Impact of future events on volatilities (ie. awaiting FDA approval etc.)

This is just a hypothetical case:

Suppose for a biotech company the current ATM implied volatility (IV) for both Call and Put options is about 30%. On Dec 7 (ie. in about 4 months from now) the FDA will decide whether an important drug product of this company will get approval or not.
How should the IVs of the monthly options for Sep, Oct, Nov, Dec, Jan, Feb realistically be, as seen from now? Which month should have the highest IV as of now (I guess the Nov and/or Dec options). How should the IVs of Jan and Feb be as of now?

Considering it is 4 months out you might not see any hump in the term structure - Especially because biotechs usually have very high non-event vol.

Remember, volatility is the average of the daily standard deviations.
So lets say the daily non event standard deviation is 4% and the implied 1 day event standard deviation is 15%. For a 4 month option (120 days). The implied volatility without the event would be 4%*16 = 64%
With the event, the average daily move would be (4*119 + 15)/120 = 4.09%.
If we multiply 4.09 by 16 we get 65.4

So for the term structure you would probably see something like:
Sept<-64
Oct<-64
Nov<-64
Dec<-65.4
Jan<-65
Feb<64.5
 
Theoretically the IV would be highest in the expiration of the event. But this isn’t the rule, and sometimes higher vol is a back dated month.

the question would be, how much conviction do you have of this fundamentally binary knowledge and how can you profit off this? Maybe trying a calendarized butterfly? Buy the wings in the lower IV surrounding the higher IV (body) binary event. Maybe break the wing or skip a strike to provide bias, and maybe even choose unbalanced contracts (132/231/253/352) to show bias to the term structure.
 
Remember, volatility is the average of the daily standard deviations.
So lets say the daily non event standard deviation is 4% and the implied 1 day event standard deviation is 15%. For a 4 month option (120 days). The implied volatility without the event would be 4%*16 = 64%
With the event, the average daily move would be (4*119 + 15)/120 = 4.09%.
If we multiply 4.09 by 16 we get 65.4

So for the term structure you would probably see something like:
Sept<-64
Oct<-64
Nov<-64
Dec<-65.4
Jan<-65
Feb<64.5

Only 1.4 vol points of “eventfulness” packed in this premium?
Same question here.

I have a question for both of you: how do I calculate the probability distribution function of a binary event assuming Gaussian distribution? The combination of two Gaussians each centers around the outcome? Is the sum of two Gaussians a Gaussian?

Thanks.
 
Only because it's so far out - It's being diluted by the non event vol.

This is where the scammy "iv ramp" that a lot of vendors push comes from.
 
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