Timeline for Option pricing using discrete fourier transform (python)
Current License: CC BY-SA 4.0
10 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Feb 5, 2021 at 7:34 | vote | accept | ThisIsGonnaBeCool | ||
| Feb 3, 2021 at 19:28 | answer | added | ThisIsGonnaBeCool | timeline score: 1 | |
| Feb 2, 2021 at 20:08 | comment | added | ThisIsGonnaBeCool | Good point @Kermittfrog - I had not in fact checked that, but I have done so now and np.power() also returns the expected result for arrays of complex numbers | |
| Feb 2, 2021 at 19:14 | comment | added | Kermittfrog | Ok, even the numpy.power function, yes? | |
| Feb 2, 2021 at 18:52 | comment | added | ThisIsGonnaBeCool | Thanks v much @Kermittfrog - you're completely correct re the discount, I have updated accordingly. On your second point, I think they can do - I have tried both fft and ifft for simple examples with complex numbers and they appear to come to the expected result. | |
| Feb 2, 2021 at 18:50 | history | edited | ThisIsGonnaBeCool | CC BY-SA 4.0 |
added 10 characters in body
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| Feb 2, 2021 at 7:43 | comment | added | Kermittfrog | ... and another question: are you sure that your functions in the second to last line are able to handle complex numbers? | |
| Feb 2, 2021 at 7:27 | comment | added | Kermittfrog | Hi and welcome! I don't think that it is driving the problem here, but shouldn't you multiply by discount at the second-to-last line of your code? | |
| Feb 2, 2021 at 7:08 | review | First posts | |||
| Feb 2, 2021 at 19:07 | |||||
| Feb 2, 2021 at 7:05 | history | asked | ThisIsGonnaBeCool | CC BY-SA 4.0 |