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Why High Implied Volatility Does Not Necessarily Mean Volatility Is Rich

Article Quant Q&A · Author: Abe

Summary

The document asks how to judge whether implied volatility is expensive or cheap when historical volatility is a weak guide. It argues that volatility’s fundamental value depends on changing conditions such as the arrival and importance of news, market sentiment, and how readily information can be traded. These drivers can be studied statistically, but relationships may fail out of sample when market conditions change.

The practical guidance is to identify a clear reason for a volatility trade, understand the instrument being traded, consider a long history of realized volatility, and assess whether quantitative signals make sense in the current market backdrop. The author’s oil trade illustrates the risk: a high and rising implied volatility level did not guarantee that selling volatility was attractive. The discussion offers no pricing model or tested framework for estimating fair value, and it emphasizes that the answer may differ across markets.

Key ideas

  • A high implied volatility level does not by itself show that volatility is overpriced.
  • Volatility depends on news flow, market sentiment, and the market’s ability to absorb new information.
  • Statistical relationships that appear useful in a backtest may fail when market conditions change.
  • Understand the exposure of the specific instrument before evaluating its volatility.
  • Use long historical context and current market conditions to assess whether a volatility signal is plausible.

Tags

Full text
# Rich Volatility, Poor Volatility


# Rich Volatility, Poor Volatility












I have been thinking very hard about properly pricing volatility. Outside of naive AR,ARCH,GARCH forecasting model which employs past data to forecast future vol, how does one "fundamentally" value volatility??? The key word here is "fundamentally".

In other worlds of insurance (health insurance, car insurance, etc.) a competent underwriter can look historically at one's driving record, health record, (past data in other words) to determine one's P(claim) & loss given claim and the entire pool's P(claim) and expected losses to determine a "fair" value to tack on for taking that risk.

So here is my question, how does one determine fundamental "fair value" for volatility of volatile securities (such as equity indicies, crude oil, gold, bonds, etc) in order to assess whether vol is rich or cheap? You might say, one starting point is to look at the past and use historical vol, however I have found this to be extremely unhelpful. The past needs to be discounted heavily in financial insurance unlike other insurance products and is a poor measure of the future. The only times I have found the imp vol to historical vol useful is in the rare occasions when historical vol exceed peoples volatility expectations which then underwriters adjusted volatility expectations upward. But this is rare and ~80% of the time implied vol is higher than historical. Black swans are as rare as they come -- you can sit there patiently waiting for one and by the time you give up on one coming is when it finally happens. Hence it's not a feasible strategy. So if we can't use historical vol what can we use to get a general idea of whether vol is rich or cheap?

I painfully ask this question because I recently learned the hard way, high implied volatility doesn't mean rich volatility. I sold vol on oil over the last several months only to get burned bad. Rising volatility DOESN'T mean rich volatility!! WTI with a vol at 20 two years ago can fundamentally have had a richer vol when it was at at a significantly lower level than than when its vol shot to 60 in the last couple of weeks.

I would appreciate any good words of help, guidance on the issue. Any past published research work on the topic you have either worked on or seen would be greatly appreciated.

## Answer by Bram (score 4)

https://quant.stackexchange.com/a/16994

I think this extremely hard to do (to the point where I think that every hedge fund that trades vol should be avoided like the plague).

The fundamental value of volatility would be a quantity that's related to the speed at which new news comes available to the market, the significance of news, the extent to which this news can be traded, general market sentiment and a host of other reasons. It is possible to do statistical analysis to the impact of certain types of news to moves in the underlying of course, but because vol is so opaque, even then it is very easy for out-of-sample performance to be horrible because some factor that was constant during your backtest, isn't anymore. Of course mileage various from market to market.

Practical advice:

- if you can't spell out exactly why you have an edge trading vol, you shouldn't be doing it (for the money; if your goal is to learn about options b/c you want to land a job as a trader, that of course is different). If the best reason you can come up with "it's been moving up so much in the past few weeks/months", think hard whether that's a reason to trade or to avoid trading.

- Know exactly what you're trading. If you are a retail investor and were trading something like options on USO, you're not exactly trading crude vol. Not saying you weren't trading crude vol, but based on the question I'm guessing you're likely to be a retail investor/trader.

- Have a long memory; I don't want to get too hung up on the crude vol example in your question (which is tempting since I actually do trade crude vol professionally), but looking back at 10 years of realized vol should have provided some indication that vol could go a lot higher (and if you think that "this time it's different than in 2008", you again need to be able to spell out the exact why of that mentioned under #1).

- I'm very quantitatively oriented. However, whenever I evaluate a vol trade that looks good just based on the numbers, I always try to think through what is going on in the market in general now as well, in order to get a feel of whether the numbers fit in with the general backdrop of the market in question.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.