Timeline for Get expected joint-payoff price of digital options from individual payoffs
Current License: CC BY-SA 3.0
12 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 3, 2016 at 13:03 | vote | accept | stochastic_zeitgeist | ||
| Oct 3, 2016 at 12:43 | answer | added | Quantuple | timeline score: 1 | |
| Oct 2, 2016 at 11:13 | comment | added | Nick | @rekcaH-Xunil, thx. Could you provide a link on the used method of pricing? | |
| Oct 2, 2016 at 8:37 | comment | added | stochastic_zeitgeist | @Nick corrected | |
| Oct 2, 2016 at 8:37 | history | edited | stochastic_zeitgeist | CC BY-SA 3.0 |
added 4 characters in body
|
| Oct 2, 2016 at 1:07 | comment | added | Nick | @rekcaH-Xunil, what means max(X1−B1) in the formula ? It will be return (X1−B1) all time. | |
| Oct 1, 2016 at 16:24 | comment | added | stochastic_zeitgeist | Unfortunately, I don't have access to it, however I am at liberty to assume the prices as independent. | |
| Oct 1, 2016 at 15:15 | comment | added | will | yesm but you need something like $E[X_1 \cdot X_2]$ (or more likely, something like $E[\mathrm{max}(X_1 - X_2,0)]$) to get the correlation, since $E[\mathrm{max}(X_1-B_1,0) \cdot \mathrm{min}(B_2-X_2,0)]$ can depend on it (depending on the distribution). | |
| Oct 1, 2016 at 14:46 | comment | added | stochastic_zeitgeist | Since I have samples of $Q_1$ and $Q_2$, which depend on $X_1$ and $X_2$. Thus I have samples that depend both on $X_1$ and $X_2$. | |
| Oct 1, 2016 at 14:02 | comment | added | will | Do you have any samples that depend on a combination of both $X_1$ and $X_2$? If you don't, then you're going to have to make some assumptions on the correlation. | |
| Oct 1, 2016 at 11:12 | review | First posts | |||
| Oct 1, 2016 at 17:41 | |||||
| Oct 1, 2016 at 11:10 | history | asked | stochastic_zeitgeist | CC BY-SA 3.0 |