Ankush Agarwal

Personal website

Google scholar

Research areas

• Mathematical finance
• Data science in finance
• Financial statistics
• Monte Carlo methods

Teaching

• FM9593: Monte Carlo Methods and Financial Applications
• FM4521B/9521: Advanced Financial Modelling
• FM2555A: Corporate Finance

Graduate Student Supervision

• Ying Liao (University of Glasgow, UK)
• Buchun Wang (University of Glasgow, UK)
• Shuya Zhang (University of Glasgow, UK)
• Bilal Husain (co-supervised with C. Bravo)
• Hailong Jiang (co-supervised with C. de Souza)

Publications

Journals 

• Numerical approximation of McKean-Vlasov SDEs via stochastic gradient descent with A. Amato, G. dos Reis and S. Pagliarani. Journal of Applied Probability. 2025.
• Robust valuation and optimal harvesting of forestry resources in the presence of catastrophe risk and parameter uncertainty with C. Ewald and Y. Zou. European Journal of Operational Research. 2025.
• Efficient calibration of the shifted square-root diffusion model to credit default swap spreads using asymptotic approximations with Y. Liao*. International Journal of Computer Mathematics. 2025, Vol. 103, No. 1, pp. 41-62.
• On the predictive power of food commodity futures prices in forecasting inflation with C-O. Ewald, S. Zhang* and Y. Zhou. Quantitative Finance. 2025, Vol. 25, No. 12, pp. 1957-1969.
• Optimal income drawdown and investment with longevity basis risk with C. Ewald and Y. Wang*. Scandinavian Actuarial Journal. 2025, Vol. 25, No. 7, pp.680-717.
• Penalized estimation of sparse Markov regime-switching vector auto-regressive models with G. Chavez Martinez, A. Khalili and S. Ejaz Ahmed. Technometrics. 2023, Vol. 65, No. 4, pp. 553-563.
• Hedging longevity risk in defined contribution pension schemes with C-O. Ewald and Y. Wang*. Computational Management Science. 2023, Vol. 20.
• A Fourier-based Picard-iteration approach for a class of McKean-Vlasov SDEs with Lévy jumps with S. Pagliarani. Stochastics. 2021, Vol. 93, No. 4, pp. 592-624.
• The implied Sharpe ratio with M. Lorig. Quantitative Finance. 2020, Vol. 20, No. 6, pp. 1009-1026.
• Branching diffusion representation of semi-linear elliptic PDEs and estimation using Monte Carlo method with J. Claisse. Stochastic Processes and Their Applications. 2020, Vol. 130, No. 8, pp. 5006-5036.
• Numerical approximation of McKean Anticipative BSDEs arising in initial margin requirements with S. De Marco, E. Gobet, J.G. Lopéz-Salas, F. Noubiagain and A. Zhou. ESAIM: Proceedings and Surveys. 2019, Vol. 65, No. 1, pp. 1- 26.
• Portfolio benchmarking under drawdown constraint and stochastic Sharpe ratio with R. Sircar. SIAM Journal on Financial Mathematics. 2018, Vol. 9, No. 2, pp. 435- 464.
• Study of new rare event simulation schemes and their application to scenario generation with S. De Marco, E. Gobet and G. Liu.  Mathematics and Computers in Simulation. 2018, Vol. 143, Supp. C, pp. 89- 98.
• American options under stochastic volatility: Control variates, randomization and multiscale asymptotics with S. Juneja and R. Sircar. Quantitative Finance. 2016, Vol. 16, No. 01, pp. 17-30.
• Nearest neighbor based estimation technique for pricing Bermudan options with S. Juneja. International Game Theory Review.2015, Vol. 17, No. 01, pp. 154002.
• Efficient simulation of large deviations events for sums of random vectors using saddle point representations with S. Dey and S. Juneja. Journal of Applied Probability. 2013, Vol. 50, No. 03, pp. 703-720.

Peer-reviewed proceedings

• Finite variance unbiased estimation of stochastic differential equations with E. Gobet. Proceedings of 2017 Winter Simulation Conference. pp. 1950-1961.
• Comparing optimal convergence rate of stochastic mesh and least squares method for Bermudan option pricing with S. Juneja. Proceedings of 2013 Winter Simulation Conference. pp. 701-712.