Vladimir V. Piterbarg was a Managing Director and the Global Head of the Quantitative Analytics group at Barclays Capital, and worked with them since 1997 as an interest rate quant at top investment banks. He taught at the University of Chicago Mathematical Finance program for a number of years, and is a prolific and respected researcher in the area of interest rate modeling.
He won two Risk Magazine's Quant of the Year Awards (2006 and 2011), and holds a PhD in Mathematics (Probability Theory) from the University of Southern California. He serves as an associate editor of The Journal of Computational Finance and The Journal of Investment Strategies.
Articles by Vladimir Piterbarg
Alternatives to deep neural networks in finance
Two methods to approximate complex functions in an explainable way are presented
Automatic implicit function theorem
New technique can improve use of adjoint algorithmic differentiation in calibration problems
The arcsine law for quantile derivatives
A new pricing model for quantile-based derivatives, such as Napoleon options, is presented
Benchmark reform goes non-linear
Terminating Libor will bring great challenges to the pricing of non-linear rate products
The optimal investment problem in stochastic and local volatility models
This paper considers the classical optimal investment allocation problem of Merton through the lens of some more modern approaches, such as the stochastic volatility and local volatility models.