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Re: SABR global versus local fit

Posted by MikeD on Jun 17, 2016; 6:40pm
URL: http://quantlib.414.s1.nabble.com/SABR-global-versus-local-fit-tp17538p17539.html

I would ditch the ql implementation of swaption cube, and go with local sabr fits and some robust interpolation methods.  Much more flexible in my opinion.  I ran into problems when data wasn't symmetrical, as is the case in most of the major currencies. Just my two cents.

On Jun 17, 2016 2:01 PM, "terry leitch" <[hidden email]> wrote:
I’m currently writing an interface for Rquantlib into the saber swaption module using SwaptionVolCube1. I have an end of day surface from a well known exchange that covers from 1x1 all the way to 10x30 swaptions at +/- 200bps around ATM. Due to the proprietary nature, I don’t have permission to share but will try to seek it so I can be more specific.

First issue is NA’s. How does quant lib handle them? The data at the front end has from 1-5 strikes with NA’s due to the low rate environment. To keep the strikes consistent across all time I need to put in values, but the fit doesn’t converge at the front end, possibly due to the interpolated values. I’ve tried several extrapolations but none produce a cube that will converge in the fit, always exceeding the max error. My current view is that I need to develop vol cubes for a given problem based on the structure of expirations. So, for a xx5 I build a shorter Does anyone have a view?

Second, how does the cube fit method weight the volatilities for swap tenors? Is it equal weighting? If it is, that would be an issue because the duration of a 1x1 is a fraction of a 1x30. I noticed most error messages in the fit involve 1Y swap tenors, is the fit weighting by duration but then failing on an absolute measure of volatility difference, a difference I might be willing to ignore due to overall magnitude?

Third, are there any examples where the normal vol option has been used?

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What NetFlow Analyzer can do for you? Monitors network bandwidth and traffic
patterns at an interface-level. Reveals which users, apps, and protocols are
consuming the most bandwidth. Provides multi-vendor support for NetFlow,
J-Flow, sFlow and other flows. Make informed decisions using capacity planning
reports. http://sdm.link/zohomanageengine
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