Dr. Steve Yang

ASSISTANT PROFESSOR
Building: Babbio Center
Room: 536
Phone: 201.216.3394
Email: syang14@stevens.edu
Website
Education

Ph.D. (Systems) University of Virginia
M.E. (Systems) University of Virginia
M.S. (C.S.) Virginia Tech
B.S. (Aero. Eng.) Beijing University of Aeronautics & Astronautics, China

Research

Microstructure, Behavioral finance, Portfolio optimization, Algorithmic trading, Financial systemic risk

General Information

Dr. Steve Yang is an Assistant Professor of the School of Business at Stevens Institute of Technology. He holds a Ph.D. in Systems Engineering from University of Virginia with concentration on Financial Engineering. His current research interests include market microstructure, behavioral finance, algorithmic trading, portfolio optimization, and agent based financial market simulation. He also received a M.E. degree in Systems Engineering from the University of Virginia and a M.S. degree in Computer Science Application from Virginia Tech. He graduated at the top of his class with a B.S. degree in Aerospace Engineering from the Beijing Institute of Aeronautics and Astronautics.

Dr. Steve Yang has worked with several major federal financial regulators such as, the Securities and Exchange Commission (SEC), the Commodity Futures Trading Commission (CFTC) and Treasury in the capacity as either a research consultant or system architect. As an expert in modeling algorithmic trading, he provides consulting services to the Chief Economist Office and the Division of Enforcement at the Commodity Futures Trading Commission in Washington DC. He served as a guest editor for Quantitative Finance and European Journal of Finance, as well as a NSF panelist. His research has been published on journals such as Journal of Banking & Finance, Quantitative Finance, Expert Systems with Applications, Neurocomputing, etc.

Professional Service

IEEE Computational Intelligence Society, Computational Intelligence in Finance and Economics Technical Committee

Consulting Service

Enforcement Division of the U.S. Commodity Futures Trading Commission Consultant  (2014-present) 

Professional Societies

The Institute for Operations Research and the Management Sciences (INFORMS), IEEE Computational Intelligence Society (CIS), American Finance Association (AFA)

Grants, Contracts & Funds

S.Y. Yang (PI), $80K, “Investment Banking Value Chain Modeling”, Accenture LLP, Co-PI with Dr. William Rouse and Mike Pennock, 2016.

S.Y. Yang (Co-PI), $470K, “Technical Leadership Development Framework”, DoD/DAU, Co-PI with Dr. Wilson Felder, 2016.

S.Y. Yang (PI), $50K, “Financial Transaction System Modeling with XBRL”, Northrop Grumman, 2016-2017.

S.Y. Yang (PI), $100K, “Elite Sourced Financial Information Modeling”, Northrop Grumman, 2014-2016.

S.Y. Yang (Co-PI), $35K, “Spoofing Detection and Methodology”, U.S. Commodity and Futures Commission, 2014-2015.

S.Y. Yang (Co-PI) , $20K, “Financial Fraud Detection with Unstructured Data”, Stevens Ignition Grant, with Dr. P.K. Subalachimi, 2014.

S.Y. Yang (Co-PI) , $68K, “High Frequency Trading White Paper”, IRRC, Co-PI with Dr. Khaldoun Khashanah and Dr. Ionut Florescu, 2013-2014.

S.Y. Yang (Co-PI), $32K, “Financial Big Data and Standardization”, SWIF, Co-PI with Dr. Suzanne Morsfield (Columbia University), 2013.

S.Y. Yang (PI), $35K, “Financial Market Simulation and Fraud Detection”, Northrop Grumman, 2013.

S.Y. Yang (PI), $96K, "HFT Trading Behavior Modeling and Fraud Detection Analytics", Commodity and Futures Trading Commission, 2012.

