Podcast: Dominique Bang on his stochastic local vol model

The new approach delivers quick and accurate computation of prices

Dominique Bang podcast
Dominique Bang (centre), with Mauro Cesa and Nazneen Sherif
Photo: Iain Winfield

Dominique Bang, head of interest rate vanilla analytics at Bank of America Merrill Lynch in London, joined us in our studio to talk about his work on a local stochastic volatility model.

In his article on this topic, Local stochastic volatility: shaken, not stirred, available now on Risk.net, Bang introduces a new European options model, where he mixes a pure stochastic volatility process with a local volatility process. It is arbitrage-free, handles non-positive interest rates, is quick to compute and allows for accurate calibration of constant maturity swaps and swaptions.

While the model’s performance is highlighted in the article with reference to the popular stochastic alpha beta rho model (SABR), it is applicable to a number of volatility models, including the Heston model.


00:00 Intro

00:58 The paper

02:30 Lamperti’s transform

03:55 Shaken, not stirred

05:08 Advantages of the new approach

06:35 Applicability

07:45 SABR example

10:05 Computational speed

12:22 Intuition and tractability

To hear the full interview, listen in the player above, or download. Future podcasts in our Quantcast series will be uploaded to Risk.net. You can also visit the main page here to access all tracks, or go to the iTunes store or Google Podcasts to listen and subscribe.

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