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 https://www.ma.imperial.ac.uk/~ajacquie/
- Quantum Computing for Finance, MSc in Mathematics and Finance
- Volatility modelling, MSc in Mathematics and Finance
- Python for 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.
Assouel A, Jacquier A, Kondratyev A, 2022, A quantum generative adversarial network for distributions, Quantum Machine Intelligence, Vol:4, ISSN:2524-4906
Jacquier A, Pannier A, 2022, Large and moderate deviations for stochastic Volterra systems, Stochastic Processes and Their Applications, Vol:149, ISSN:0304-4149, Pages:142-187
Jacquier A, Badikov S, Davis M, 2021, Perturbation analysis of sub/super hedging problems, Mathematical Finance, Vol:31, ISSN:0960-1627, Pages:1240-1274
et al., 2021, Pathwise large deviations for the rough Bergomi model: Corrigendum, Journal of Applied Probability, Vol:58, ISSN:0021-9002, Pages:849-850
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