Matthew Francis Dixon

Illinois Institute of Technology

Assistant Professor of Applied Math

Department of Mathematics

W 32nd St., E1 room 208, 10 S Wabash Ave, Chicago,

Chicago, IL 60616

United States

Illinois Institute of Technology - Stuart School of Business, IIT

10 West 35th Street, 18th Floor

Chicago, IL 60616

United States

SCHOLARLY PAPERS

21

DOWNLOADS
Rank 2,415

SSRN RANKINGS

Top 2,415

in Total Papers Downloads

20,311

SSRN CITATIONS
Rank 39,197

SSRN RANKINGS

Top 39,197

in Total Papers Citations

10

CROSSREF CITATIONS

9

Scholarly Papers (21)

1.

Classification-Based Financial Markets Prediction Using Deep Neural Networks

Algorithmic Finance, 2016.
Number of pages: 20 Posted: 30 Mar 2016 Last Revised: 09 Dec 2016
Matthew Francis Dixon, Diego Klabjan and Jin Bang
Illinois Institute of Technology, Northwestern University and Northwestern University
Downloads 9,850 (781)
Citation 18

Abstract:

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Deep Neural Networks, Algorithmic Trading, Commodity Futures, FX Futures

2.

The Four Horsemen of Machine Learning in Finance

Number of pages: 24 Posted: 24 Sep 2019
Matthew Francis Dixon and Igor Halperin
Illinois Institute of Technology and Fidelity Investments, Inc.
Downloads 3,399 (4,864)
Citation 4

Abstract:

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machine learning, asset management, optimal hedging, neural networks, price impact

3.

Implementing Deep Neural Networks for Financial Market Prediction on the Intel Xeon Phi

Number of pages: 6 Posted: 07 Jul 2015 Last Revised: 13 Sep 2015
Matthew Francis Dixon, Diego Klabjan and Jin Bang
Illinois Institute of Technology, Northwestern University and Northwestern University
Downloads 1,724 (14,602)

Abstract:

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machine learning, financial markets, many-core computing

4.

A High Frequency Trade Execution Model for Supervised Learning

Forthcoming in High Frequency
Number of pages: 27 Posted: 15 Nov 2016 Last Revised: 06 Dec 2017
Matthew Francis Dixon
Illinois Institute of Technology
Downloads 898 (38,051)
Citation 2

Abstract:

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Supervised Learning, High-Frequency Trading, Market Making, Algorithmic Finace

5.

Delta-Gamma Component VaR: Non-Linear Risk Decomposition for any Type of Funds

Number of pages: 12 Posted: 25 May 2015 Last Revised: 27 Sep 2021
Matthew Francis Dixon
Illinois Institute of Technology
Downloads 509 (79,850)

Abstract:

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Component VaR, Non-linear Risk, Investment Management, CTAs

6.

G-Learner and GIRL: Goal Based Wealth Management with Reinforcement Learning

Number of pages: 20 Posted: 20 Mar 2020 Last Revised: 23 Mar 2020
Matthew Francis Dixon and Igor Halperin
Illinois Institute of Technology and Fidelity Investments, Inc.
Downloads 501 (81,644)
Citation 1

Abstract:

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G-learning, goal based wealth management, imitation learning, reinforcement learning

7.

Industrial Forecasting with Exponentially Smoothed Recurrent Neural Networks

Number of pages: 30 Posted: 05 May 2020
Matthew Francis Dixon
Illinois Institute of Technology
Downloads 438 (95,223)

Abstract:

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times series modeling, recurrent neural network, exponential smoothing

8.

A Bayesian Approach to Ranking Private Companies Based on Predictive Indicators

Number of pages: 19 Posted: 30 Jun 2012 Last Revised: 28 Jan 2013
Matthew Francis Dixon and Jike Chong
Illinois Institute of Technology and University of California, Berkeley - Department of Electrical Engineering & Computer Sciences (EECS)
Downloads 406 (103,957)

Abstract:

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private equity, support vector machines, Bayesian analysis

9.

Deep Partial Least Squares for Empirical Asset Pricing

Number of pages: 48 Posted: 27 Jun 2022
Matthew Francis Dixon, Nick Polson and Kemen Goicoechea
Illinois Institute of Technology, University of Chicago - Booth School of Business - Econometrics and Statistics and Illinois Institute of Technology
Downloads 404 (104,563)

Abstract:

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Deep Learning, Partial Least Squares, Shrinkage, Empirical Asset Pricing, Conditional Latent Factor Models, Non-Linear Risk

10.

MLEMVD: A R Package for Maximum Likelihood Estimation of Multivariate Diffusion Models

Number of pages: 15 Posted: 03 Apr 2017 Last Revised: 19 Nov 2020
Matthew Francis Dixon
Illinois Institute of Technology
Downloads 403 (104,856)

Abstract:

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Maximum likelihood estimation, Heston, R

11.