Selected Publications
Journals
  1. Steve Y. Yang, Fang-Chun Liu, Xiaodi Zhu, David C. Yen. (2018). "A graph mining approach to identify financial reporting patterns: An empirical examination of industry classifications", Decision Sciences, Wiley, 2018 (forthcoming).
  2. Steve Yang, Esen Onur. (2018). "The complexity of the interest rate SWAP market and its risk implications", Complexity, Wiley - Hindawi, Vol 2018, 20-32 DOI: 10.1155/2018/5470305.
  3. Steve Y. Yang; Yangyang Yu; Saud Almuhdi. (2018). "An investor sentiment reward-based trading system using Gaussian inverse reinforcement learning algorithm", Expert Systems with Applications, 114 388-401.
  4. Anqi Liu, Cheuk Yin Jeffrey Mo, Mark E. Paddrik, Steve Y. Yang. (2018). "An Agent-Based Approach to Interbank Market Lending Decisions and Risk Implications", Information, MDPI. 9 (6), 132-150.
  5. Steve Y. Yang, Anqi Liu, Jing Chen, and Alan Hawkes. (2018). "Applications of Bivariate Hawkes Process to Joint Modeling of Sentiment and Equity Return Events", Quantitative Finance, 18 (2), 295-310 .
  6. Maggie Chen, Alan Hawkes, Khaldoun Khashanah, David McMillan, Steve Yang. (2018). "Editors' foreword on 'Hawkes Processes in Finance'", Quantitative Finance, 18 (2), 191-192 .
  7. Saud Almahdi, Steve Y. Yang. (2017). "An adaptive portfolio trading system: A risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown", Expert Systems with Application, 87 (30), 267-279.
  8. Anqi Liu, Mark Paddrick, Steve Y. Yang and Xingjia Zhang. (2017). "Interbank Contagion: An ABM Approach to Endogenously Form Networks", DOI: 10.1016/j.jbankfin.2017.08.008, Journal of Banking and Finance.
  9. Steve Y. Yang, Sheung Yin Kevin Mo, Anqi Liu, Andrei Kirilenko. (2017). "Genetic programming optimization for a sentiment feedback strength based trading strategy", Neurocomputing, 264 (C), 29-41.
  10. Qiang Song, Anqi Liu, Steve Y. Yang. (2017). "Stock portfolio selection using learning-to-rank algorithms with news sentiment", Neurocomputing, 264 (C), 20-28 .
  11. Steve Y. Yang and Sheung Yin Kevin Mo. (2016). "Social media and news sentiment analysis for advanced investment strategies", Studies of Computational Intelligence, 636 237-272 .
  12. Sheung Yin Kevin Mo, Anqi Liu, Steve Y. Yang. (2016). "News Sentiment to Market Impact and its Feedback Effect", Environment Systems and Decisions, 36 (2), 158-166.
  13. Steve Y. Yang, Qiang Song, Sheung Yin Kevin Mo1, Kaushik Datta, and Anil Deane. (2015). "The Impact of Abnormal News Sentiment on Financial Markets", Journal of Business and Economics, 10 (6), 1682-1694.
  14. Steve Y. Yang, Sheung Yin Kevin Mo, Anqi Liu. (2015). "Twitter financial community sentiment and its predictive relationship to stock market movement", Quantitative Finance, 15 (10), 1637-1656.
  15. Steve Yang, Qifeng Qiao, Peter Beling, William Scherer and Andrei Kirilenko. (2015). "Gaussian process-based algorithmic trading behavior identification", Quantitative Finance, 15 (10), 1683-1703.
Conference Proceedings
  1. Qiang Song, Saud Almahdi, and Steve Y. Yang. (2017). "Entropy Based Measure Sentiment Analysis in the Financial Market", Proceedings of IEEE Computational Intelligence in Financial Engineering and Economics, Honolulu, Hawaii, 2017.
  2. Steve Y. Yang, Fang-Chun Liu, and Xiaodi Zhu. (2016). "Impact of XBRL on Financial Statement Structural Comparability", Proceedings of International Conference on Information Systems, Dublin 2016 .
