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Choosing SABR Beta for EURIBOR Swaption Smiles and CMS Pricing

Article Quant Q&A · Author: Søren Skov

Summary

The document considers how to choose the beta parameter in SABR when using swaption volatility smiles to price a constant maturity swap. The example uses European payer and receiver swaptions to replicate the CMS value, with SABR used to interpolate and extrapolate market smiles. Two beta choices produce different CMS spread estimates, one closer to the cited market quote; the question is whether choosing the closer value is academically defensible.

The answer describes several approaches rather than a unique calibration rule. One can fit beta to CMS market prices, or infer a rough estimate from the slope of log at-the-money volatility against log forward rate, though that slope is noisy and may not distinguish nearby beta values. It warns that CMS convexity is sensitive to smile extrapolation and that SABR can imply volatility continuing to rise at extreme strikes. Desk practices differ, and a single beta fitted to limited CMS quotes may not be robust or evolve as expected over time.

Key ideas

  • The SABR beta choice can materially affect CMS convexity adjustments through its effect on smile extrapolation.
  • One approach is to calibrate beta to observed CMS swap prices, though a single parameter may only achieve a best fit.
  • A slope-based estimate from log volatility and log forward rates can be noisy.
  • Extrapolating SABR volatility to extreme strikes requires care because the model may keep volatility rising.

Tags

Full text
# What SABR $\beta$ to use for EURIBOR swaption smiles


# What SABR $\beta$ to use for EURIBOR swaption smiles












I am currently wrapping up my thesis. My final chapter is on applying the SABR model model for pricing purposes. I am valuing a constant maturity swap by replicating its value using plain vanille European payer and receiver swaptions as described by P. Hagan (http://pds4.egloos.com/pds/200702/26/99/convexit.pdf) in equation (2.19a). I use the SABR model to inter- and extrapolate market volatility smiles.

To be more specific, I am pricing a 5Y CMS swap swapping the 10Y EURIBOR6M swap rate against a floating payment of EURIBOR3M with payments being made quarterly. I have (somewhat arbitrarily) chosen to price the CMS swap as if today is June 1st 2010, but $\beta$ should be fairly stable and a contemporary estimate would be equally helpful/interesting. My "problem" is, that using $\beta=0.25$ gives me a CMS spread of 162 bp while using $\beta=0.85$ gives me a CMS spread of 176 bp. The Bloomberg mid quote for this specific product on June 1st 2010 is 175.5 bp, but I feel that simply choosing the $\beta$ that fits better is not very... academic.

## Answer by ldnquant (score 7, accepted)

https://quant.stackexchange.com/a/579

There's a paper by Fabio Mercurio called "Smiling at Convexity" which discusses this and proposes doing basically what you've done, namely setting beta to match the market prices of CMS swaps.

In the Hagan et. al. SABR paper they discuss ways of setting beta based on plotting ATM vols versus the forward rates. The idea here is to plot log vol vs log fwd rate, the slope of which is 1 - $\beta$. This gives you a rough idea, but it's very noisy, so you wouldn't really be able to distinguish (say) $\beta$ = 0.5 and beta = 0.6.

The convexity adjustment will be very sensitive to how you extrapolate the smile, which in the SABR model is strongly affected by the value of beta. You also have to be a bit careful with how far you take the extrapolation, the SABR model will just keep the vol going up forever as you integrate the strike up to infinity.

EDIT: Just to be clear, there's no unique answer, different desks will do different things. Fitting the CMS swaps is probably a good idea, but given only one parameter $\beta$ you would only get a best fit. I've not tried to do this, but I suspect that your $\beta$ values would be very stable against moves in the the CMS market, which seems unsatisfiying, as you'd expect $\beta$ to change very slowly with time.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.