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Dr. Steve Y. Yang Assistant Professor Stevens Institute of Technology Office: Babbio 536 Phone: (201) 216-3394 (w) Email: STEVE.YANG@STEVENS.EDU |
Research
interests:
Market microstructure, algorithmic
trading, behavioral finance, portfolio optimization, and agent
based financial market/system modelling.
Ph.D. in Systems Engineering
Concentration:
Financial Engineering
School of Engineering &
Applied Science, Charlottesville, VA, USA
University of Virginia
M.E. in System Engineering
Concentration: Engineering Management
School of Engineering & Applied
Science Charlottesville, VA, USA
University of Virginia
M.S. Computer Science Application
Concentration: Software Engineering
Virginia Polytechnic Institute & State University, Blacksburg,
VA, USA
Virginia Tech
B.S. Aerospace Engineering
Beijing Institute of Aeronautics & Astronautics, Beijing,
China
Selected Journal Publications:
1. A graph mining approach to identify financial reporting patterns: An empirical examination of industry classifications, Steve Y. Yang, Fang-Chun Liu, Xiaodi Zhu, David C. Yen, Decision Sciences, 2018, DOI: https://doi.org/10.1111/deci.12345
2. The complexity of the interest rate SWAP market and its risk implications, Steve Yang, Esen Onur, Complexity, Vol. 2018, DOI: 10.1155/2018/5470305
3. An investor sentiment reward-based trading system using Gaussian inverse reinforcement learning algorithm, Steve Y. Yang, Yangyang Yu, and Saud Almaldi, Expert Systems with Applications, Vol 114C(2018), DOI: 10.1016/j.eswa.2018.07.056
4. An Agent-Based Approach to Interbank Market Lending Decisions and Risk Implications, Anqi Liu, Cheuk Yin Jeffrey Mo, Mark E. Paddrik, and Steve Y. Yang, Information, Vol 9(6), 132, 2018, DOI: 10.3390/info9060132
5. Applications of a Multivariate Hawkes Process to Joint Modeling of Sentiment and Market Return Events, Steve Y. Yang, Anqi Liu, Chen Jin, Alan Hawkes, Quantitative Finance, Vol 18(2), pp.295-310, 2017, DOI: 10.1080/14697688.2017.1403156
6. Editors’ foreword on ‘Hawkes Processes in Finance’, Maggie Chen, Alan Hawkes, Khaldoun Khashanah, David McMillan, Steve Yang, Quantitative Finance, 18(2), pp. 191–192, 2018, DOI: 10.1080/14697688.2018.1404804
7. Interbank Contagion: An Agent-based Model Approach to
Endogenously Formed Networks, Anqi Liu, Mark Paddrik, Steve Y. Yang, Xingjia Zhang, Journal of Banking and Finance, SI:IFABS 2017, DOI: 10.1016/j.jbankfin.2017.08.008
8. An adaptive portfolio trading system: A risk-return portfolio optimization using recurrent reinforcement learning with expected maximum drawdown
, Saud Almaldi, Steve Y. Yang, Expert Systems with Applications, Vol 87 (30), pp. 267–279, 2017, DOI: 10.1016/j.eswa.2017.06.023
9. Stock portfolio selection using learning-to-rank
algorithms with news sentiment, Qiang Song, Anqi Liu, Steve Y. Yang, Neurocomputing 264C (2017) pp. 20-28, (Submitted 2016) 2017, DOI: 10.1016/j.neucom.2017.02.097
10. Genetic programming optimization for a sentiment feedback strength based trading strategy, Steve Y. Yang, Sheung Yin Kevin Mo, Anqi Liu, Andrei Kirilenko, Neurocomputing 264C (2017) pp. 29-41, (Submitted 2015) 2016, DOI: 10.1016/j.neucom.2016.10.103
11. Social media and news sentiment analysis for advanced investment strategies, Steve Y. Yang and Sheung Yin Kevin Mo (2015), Studies of Computational Intelligence, (Submitted 2015) 2016, Vol. 636 pp. 237-272
12. The Impact of Abnormal News Sentiment on Financial Markets, Steve Y. Yang, Qiang Song, Sheung Yin Kevin Mo1, Kaushik Datta, and Anil Deane, Journal of Business and Economics, Vol 6 (10), P. 1682-1694, 2015.
