World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
30
Citations
3829
World Ranking
3520
National Ranking
226

Overview

Ben Hambly is affiliated with the University of Oxford in the United Kingdom. Their academic work primarily spans the fields of Economics, Econometrics and Finance, as well as Mathematics.

Their research covers a range of subfields, including:

  • Finance
  • Statistical and Nonlinear Physics
  • Computational Theory and Mathematics
  • Management Science and Operations Research
  • Economics and Econometrics

Main topics of their research activity include:

  • Stochastic processes and financial applications
  • Advanced Thermodynamics and Statistical Mechanics
  • Advanced Mathematical Modeling in Engineering
  • Mathematical Biology Tumor Growth
  • Advanced Bandit Algorithms Research
  • Complex Systems and Time Series Analysis
  • Adaptive Dynamic Programming Control

Ben Hambly has published extensively, with frequent publications in venues such as:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Stochastic Processes and their Applications
  • Mathematical Finance
  • SIAM Journal on Control and Optimization

Selected recent papers from Ben Hambly include:

  • Recent advances in reinforcement learning in finance, 2023, Mathematical Finance
  • Recent Advances in Reinforcement Learning in Finance, 2021, SSRN Electronic Journal
  • Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a Finite Horizon, 2021, SIAM Journal on Control and Optimization
  • Limit Order Books, Diffusion Approximations and Reflected SPDEs: From Microscopic to Macroscopic Models, 2020, Applied Mathematical Finance
  • Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a Finite Horizon, 2020, arXiv (Cornell University)

Frequent collaborators in research include:

  • Renyuan Xu
  • Huining Yang
  • Philipp Jettkant
  • Andreas Søjmark
  • Julian Meier

Best Publications

  • Fractals, random shapes, and point fields

    Ben Hambly

  • Uniqueness for the signature of a path of bounded variation and the reduced path group

    Ben M. Hambly;Terry J. Lyons

  • MONTE CARLO METHODS FOR THE VALUATION OF MULTIPLE‐EXERCISE OPTIONS

    Nicolai Meinshausen;B.M. Hambly

  • Modelling spikes and pricing swing options in electricity markets

    Ben Hambly;Sam Howison;Tino Kluge

  • Transition density estimates for Brownian motion on affine nested fractals

    Pat J. Fitzsimmons;Ben M. Hambly;Takashi Kumagai

  • Transition Density Estimates for Diffusion Processes on Post Critically Finite Self-Similar Fractals

    B. M. Hambly;T. Kumagai

  • Invariance principle for the random conductance model

    S. Andres;M. T. Barlow;J.-D. Deuschel;B. M. Hambly

  • Brownian motion on a homogeneous random fractal

    B. M. Hambly

  • Brownian motion on a random recursive Sierpinski gasket

    B. M. Hambly

  • Parabolic Harnack Inequality and Local Limit Theorem for Percolation Clusters

    Ben M Hambly;Martin T Barlow

  • Stochastic Evolution Equations in Portfolio Credit Modelling

    N. Bush;B. M. Hambly;H. Haworth;L. Jin

  • Random fractal strings: Their zeta functions, complex dimensions and spectral asymptotics

    Ben M. Hambly;Michel L. Lapidus

  • Heat kernel estimates for symmetric random walks on a class of fractal graphs and stability under rough isometries

    B. M. Hambly;T. Kumagai

  • FINITELY RAMIFIED GRAPH-DIRECTED FRACTALS, SPECTRAL ASYMPTOTICS AND THE MULTIDIMENSIONAL RENEWAL THEOREM

    B. M. Hambly;S. O. G. Nyberg

  • Policy Gradient Methods for the Noisy Linear Quadratic Regulator over a Finite Horizon

    Ben Hambly;Renyuan Xu;Huining Yang

  • Recent Advances in Reinforcement Learning in Finance

    Ben M. Hambly;Renyuan Xu;Huining Yang

  • A dual approach to multiple exercise option problems under constraints

    Nikolay Aleksandrov;Ben Hambly

  • Stochastic area for Brownian motion on the Sierpinski gasket

    B. M. Hambly;T. J. Lyons

  • Diffusion on the Scaling Limit of the Critical Percolation Cluster in the Diamond Hierarchical Lattice

    B. M. Hambly;T. Kumagai

  • Self‐Similar Energies on Post‐Critically Finite Self‐Similar Fractals

    Ben M. Hambly;V. Metz;Alexander Teplyaev

  • Extending the Wong-Zakai theorem to reversible Markov processes

    Richard F. Bass;Ben Hambly;Terry J. Lyons

  • Parabolic Harnack Inequality and Local Limit Theorem for Percolation Clusters

    Martin Barlow;Ben Hambly

Frequent Co-Authors

Takashi Kumagai
Takashi Kumagai Waseda University
Terry Lyons
Terry Lyons University of Oxford
Neil O'Connell
Neil O'Connell University College Dublin
Martin T. Barlow
Martin T. Barlow University of British Columbia
Mark S.P. Sansom
Mark S.P. Sansom University of Oxford
Jacob Piehler
Jacob Piehler Osnabrück University
Colin Kleanthous
Colin Kleanthous University of Oxford
Andreas E. Kyprianou
Andreas E. Kyprianou University of Warwick
Michel L. Lapidus
Michel L. Lapidus University of California, Riverside

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Mathematics in the USA opens doors to a variety of related online degrees and promising career pathways. For those looking to strengthen their leadership and business skills alongside a quantitative background, exploring the best one year mba programs can be a strategic option. These programs offer a fast track to managerial roles without requiring a lengthy commitment.

Additionally, students who have completed prior coursework might find online mba programs that accept transfer credits beneficial. This flexibility can save time and costs while allowing for a personalized educational journey, especially for mathematics graduates considering career shifts or advancement in business fields.

Mathematics students interested in emerging data-driven industries will find analytics masters programs particularly relevant. These programs build advanced skills in data analysis, a natural extension of a strong math foundation, and are increasingly valuable in sectors like finance, technology, and healthcare.

For those seeking accessible entry points into business education, understanding the easiest mba program options could help balance academic rigor with a smooth transition from mathematics study to leadership roles. Together, these pathways illustrate the diverse opportunities for math graduates to enhance their qualifications and career prospects through related online degrees.

Best Scientists Citing Ben Hambly

Trending Scientists