Started with a Q&A, and then moved to optionality, convexity and model error. @DrCirillo talked about EVT and @financequant was able to join us again.
Personal highlights
- Optionality: You have the right but not the obligation. Notice the asymmetry here.
2/n #RWRI 14
- Optionality gives you convex payoffs (very rarely optionality <=> convexity doesn't hold)
- Example of optionality: trial and error (T&E)
- How to find hidden optionality?
A. Not easy. You need to train for it. Domain dependent, but T&E gives you optionality
Today we continued talking about fat tails and convexity. @financequant's talk had to be postpone because power went out in his location.
Personal highlights
- We have said before that we can't forecast fat tail variables. But why?
2/n
Ans: Because fat tails are determine by one or a few points. The fatter the tail, the bigger the effect of one observation.
- This argument also explains why correlation has no meaning under fat tail variables. The relationship between two fat tails is given by a point
1 subscribed
