Why Deep Out-of-the-Money Option Implied Volatility Can Be Noisy
Summary
The document considers fitting an implied-volatility curve to intraday option observations, where data become sparse and variable at extreme out-of-the-money strikes. The question is whether unusual observations can be discounted and whether option-market behavior provides a sound explanation beyond the small sample size.
A brief qualitative response points to the convexity and tail exposure of deep OTM options. Their payoffs relate to rare, potentially severe market moves, and demand for protection can affect premiums and implied volatility. The answer suggests that tail-event uncertainty and hedging needs may help explain distinctive pricing, but it does not establish that outliers are uninformative or caused by amateur trading. It offers no data, statistical test, or cited empirical literature. Sparse observations, bid-ask effects, and model sensitivity remain reasons to analyze the points carefully rather than simply remove them.
Key ideas
- Intraday implied-volatility observations can become sparse and unstable at extreme OTM strikes.
- Deep OTM options have convex payoffs that can respond sharply to large market moves.
- Tail-event uncertainty and hedging demand may influence premiums and implied volatility.
- The response is qualitative and does not prove that outliers contain little market information.
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# Variability of IVs of OTM options # Variability of IVs of OTM options I'm attempting to fit a curve through moneyness/IV datapoints of intra-day options. As you can see, the data gets sparser and more variable for highly OTM options. I'd like to argue why the outliers in this case can be (at least partially) ignored. One topic-independent argument would be simply the sparsity of the data, giving the outliers exaggerated importance. I would like to make a stronger argument with connection to options though. My reasoning, from what I gathered through a little research, is something along the lines of: the OTM options are by their nature more likely to create anomalies like this since they are very risky and likely to be traded by amateurs who are attracted by low option premiums. Thus an outlier is less likely to hold valuable information about the market. Whether that makes (any) sense and whether that could create this effect in the IV is not something I can decide with my lack of theoretical and empirical knowledge about this topic. Am I at least somewhat correct? What would be a correct argument? Is there some literature backing up the statements? It's entirely possible I'm missing something or am completely wrong. If that's the case, is there an argument to be made to the same effect? Please answer in simple terms. I am a student of mathematics so I can deal with mathematical complexity, but have very little knowledge of financial derivatives. Thank you very much! ## Answer by cdcaveman (score 0, accepted) https://quant.stackexchange.com/a/28172 This is a qualitative answer... Deep otm options have a value associated with there degree of convexity.. it has a much higher rate of change then anything ATM... Gamma is explosive for expiring otm options... Otm options also represent the rare event of a higher order.. so a deep otm option represents a tail event basically... we don't know much about tail events just that they have power laws to them .. nothing about their frequency... So basically you would have to make enough money selling those deep otm premiums to cover the loss when the rare event blows through your strike... Because a very small amount of money can hedge a very large drop in a portfolio the premium demand is higher as well.. I've been told this happened after 87 crash... It has to do with convex asymmetric payoffs basically... It's the first thing you learn when trading otm options typically by losing money
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