13. News Sentiment to Market Impact and its Feedback Effect, Sheung Yin Kevin Mo, Anqi Liu, Steve Y. Yang. Environment Systems and Decisions, (submitted 2015) 2016, DOI:10.1007/s10669-016-9590-9
14. Twitter financial community sentiment and its predictive relationship to stock market movement, Steve Y. Yang, Sheung Yin Kevin Mo, Anqi Liu. Quantitative Finance, Vol 15 (10), P. 1637-1656, (Submitted 2014) 2015 DOI: 10.1080/14697688.2015.1071078,
15. Gaussian process-based algorithmic trading strategy identification,
Steve Yang, Qifeng Qiao, Peter Beling, William Scherer and Andrei Kirilenko, Quantitative Finance, Vol 15(10) 1683-1703, (Submitted 2013) 2015, DOI: 10.1080/14697688.2015.1011684
Selected Conference Publications:
1. Entropy Based Measure Sentiment Analysis in the
Financial Market, Qiang Song, Saud Almahdi, and Steve Y. Yang, Proceedings of IEEE Computational Intelligence in Financial Engineering and Economics, Honolulu, Hawaii, 2017.
2. Forecasting Equity Risk Using Firm Risk Disclosures, Xiaodi Zhu, Steve Y. Yang, and Somayeh Mozani, Proceedings of IEEE Computational Intelligence in Financial Engineering and Economics, Athens, Greece, 2016.
3. Agent-based financial markets: A review of the methodology and domain, Andrew Todd, Peter Beling, William Scherer and Steve Y. Yang, Proceedings of IEEE Computational Intelligence in Financial Engineering and Economics, Athens, Greece, 2016.
4. Impact of XBRL on Financial Statement Structural Comparability, Steve Y. Yang, Fang-Chun Liu, and Xiaodi Zhu, Proceedings of International Conference on Information Systems, Dublin 2016.
5. Social media and news sentiment analysis for advanced investment strategies, Steve Y. Yang and Sheung Yin Kevin Mo, Sentiment Analysis and Ontology Engineering: An Environment of Computational Intelligence, 2015, Springer ISBN 978-3-319-30319-2
6. Influencing Message Propagation in a Social Network Using Embedded
Boolean Networks: A Demonstration Using Agent-Based Modeling, George Polacek, Dinesh Verma, and Steve Y. Yang, 26th INCOSE International Symposium. Vol. 26. No. 1. 2016
7. Bitcoin Market Return and Volatility Forecasting Using Transaction Network Flow Properties, Steve Y. Yang and Jinhyoung Kim, Proceedings of 2015 IEEE Computational Intelligence in Financial Engineering and Economics Conference, 2015, Cape Town, South Africa
8. An Extreme Firm-Specific News Sentiment Asymmetry Based Trading Strategy, Qiang Song, Anqi Liu, Steve Y. Yang, Anil Deane and Kaushik Datta, Proceedings of 2015 IEEE Computational Intelligence in Financial Engineering and Economics Conference, 2015, Cape Town, South Africa
9. Algorithmic Trading Behavior Identification Using Reward Learning Method, Steve Y. Yang, Qifeng Qiao, Peter A. Beling, and William T. Scherer. Proceedings of 2014 International Joint Conference
on Neural Networks
10. Twitter Financial Community Modeling using Agent Based Simulation, Steve Y. Yang, Anqi Liu, and Sheung Yin Kevin Mo. Proceedings of 2014 IEEE Computational
Intelligence in Financial Engineering and Economics, London, United Kingdom
11. An Empirical Study of the Financial Community Network on Twitter, Steve Y. Yang, Sheung Yin Kevin Mo, and Xiaodi Zhu. Proceedings of 2014 IEEE Computational
Intelligence in Financial Engineering and Economics, London, United Kingdom
12. A Study of
Dark Pool Trading Using Agent Based Modeling, Kevin Mo, Mark Paddrik, and Steve Y. Yang. Proceedings of 2013 IEEE Computational
Intelligence in Financial Engineering and Economics, Singapore, Singapore
13. Balance Sheet
Outliers Detection Using a Graph Similarity Algorithm, Steve Y. Yang, and Randy Cogill. Proceedings of 2013 IEEE
Computational Intelligence in Financial Engineering and Economics, Singapore, Singapore
14. Behavior
based Learning in Identifying High Frequency Trading Strategies, Steve Y. Yang, Mark Paddrik, Roy Hayes, Andrew
Todd, A. Kirilenko, Peter Beling, and William Scherer. Proceedings of 2012 IEEE Computational
