Dr Ankush Agarwal

  • Lecturer in Quantitative Finance and Risk Management (Economics)

Biography

Ankush is educated at IIT Bombay (BTech, MTech) and Tata Institute of Fundamental Research (PhD). Before joining the University of Glasgow Adam Smith Business School, Ankush worked at the commodities trading desk of Bank of America (2006-09) and as a post-doctoral researcher (2014-17) in Financial Modelling group at Centre of Applied Mathematics, École Polytechnique.


Research interests

Ankush is a member of the School's Finance research cluster.

Areas of expertise:

  • Mathematical finance
  • Monte Carlo methods
  • Markov Chain Monte Carlo methods
  • Stochastic analysis

Grants

  • Principal’s Early Career Mobility Scheme Fund (£2300)
  • Fully funded researcher, CEMRACS 2017, CIRM, Marseille (EUR 2500)
  • Travel grant, 2015 Workshop on systemic risk and financial networks, IPAM, UCLA ($750)
  • Travel grant, 2013 RTG Summer School in Financial Mathematics, Princeton University ($1200)

Supervision

Current PhD students

  • Yongjie Wang (2018 - present)
  • Yihan Zou (2018 - present)

Teaching

  • Derivatives pricing
  • Mathematical finance
  • Computational finance

Additional information

  • Post-doctoral fellowship by Risk Foundation (2014-17)
  • Tata Consultancy Services research scholarship (2012-14)
  • National Talent Search Scholarship awarded by Govt of India (2001-06)

Publications

List by: Type | Date

Jump to: 2019 | 2018 | 2016 | 2015 | 2013
Number of items: 8.

2019

Agarwal, A. , De Marco, S., Gobet, E., Lopez-Salas, J.-G., Noubiagain, F. and Zhou, A. (2019) Numerical approximations of McKean anticipative backward stochastic differential equations arising in initial margin requirements. ESAIM: Proceedings and Surveys, 65, pp. 1-26. (doi:10.1051/proc/201965001)

2018

Agarwal, A. , De Marco, S., Gobet, E. and Liu, G. (2018) Study of new rare event simulation schemes and their application to extreme scenario generation. Mathematics and Computers in Simulation, 143, pp. 89-98. (doi:10.1016/j.matcom.2017.05.004)

Agarwal, A. and Gobet, E. (2018) Finite Variance Unbiased Estimation of Stochastic Differential Equations. In: 2017 Winter Simulation Conference, Las Vegas, NV, USA, 03-06 Dec 2017, pp. 1950-1961. ISBN 9781538634288 (doi:10.1109/WSC.2017.8247930)

Agarwal, A. and Sircar, R. (2018) Portfolio benchmarking under drawdown constraint and stochastic sharpe ratio. SIAM Journal on Financial Mathematics, 9(2), pp. 435-464. (doi:10.1137/16M1100861)

2016

Agarwal, A. , Juneja, S. and Sircar, R. (2016) American options under stochastic volatility: control variates, maturity randomization & multiscale asymptotics. Quantitative Finance, 16(1), pp. 17-30. (doi:10.1080/14697688.2015.1068443)

2015

Agarwal, A. and Juneja, S. (2015) Nearest neighbor based estimation technique for pricing Bermudan options. International Game Theory Review, 17(1), 1540002. (doi:10.1142/s0219198915400022)

2013

Agarwal, A. and Juneja, S. (2013) Comparing optimal convergence rate of stochastic mesh and least squares method for Bermudan option pricing. In: 2013 Winter Simulation Conference (WSC), Washington, DC, USA, 08-11 Dec 2013, pp. 701-712. ISBN 9781479939503 (doi:10.1109/wsc.2013.6721463)

Agarwal, A. , Dey, S. and Juneja, S. (2013) Efficient simulation of large deviation events for sums of random vectors using saddle-point representations. Journal of Applied Probability, 50(3), pp. 703-720. (doi:10.1017/s0021900200009797)

This list was generated on Mon May 20 02:12:57 2019 BST.
Number of items: 8.

Articles

Agarwal, A. , De Marco, S., Gobet, E., Lopez-Salas, J.-G., Noubiagain, F. and Zhou, A. (2019) Numerical approximations of McKean anticipative backward stochastic differential equations arising in initial margin requirements. ESAIM: Proceedings and Surveys, 65, pp. 1-26. (doi:10.1051/proc/201965001)

Agarwal, A. , De Marco, S., Gobet, E. and Liu, G. (2018) Study of new rare event simulation schemes and their application to extreme scenario generation. Mathematics and Computers in Simulation, 143, pp. 89-98. (doi:10.1016/j.matcom.2017.05.004)

Agarwal, A. and Sircar, R. (2018) Portfolio benchmarking under drawdown constraint and stochastic sharpe ratio. SIAM Journal on Financial Mathematics, 9(2), pp. 435-464. (doi:10.1137/16M1100861)

Agarwal, A. , Juneja, S. and Sircar, R. (2016) American options under stochastic volatility: control variates, maturity randomization & multiscale asymptotics. Quantitative Finance, 16(1), pp. 17-30. (doi:10.1080/14697688.2015.1068443)

Agarwal, A. and Juneja, S. (2015) Nearest neighbor based estimation technique for pricing Bermudan options. International Game Theory Review, 17(1), 1540002. (doi:10.1142/s0219198915400022)

Agarwal, A. , Dey, S. and Juneja, S. (2013) Efficient simulation of large deviation events for sums of random vectors using saddle-point representations. Journal of Applied Probability, 50(3), pp. 703-720. (doi:10.1017/s0021900200009797)

Conference Proceedings

Agarwal, A. and Gobet, E. (2018) Finite Variance Unbiased Estimation of Stochastic Differential Equations. In: 2017 Winter Simulation Conference, Las Vegas, NV, USA, 03-06 Dec 2017, pp. 1950-1961. ISBN 9781538634288 (doi:10.1109/WSC.2017.8247930)

Agarwal, A. and Juneja, S. (2013) Comparing optimal convergence rate of stochastic mesh and least squares method for Bermudan option pricing. In: 2013 Winter Simulation Conference (WSC), Washington, DC, USA, 08-11 Dec 2013, pp. 701-712. ISBN 9781479939503 (doi:10.1109/wsc.2013.6721463)

This list was generated on Mon May 20 02:12:57 2019 BST.