Timeline for A tricky question about sequences of Normal RVs
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| May 23, 2018 at 22:42 | comment | added | Pierre Cattin | There's a good explanation of Brownian motion in week 8 of this free course: coursera.org/learn/financial-engineering-1 | |
| May 23, 2018 at 22:32 | comment | added | Pierre Cattin | It didn't disappear, it's on the next line :) $$2(E[A^2]E[R]-E[A]E[A]E[R]]) = 2((var(A)+E[A]^2)E[R]-E[A]E[A]E[R])$$ | |
| May 23, 2018 at 22:21 | vote | accept | eSurfsnake | ||
| May 23, 2018 at 22:19 | comment | added | eSurfsnake | That is a genius way to look at it. It also explains a simple Monte Carlo I was doing that gave a puzzling outcome, but I think I see why, roughly (if I actually do a number of numeric trials, then look at the correlation, it is amazingly insensitive to $\sigma$, but leads to a 5%-10% 'error' in std deviation depending on $\mu$, in line with your simulation). I have been looking into Brownian motions, but it is near impossible to find anyone or text who can explain and reconcile what it all means. How did you get to 4th line on variance, where $2(E[A2]E[R]−E[A]E[A]E[R]])$ 'disappeared'? | |
| May 23, 2018 at 21:46 | history | answered | Pierre Cattin | CC BY-SA 4.0 |