Blockchain Analytics for Intraday Financial Risk Modeling

Number of pages: 25 Posted: 19 Jan 2019
Matthew Francis Dixon, Cuneyt Akcora, Yulia Gel and Murat Kantarcioglu
Illinois Institute of Technology, University of Texas at Dallas - Erik Jonsson School of Engineering and Computer Science, Department of Mathematical Sciences and University of Texas at Dallas - Erik Jonsson School of Engineering and Computer Science
Downloads 296 (146,821)
Citation 1

Abstract:

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Cryptocurrencies, Graph Analysis, Forecasting, Financial Risk, ICOs

12.

Acceleration of Market Value-at-Risk Estimation

Number of pages: 8 Posted: 28 Mar 2010
Jike Chong, Kurt Keutzer and Matthew Francis Dixon
University of California, Berkeley - Department of Electrical Engineering & Computer Sciences (EECS), University of California, Berkeley - Department of Electrical Engineering & Computer Sciences (EECS) and Illinois Institute of Technology
Downloads 288 (151,012)
Citation 2

Abstract:

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Value-at-risk, Monte-Carlo Simulation, Graphics Processing Units (GPUs), Parallel Computing

13.

Bitcoin Risk Modeling With Blockchain Graphs

Number of pages: 5 Posted: 14 Jun 2018
Cuneyt Akcora, Matthew Francis Dixon, Yulia Gel and Murat Kantarcioglu
University of Texas at Dallas - Erik Jonsson School of Engineering and Computer Science, Illinois Institute of Technology, Department of Mathematical Sciences and University of Texas at Dallas - Erik Jonsson School of Engineering and Computer Science
Downloads 276 (157,667)
Citation 2

Abstract:

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Cryptocurrencies, Graph Analysis, Forecasting, Financial Risk, GARCH, ICOs

14.

gpusvcalibration: A R Package for Fast Stochastic Volatility Model Calibration Using GPUs

Number of pages: 10 Posted: 13 Feb 2014
Matthew Francis Dixon, Sabbir Khan and Mohammed Zubair
Illinois Institute of Technology, Old Dominion University and Old Dominion University
Downloads 206 (208,982)

Abstract:

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15.

Accelerating Option Risk Analytics in R Using GPUs

Number of pages: 7 Posted: 26 Nov 2013 Last Revised: 12 Feb 2014
Matthew Francis Dixon, Sabbir Khan and Mohammed Zubair
Illinois Institute of Technology, Old Dominion University and Old Dominion University
Downloads 181 (234,347)
Citation 2

Abstract:

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Stochastic Volatility, Calibration, R, GPGPU computing

16.

OSTSC: Over Sampling for Time Series Classification in R

Number of pages: 33 Posted: 30 Nov 2017
Matthew Francis Dixon, Diego Klabjan and Lan Wei
Illinois Institute of Technology, Northwestern University and Illinois Institute of Technology
Downloads 156 (265,570)
Citation 3

Abstract:

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17.

Calibration of Stochastic Volatility Models on a Multi-Core CPU Cluster

Number of pages: 7 Posted: 05 Nov 2013
Matthew Francis Dixon and Mohammed Zubair
Illinois Institute of Technology and Old Dominion University
Downloads 132 (302,954)

Abstract:

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Calibration, Stochastic Volatility, Distributed Algorithms

18.

Takeuchi's Information Criteria as a Form of Regularization

Number of pages: 26 Posted: 16 Mar 2018 Last Revised: 18 Apr 2018
Matthew Francis Dixon and Tyler Ward
Illinois Institute of Technology and New York University (NYU)
Downloads 106 (354,119)

Abstract:

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regularization, information criterion, statistical inference

19.

Gaussian Process Regression for Derivative Portfolio Modeling and Application to CVA Computations

Number of pages: 31 Posted: 11 Feb 2019
Stéphane Crépey and Matthew Francis Dixon
Université d'Évry - Equipe d'Analyse et Probabilites and Illinois Institute of Technology
Downloads 73 (443,860)
Citation 1

Abstract:

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Gaussian Processes, Kriging, OTC Derivatives, CVA

20.

A Portable and Fast Stochastic Volatility Model Calibration Using Multi and Many-Core Processors

Number of pages: 6 Posted: 06 Oct 2014
Matthew Francis Dixon, Jorg Lotze and Mohammed Zubair
Illinois Institute of Technology, Xcelerit and Old Dominion University
Downloads 65 (471,612)

Abstract:

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Calibration, Stochastic Volatility, GPGPU

21.

Gaussian Process Regression for Derivative Portfolio Modeling and Application to Credit Valuation Adjustment Computations

Journal of Computational Finance, Vol. 24, No. 1, 2020
Number of pages: 36 Posted: 19 Jan 2021
Stéphane Crépey and Matthew Francis Dixon
Université d'Évry - Equipe d'Analyse et Probabilites and Illinois Institute of Technology
Downloads 0 (927,392)
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Abstract:

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Gaussian processes regression, surrogate modeling, mark-to-market cube, derivatives, credit valuation adjustment, uncertainty quantification.