Dr Antoine Jacquier is a Reader in the Department of Mathematics at Imperial College London.
His research interests are in Probability and Mathematical Finance. He is particularly interested in large deviations methods and asymptotic expansions for stochastic processes, and their applications to volatility modelling.
He also works on applications of Deep Learning and Quantum Computing in Mathematical Finance.
His personal webpage can be found at www2.imperial.ac.uk/~ajacquie/
- Statistical Methods in Finance, MSc in Mathematics and Finance.
From September 2006 to September 2010, Dr Antoine Jacquier has been acting as a quantitative consultant for Zeliade Systems, Paris. The main areas of research were the calibration of stochastic volatility models and the pricing of volatility derivatives.
He has also been consulting for banks in the area of model calibration and option pricing.
et al., 2021, Pathwise large deviations for the rough Bergomi model: Corrigendum, Journal of Applied Probability, Vol:58, ISSN:0021-9002, Pages:849-850
Jacquier A, Badikov S, Davis M, 2021, Perturbation analysis of sub/super hedging problems, Mathematical Finance, ISSN:0960-1627
El Amrani M, Jacquier A, Martini C, 2021, Short communication: dynamics of symmetric SSVI smiles and implied volatility bubbles, Siam Journal on Financial Mathematics, Vol:12, ISSN:1945-497X, Pages:1-15
et al., 2020, Correction note to pathwise large deviations for the rough Bergomi model, Journal of Applied Probability, ISSN:0021-9002
Jacquier A, Shi F, 2020, Small-time moderate deviations for the randomised Heston model, Journal of Applied Probability, ISSN:0021-9002