Intelligence in Financial Engineering and Economics, New York City, USA
15. An Agent
Based Model of the E-Mini S&P 500,
Mark Paddrik, Roy Hayes, Andrew Todd, Steve Y. Yang, Peter Beling, and William
Scherer; Proceedings of 2012 IEEE Computational Intelligence in Financial Engineering and
Economics, New York City, USA
16. Agent
Based Model of the E-MINI Future Market: Applied to Policy Decisions,
Mark Paddrik, Roy Hayes, Andrew Todd, Steve Y. Yang,
Peter Beling, and William Scherer; 2012 Winter Simulation Conference, Berlin,
Germany
Submitted/Working Paper:
An Agent-based Model for Bank Contagion Risk through Fire-sale, Lauren Zhang, Cheuk Mo, Steve Y. Yang 2018 (Working
paper)
Detecting market irrationality using news sentiment and information entropy, Anqi Liu, Jin Chen, Steve Yang 2017 (Working
paper)
A GARCH-Hawkes Jump Model: Self-excitation and Calibration, Jing Chen, Steve Y. Yang, Alan Hawkes 2017 (Working
paper)
Dark Pool Trading Mechanism and its Impact to Fundamental Investors, Steve Y. Yang, Jeffrey Cheuk Mo, Mark Paddrik 2016 (Working
paper)
Evidence from risk disclosures: Are banks transparent about their risks?, Xiaodi Zhu, Aparna Gupta, and Steve Yang 2018 (IRMC 2018 Conference; SSRN Working
paper)
Structural Comparability of Financial Statements, Elaine Henry, Fang-Chun Liu, Steve Yang, and Xiaodi Zhu, 2018 (SSRN Working
paper)
Presentations:
Evidence from risk disclosures: Are banks transparent about their risks?, Steve Yang, Internation Risk Management Conference (IRMC) 2018 Conference, Paris, Jun. 9th, 2018
Interest Rate Swap Market Complexity and its Risk Implications, Steve Yang, Internation Finance and Banking Society (IFABS) 2017 Conference, Oxford, Jul. 16th, 2017
Interest Rate Swap Market Modeling with Information Flow Networks, Steve Yang, Office of Financial Research, U.S. Treasury Invited Talk, Apr. 18th, 2017
Interest Rate Swap Market Network Complexity and its Risk Implications, Steve Yang, RPI Invited Talk, Mar. 25th, 2017
Interest Rate Swap Market Network Complexity and its Volatility Implications, Steve Yang, The U.S. Commodity Futures Trading Commission (CFTC), Nov. 7th, 2016
Interbank Contagion: An Agent-based Model for Banking System, Steve Yang, Federal Reserve Systems (FED), Oct. 23th, 2016
Impact of XBRL on Financial Statement Structural Comparability, Steve Yang, The Securities and Exchange Commission (SEC), August, 2016
Interbank Contagion with Suboptimal Bilateral Exposures: An ABM Approach to Endogenously Form Networks, Steve Yang, 2016 International Finance and Banking Society (IFABS) Conference, Barcelona, Spain
Feedback Effects of Financial Market in Simulation, Steve Yang, MIT Lincoln Lab, 2015, Boston, Massachusetts
Emerging Behavior of Financial Market, Steve Yang, Stevens-Accenture ACE Workshop, 2015, Hoboken, NJ
A critical and empirical examination of currently-used financial data collection processes and standards, Suzanne Morsfield, Steve Yang and Susan Yount, Initial Model & Pilot Study Results for SWIFT Institute Annual Conference 2014, London, UK
A graph mining approach to Big Financial Data problem in XBRL financial disclosures, Steve Yang, Invited speaker at 2014 XBRL International Conference, Orlando, FL, US
Emerging Complex Systems Behavior using a Bottom-up Approach in Finance, Steve Yang, KAIST Workshop at Stevens, U.S, June 2014
Twitter Financial Community Modeling using Agent Based Simulation, Steve Yang, IEEE CIFEr Conference 2014, London, UK
Emerging Behavior Pattern Identification and Prediction Using a Bottom-up Approach in Finance, Steve Yang and Peter Beling, FDIC, Washington DC, 2014
Elite Source Information Modeling for Financial Investment, Steve Yang,
Northrop Grumman Information Systems’ 2014 TechExpo in McLean, VA, US
Emerging Behavior Pattern Identification Using Social Media Twitter Sentiment Analysis, Steve Yang,
Accenture-AIB (Scottland) Workshop on Financial Analytics at Stevens Institute of Technology, U.S.
