Roy Hayes

University of Virginia

PhD Student

United States

  • University of Virginia

SCHOLARLY PAPERS

7

DOWNLOADS
Rank 22,917

SSRN RANKINGS

Top 22,917

in Total Papers Downloads

3,069

SSRN CITATIONS
Rank 45,309

SSRN RANKINGS

Top 45,309

in Total Papers Citations

7

CROSSREF CITATIONS

8

Scholarly Papers (7)

Actions:
Email selected abstracts
1.

Behavior Based Learning in Identifying High Frequency Trading Strategies

Number of pages: 8 Posted: 08 Nov 2011
Steve Y. Yang, Mark E. Paddrik, Roy Hayes, Andrew Todd, Andrei A. Kirilenko, Peter Beling and William Scherer
Stevens Institute of Technology, Government of the United States of America - Office of Financial Research, University of Virginia, University of Virginia, University of Cambridge - Finance, University of Virginia, Dept. of System & Information Engineering and IEEE Intelligent Transportation Systems Society
Downloads 1,769 (13,314)
Citation 2

Abstract:

Loading...

Limit order book, Inverse Reinforcement Learning, Markov Decision Process, Maximum likelihood, Price impact, High Frequency Trading

2.

An Agent Based Model of the E-Mini S&P 500 and the Flash Crash

Number of pages: 8 Posted: 23 Sep 2011 Last Revised: 18 Jul 2012
Mark E. Paddrik, Roy Hayes, Andrew Todd, Steve Y. Yang, William Scherer and Peter Beling
Government of the United States of America - Office of Financial Research, University of Virginia, University of Virginia, Stevens Institute of Technology, IEEE Intelligent Transportation Systems Society and University of Virginia, Dept. of System & Information Engineering
Downloads 575 (65,613)
Citation 9

Abstract:

Loading...

Agent Base, Flash Crash, S&P 500, Zero-Intelligence

3.

Effects of Limit Order Book Information Level on Market Stability Metrics

Journal of Economic Interaction and Coordination, Forthcoming, Office of Financial Research Working Paper No. 14-09
Number of pages: 27 Posted: 22 Aug 2015 Last Revised: 12 Nov 2015
Mark E. Paddrik, Roy Hayes, William Scherer and Peter Beling
Government of the United States of America - Office of Financial Research, University of Virginia, University of Virginia and University of Virginia, Dept. of System & Information Engineering
Downloads 229 (182,124)
Citation 1

Abstract:

Loading...

4.

Agent Based Model of the E-Mini S&P 500 Future: Application for Policy Making

Proceedings of the 2012 Winter Simulation Conference
Number of pages: 12 Posted: 19 Jul 2012 Last Revised: 20 Jun 2013
Roy Hayes, Mark E. Paddrik, Andrew Todd, Steve Y. Yang, Peter Beling and William Scherer
University of Virginia, Government of the United States of America - Office of Financial Research, University of Virginia, Stevens Institute of Technology, University of Virginia, Dept. of System & Information Engineering and IEEE Intelligent Transportation Systems Society
Downloads 223 (186,666)
Citation 8

Abstract:

Loading...

Agent Based Model, Agent, E-MINI S&P 500, Minimum Quote Life, Policy, Rule Making

5.

Revolutionizing Financial Engineering Education: Simulation-Based Strategies for Learning

Number of pages: 19 Posted: 08 Jan 2013 Last Revised: 19 Mar 2013
Matt Olfat, Mark E. Paddrik, Roy Hayes and Kari Wold
University of Virginia, Government of the United States of America - Office of Financial Research, University of Virginia and University of Virginia
Downloads 130 (294,973)
Citation 2

Abstract:

Loading...

market microstructure, financial engineering, simulation, education

6.

An Agent-Based Financial Simulation for Use by Researchers

Number of pages: 10 Posted: 12 Apr 2014 Last Revised: 17 Apr 2014
Roy Hayes, Andrew Todd, Nachapon Chaidarun, Scott Tepsuporn, Peter Beling and William Scherer
University of Virginia, University of Virginia, University of Virginia, University of Virginia, University of Virginia, Dept. of System & Information Engineering and University of Virginia
Downloads 115 (322,501)

Abstract:

Loading...

Agent-based, Finance, High Frequency Traders, Regulation, Policy

7.

Machine Learning Classifications of Player Behavior

Number of pages: 26 Posted: 22 Apr 2021
Morgan Freiberg, Kent McLaughlin, Adinda Ningtyas, Oliver Taylor, Roy Hayes, Stephen Adams and Peter Beling
affiliation not provided to SSRN, affiliation not provided to SSRN, Independent, affiliation not provided to SSRN, University of Virginia, affiliation not provided to SSRN and University of Virginia, Dept. of System & Information Engineering
Downloads 28 (628,128)

Abstract:

Loading...

Machine Learning