  3. Xiaodi Zhu, Steve Y. Yang, and Somayeh Mozani. (2016). "Forecasting Equity Risk Using Firm Risk Disclosures", Proceedings of 2016 IEEE Symposium Series on Computational Intelligence, Athens, Greece, 2016 .
  4. Andrew Todd, Peter Beling, William Scherer, and Steve Y. Yang. (2016). "Agent-based financial markets: A review of the methodology and domain", Proceedings of IEEE Symposium Series on Computational Intelligence, Athens, Greece.
  5. George Polacek, Dinesh Verma, and Steve Y. Yang. (2016). "Influencing Message Propagation in a Social Network Using Embedded Boolean Networks: A Demonstration Using Agent-Based Modeling", 26th INCOSE International Symposium.
  6. Steve Y. Yang and Jinhyoung Kim. (2015). "Bitcoin Market Return and Volatility Forecasting Using Transaction Network Flow Properties", Proceedings of IEEE Symposium Series on Computational Intelligence, 2015, Cape Town, South Africa.
  7. Qiang Song, Anqi Liu, Steve Y. Yang, Anil Deane and Kaushik Datta. (2015). "An Extreme Firm-Specific News Sentiment Asymmetry Based Trading Strategy", Proceedings of IEEE Symposium Series on Computational Intelligence, 2015, Cape Town, South Africa .
  8. Steve Y. Yang, Qifeng Qiao, Peter A. Beling, and William T. Scherer. (2014). "Algorithmic Trading Behavior Identification Using Reward Learning Method", 2014 International Joint Conference on Neural Networks .
  9. Steve Y. Yang, Anqi Liu, and Sheung Yin Kevin Mo. (2014). "Twitter Financial Community Modeling using Agent Based Simulation", Proceedings of 2014 IEEE/IAFE Computational Intelligence in Financial Engineering and Economics Conference, London.
  10. Steve Y. Yang, Sheung Yin Kevin Mo, and Xiaodi Zhu. (2014). "An Empirical Study of the Financial Community Network on Twitter", Proceedings of 2014 IEEE/IAFE Computational Intelligence in Financial Engineering and Economics Conference, London.
  11. Kevin Mo, Mark Paddrik, and Steve Y. Yang. (2013). "A Study of Dark Pool Trading using Agent Based Modeling", 2013 IEEE Computational Intelligence in Financial Engineering and Economics, Singapore, Singapore.
  12. Steve Y. Yang, and Randy Cogill. (2013). "Balance Sheet Outliers Detection Using a Graph Similarity Algorithm", 2013 IEEE Computational Intelligence in Financial Engineering and Economics, Singapore, Singapore .
  13. Roy Hayes, Andrew Todd, A. Kirilenko, Peter Beling, and William Scherer. (2012). "Behavior based Learning in Identifying High Frequency Trading Strategies, Steve Y. Yang, Mark Paddrik", 2012 IEEE Computational Intelligence in Financial Engineering and Economics, New York City.
  14. Mark Paddrik, Roy Hayes, Andrew Todd, Steve Y. Yang, Peter Beling, and William Scherer. "An Agent Based Model of the E-Mini S&P 500", 2012 IEEE Computational Intelligence in Financial Engineering and Economics, New York City, USA .
  15. Roy Hayes, Mark Paddrik, Andrew Todd, Steve Y. Yang, Peter Beling, and William Scherer. (2012). "Agent Based Model of the E-MINI Future Market: Applied to Policy Decisions", 2012 Winter Simulation Conference, Berlin, Germany.
Courses
  • FE 610 Stochastic Calculus for Financial Engineers
  • FE 900 Masterís Thesis in Financial Engineering
  • FE 570 Market Microstructure and Trading Strategies
  • FE 670 Algorithmic Trading Strategies
  • FE 672 Advanced Market Structure and HFT Strategies