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Matthew Dixon

Matthew Dixon

Assistant Professor of Applied Mathematics

Phone: 

650.704.2977

Office: 

Robert A. Pritzker Science Center, Room 106E

Office Hours: 

Mondays 12:50 - 1:50 PM (PS 240)
Wednesdays 1:00 - 2:00 PM (PS 240)

Education 

Ph.D. in Applied Mathematics, Imperial College, London
M.Sc. in Parallel and Scientific Computation (with distinction), University of Reading,
M.Eng. in Civil and Environmental Engineering, Imperial College, London,

Expertise 

Computational finance, statistical machine learning, scientific computing, fintech

Awards 

Faculty Innovation Award, Fall 2018

Publications 

SELECTED PUBLICATIONS

M.F. Dixon, N. Polson and V. Sokolov, Deep Learning for Spatial-Temporal Modeling: Dynamic Traffic Flows and High Frequency Trading, to appear in Applied Stochastic Models in Business and Industry, 2018

M.F. Dixon, A High Frequency Trade Execution Model for Supervised Learning, High Frequency, 1(1), pp. 32-52, 2018.

C. Akcora, M.F. Dixon, Y. Gel and M. Kantarcioglu, Bitcoin Risk Modeling With Blockchain Graphs, to appear in Economic Letters, 2018. 

M.F. Dixon, Sequence Classification of the Limit Order Book using Recurrent Neural Networks, J. Computational Science 24, pp. 277-286, 2017. 

M.F. Dixon, D. Klabjan, and J. H. Bang, Classification-based Financial Markets Prediction using Deep Neural Networks, Algorithmic Finance 6(3-4), pp. 66-99, 2017. 

M.F. Dixon, J. Chong and K. Keutzer, Accelerating Value-at-Risk Estimation on Highly Parallel Architectures, Concurrency Computat.: Pract. Exper 24(8), Wiley, pp. 895-907, 2012.

 

Grants 

Intel funded research in computational finance