Is There Predictive Power In The Option-Implied Volatility Smirk?

Apparently, the answer is yes. Xiaoyan Zhang (of Cornell), Rui Zhao (of Blackrock Inc.), and Yuhang Xing (of Rice University) recently conducted a study titled "What Does Individual Option Volatility Smirk Tell Us about Future Equity Returns?" Here's their abstract (emphasis mine):

The shape of the volatility smirks has significant cross-sectional predictive power for future equity returns. Stocks exhibiting the steepest smirks in their traded options underperform stocks with the least pronounced volatility smirks in their options by around 15% per year on a risk-adjusted basis. This predictability persists for at least six months, and firms with steepest volatility smirks are those experiencing the worst earnings shocks in the following quarter. The results are consistent with the notion that informed traders with negative news prefer to buy out-of-the-money put options, and that the equity market is slow in incorporating the information embedded in volatility smirks.

Basically, they calculate the "volatility smirk" (the difference between the implied volatility for At-The-Money (ATM) calls and Out-of-The-Money (OTM) puts) for individual stocks. They then sort firms into portfolios based on deciles of the smirk, and compare returns for the various portfolios (or for "hedge portfolios" constructed by shorting the "high smirk" decile and going long the "low smirk" decile) . The logic for this approach is the hypothesis that informed traders with negative news will choose to buy OTM puts, thereby causing a divergence in the IV of the puts vs for the call.

All in all, a pretty cool paper showing how information flows across markets. Given some work I'm doing with options data, I found it to be particularly timely.

Read the whole thing here.

HT: CXO Advisory Group

Options and The Volatility Risk Premium

Classical mean-variance portfolio theory assumes that investors are risk-averse. Here's a paper that examines the "volatility risk" premium using options data, titled "The Price of Market Voilatility Risk", by Jefferson Duarte and Christopher Jones:

We analyze the volatility risk premium by applying a modified two-pass Fama-MacBeth procedure to the returns of a large cross section of the returns of options on individual equities. Our results provide strong evidence of a volatility risk premium that is increasing in the level of overall market volatility. This risk premium provides compensation for risk stemming both from the characteristics of the option contract and the riskiness of the underlying equity. We also show with a large scale Monte Carlo simulation that measurement error in option prices and violations of arbitrage bounds induce highly economically significant biases in the mean returns of options. In fact, our simulation results demonstrate that biases can be up to several percentage points per day. These large biases can lead researchers to faulty conclusions with respect to both the magnitude of the volatility risk premium and the sign of expected option returns.

Read the whole thing here.

While their paper does a good job of showing how option returns in academic studies can be biased by bid-ask spread, they also give some nice results on just how big the "volatility premium" may be (they're not the first to find this, but I like their results nonetheless).

The following table from the paper, shows mean returns on S&P 500 index options at various maturities (Short, Medium, Long) and degrees of of moneyness (In The Money, At The Money, Out of The Money). The figures are in basis points/day and are adjusted for bid-ask spread biases. What I found most striking were the results for short positions on short-term deep out-of-the-money puts (4% return per day) and deep OTM calls (3-9% per day).

Now THAT's definitely a table suitable for use in class.

HT: CXO Advisory Group

What's the Return to Shorting Naked Puts?

We're talking (briefly) about option payoffs in class this week. So, I was excited when I came across this piece titled "Why are Put Options So Expensive?", by Oleg Bondarenko of the University if Illinois at Chicago. In it, he provides some very interesting figures. First off, the abstract:

This paper studies the "overpriced puts puzzle" - the finding that historical prices of the S&P 500 put options have been too high and incompatible with the canonical asset-pricing models, such as CAPM and Rubinstein (1976) model. Simple trading strategies that involve selling at-the-money and out-of-the-money puts would have earned extraordinary profits. To investigate whether put returns could be rationalized by another, possibly nonstandard equilibrium model, we implement a new methodology. The methodology is "model-free" in the sense that it requires no parametric assumptions on investors' preferences. Furthermore, the methodology can be applied even when the sample is affected by certain selection biases (such as the Peso problem) and when investors' beliefs are incorrect.

We find that no model within a fairly broad class of models can possibly explain the put anomaly.

Writing put options should make consistent small profits,. but with a chance that the option writer will occasionally get really hosed. But by Bondareknko's analysis, markets consistently overvalue at the money (ATM) and out of the money options (OTM) that are "close" (i.e. within 6% of ATM). In fact, writing options seems to result in average returns of 39% per month, with returns for deep OTM options of almost double that. That's right - almost 40% per month.

So, how likely is the "hosing"? Does this merely reflect the risk of large losses? By his estimates, there would have to be a meltdown like the one in October 1987 1.3 times a year for the option writer to lose money.

So, why are put options so apparently overvalued? There are at least two possible explanations (other than something really funky/wrong with the data): one is that investors systematically overestimate the chance or severity of large market declines. The other is that option buyers have a utility function that is extremely risk averse. In either case, there's apparently an excess demand for insurance that option writers can benefit from (if they're willing to bear the risk).

HT: CXO Advisory group