Timeline for spline Interpolation on volatility surface not smooth
Current License: CC BY-SA 4.0
9 events
| when toggle format | what | by | license | comment | |
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| Mar 29, 2019 at 12:57 | comment | added | amdopt | You could use a constrained spline interpolation to avoid the overshooting at points 70 and 85. I have an example in a spreadsheet that is coded in VBA. I have a Python script somewhere as well. I'd be happy to post if it would help though it wouldn't be a complete answer to your question. | |
| Mar 29, 2019 at 11:18 | comment | added | JohnDoe | What else should your plot look like? Given your input data, which is matched by the spline, that is exactly what you would expect. So I guess you did nothing wrong with the interpolation. Maybe you should take another look at your input data especially the orange points at 170 and 70 look somewhat "wrong". And an extrapolation with splines is always problematic since it tends to show weird behavior like exploding values or even negative ones and offers posibilities for arbitrage. Maybe you could think about clamped splines. | |
| Mar 28, 2019 at 15:19 | comment | added | Jason Chen | @BobJansen I just added my MATLAB code. | |
| Mar 28, 2019 at 15:17 | history | edited | Jason Chen | CC BY-SA 4.0 |
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| Mar 28, 2019 at 15:09 | comment | added | Bob Jansen♦ | Aha, I think it would be helpful if you show how you interpolated the data in MATLAB. | |
| Mar 28, 2019 at 14:56 | comment | added | Jason Chen | @BobJansen I generated interpolated data in Matlab and scatter plot in Excel | |
| Mar 28, 2019 at 14:46 | comment | added | Bob Jansen♦ | This doesn't look good, no. How did you create the plot? | |
| Mar 28, 2019 at 14:45 | review | First posts | |||
| Mar 28, 2019 at 15:15 | |||||
| Mar 28, 2019 at 14:44 | history | asked | Jason Chen | CC BY-SA 4.0 |