At first sight, put options are pretty straight forward derivatives. The buyer purchases the right to sell a given asset for a predetermined price during a specified period of time (American Option) or on a specified date (European Option). In return for this price insurance, the option buyer pays a premium to the seller. In theory the option buyer can thereby effectively put a floor under the asset while retaining most of the upside.
Ideally a portfolio that is long the asset and the put option (protective put position)therefore has an asymmetric return profile with a significantly higher upside than downside beta. Unfortunately, the theoretical simplicity of protective puts conceals the actual complexity of their behavior in real markets.
Most importantly, two factors adversely affect the realized risk/return profile of protective put portfolios:
1) The volatility risk premium priced into traded options
2) The path dependency of put option's effectiveness
Especially the latter point is not easy to comprehend and tends to get underestimated by investors.
In a nutshell, I find that put options only work if their maturity profile closely matches the length of the drawdown against which it is supposed to protect the holder.
My study thereby confirms the findings of Israelov 2017 but goes beyond it in including the Covid crash as well as strategies on non US equity markets.
During longer drawdowns (such as the 2008 Financial Crisis) protective puts provide little downside protection. Even worse, due to their costliness, they perform extremely poorly during prolonged sidewards markets. In the worst case, investors don't just forgive returns (due to the option premium) but end up with higher drawdowns (risk) than observed for the respective long-only portfolio.
In the attached paper, I study the performance of protective put indices covering different markets. Beyond this, I model the historical returns of a protective put strategy on the S&P 500 using the Black-Scholes model. This enables scenario analysis, most importantly the simulation of strategies using options with different maturity profiles.
Luckily, the fOptions package on CRAN provides a very handy, highly efficient implementation of the option pricing model which allows the fast calculation of thousands of prices.
We are currently working on an interactive simulation module for the quantamental platform.