Quote from kapw7:
What you need to look up is "root time vega"
Generally you cannot add the vegas of two options with different expiries. One way to do it is to normalise the vega(s) by dividing with the square root of time. Then you can weigh your calendar to be vega neutral.
My turn to ask a question:
This makes some assumptions about volatility. For example that there is no mean reversion. Is that something you need to consider in practice?
Quote from kapw7:
What you need to look up is "root time vega"
Generally you cannot add the vegas of two options with different expiries. One way to do it is to normalise the vega(s) by dividing with the square root of time. Then you can weigh your calendar to be vega neutral.
My turn to ask a question:
This makes some assumptions about volatility. For example that there is no mean reversion. Is that something you need to consider in practice?
Quote from luisHK:
I'm not sure wether you're adressing me, as the discussion about root time vega is as much out of my league as before I opened 2 links on the topic.
I would assume Volatility is mean reverting, and consider it when trading it.
Quote from cdcaveman:
don't worry its out of no ones league... you can't look at one option for jan expiration and one at feb expiration and account for the difference in time.. so you adjust for time..
thats all multiplying by the square foot of time does.. It normalizes the figure to time... brings it back to a unit that is directly comparable between different expiration..
don't be like me.. i sit there and say i don't understand before i even try because i'm scared i'll feel stupid and not get it after really trying hard.. theres no rush to figure everything out. The joy is in the Journey!
Yes, square root time scaling can be misleading. Diebold et al. address this in the attached paper.Quote from kapw7:
This makes some assumptions about volatility. For example that there is no mean reversion. Is that something you need to consider in practice?
Quote from Kevin Schmit:
Yes, square root time scaling can be misleading. Diebold et al. address this in the attached paper.