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What you often obeserve in implied volatiltiy are higher levels of implied volatility for upcoming events like earnings or presentation of pharma data. For a human being which collects manual the information it is possbile to interpret this "spikes" or higher levels in implied volatility. Higher implied volatility in a single stock could also be observed if the whole market is facing higher implied volatility.

Is there a model or way you suggest, to decompose implied volatility to a market driven component and an idiosyncratic component?

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I was also looking for a way to attribute the changes in single equity's implied volatility to the change in general market vs. the idiosyncratic change of this particular equity. I ended up with a very simplistic and transparent approach: VIX is the market, while the difference between this equity's implied vol and VIX is idiosyncratic, not explained by the market. No betas or anything fancy. If the difference moves, then look for news that might have triggered the movement.

For a sufficiently liquid CDS, I very similarly look at CDS spread changes, but don't currently try to take out "the market", and am thinking of simply subtracting CDX NA IG.

However you may want to look for other "market" numbers roe names that aren't North American large caps.

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  • $\begingroup$ Thank you very much for your answer. Did you have any special approach for expiry matching, like trying so replicate the VIX methodology on every available index option expiry? My current knowledge is, that the VIX Index is the implied volatility for on a rolling basis of 30 days, so VIX Future which expires in November is replicating the Implied Volatility of Dec options. If you have a priced in gap between this could be a problem, couldn't be? $\endgroup$ Commented Nov 19, 2022 at 21:22

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