our direct estimate of the expected stock return as a predictor variable, we again find that it predicts price levels well, but not returns.
Finally, we find violations of put-call-parity consistent with our result. In particular, the level of expected stock return is a strong predictor of the implied volatility spread between a pair of calls and puts. This suggest that options are priced such that they largely offset the effects of the underlying’s expected return on the expected option returns.
In short, the article concluded that,
- Options are not effective instruments for capturing stock risk premia,
- Option prices are influenced by the expected returns of the underlying stocks, which challenges a core assumption of traditional option pricing theory.
These findings are interesting and somewhat surprising. However, we note that they apply only to cross-sectional returns. As observed by the authors, if one has a directional bias, then simply buying calls can deliver respectable risk-adjusted returns. Hence, in the time-series momentum space, having a directional edge could be augmented by using options.
Let us know what you think in the comments below or in the discussion forum.
References
[1] d'Avernas, Adrien and Schlag, Christian and Sichert, Tobias and Sichert, Tobias and Waibel, Martin and Wang, Chunjie, Betting on Stocks with Options?, Swedish House of Finance Research Paper No. 2025-03 https://ift.tt/Ap1GTJQ
Originally Published Here: Harvesting the Equity Risk Premia Through Options
source https://harbourfronts.com/harvesting-the-equity-risk-premia-through-options/
