Cutting Edge introduction: requiem for a probabilist

The already challenging task of calibrating stochastic volatility models becomes even more complex when rates are random too. But an efficient Monte Carlo approach can be found – by using an esoteric, but neglected, stochastic calculus. Laurie Carver introduces this month’s technical papers

Paul Malliavin, a French mathematician who died in 2010 aged 84, was working on an esoteric problem in pure probability in the 1970s – under what conditions the distribution of a random variable is smooth – when he discovered one of the revolutionary ideas of stochastic analysis. His breakthrough has been largely ignored by finance practitioners, but the first of this month’s technical papers – Being particular about calibration, by Société Générale’s Julien Guyon and Pierre Henry-Labordère –