Financial Systemic Risk vs. Social Mood, Steve Yang,
Accenture-Fannie Mae Workshop on Financial Analytics at Stevens Institute of Technology, U.S.
Systemic Risk Modeling using a Bottom-up Approach in Finance, Steve Yang,
NSF CDDA Annual Conference 2014 at Stony Brook University, U.S. 2014
Balance sheet Based Outlier Detection, Steve Yang, Proceedings of
2013 IEEE Computational Intelligence Society Symposium Series, April, 2013
Balance sheet Based Outlier Detection, Steve Yang,
Proceedings of 2013 IEEE Computational Intelligence Society Symposium Series, April, 2013
Model
Financial Market Complexity, Steve Yang,
Financial Engineering Seminar at Stevens Institute of Technology, Feb, 2013
Decoding Genes of Algorithmic Trading Strategies, Steve Yang,
Division of Market Surveillance Seminar at Commodity Futures Trading Commission, July, 2012
Decoding Genes of Algorithmic Trading Strategies, Steve Yang,
Office of Chief Economist at Commodity Futures Trading Commission, March, 2012
Behavior
Based Learning in Identifying Algorithmic Trading Strategies, Steve Yang, Financial Engineering Seminar at
Stevens Institute of Technology, December, 2011
Agent Based E-Mini
S&P 500 Futures Market Simulation and Algorithmic Trading Strategies, Steve Yang, Mark Paddrik, Roy Hayes, Andrew Todd.
Colloquium Presentation at University of Virginia, August, 2011
Behavior
Based Learning in Identifying Algorithmic Trading Strategies, Steve Yang, Research Seminar at Commodity Futures
Trading Commission, July, 2011
CME GLOBEX
Trading System Incident and Economic Impact, Steve Yang, Commission Testimony/Hearing at Commodity Futures Trading
Commission, February, 2011
Commodity and
Futures Trading Data Standardization,
Steve Yang, Technology Seminar at Commodity Futures Trading Commission, April,
2009
Achieving
High Business Agility through Data Standardization, Steve Yang, Technical Fellow Seminar at Northrop
Grumman Corporation, July, 2008
Funding/Grants:
| PI | Financial Information Exchange Framework and Standards Modeling |
Northrop Grumman Corporation 2016-2017, USD50,000 |
| Co-PI | Framework for Technical Leadership Development |
DASD(SE)/SERC 2015-2016, USD475,000 |
| PI | Investment Banking Value Chain Modeling and Simulation |
Accenture 2015-2016, USD80,000 |
| PI | Methodology and Tools for Detecting Spoofing |
Commodity Futures Trading Commission 2014-2015, USD35,000 |
| PI | Market Elite Soured Data Modeling |
Northrop Grumman Corporation 2014-2016, USD100,000 |
| CoPI | Mining Financial Text Disclosures for Fraud Detection |
IGI Grant - ACT/SERC, Stevens 2014, USD20,000 |
| CoPI | The Impact of High Frequency Trading on Institutional Investing |
Investor Responsibility Research Center (IRRC) Institute 2013, USD68,000 |
| CoPI | Financial Standards and Big Data |
The Society for Worldwide Interbank Financial Telecommunication (SWIFT) 2013, USD32,000 |
| PI | Limit Order Book Modeling/Visualization |
Northrop Grumman Corporation 2013, USD35,000 |
| PI | Trade Based Fraud Detection Analytics |
Commodity and Futures Trading Commission, 2012, USD96,000 |
Awards:
·
Distinguish Summer Visiting Scholar, the Securities and Exchange Commission, 2016
·
Top Performer Award from School of Systems and Enterprises 2015
·
Top Performer Award from School of Systems and Enterprises 2013
·
Best Applied Paper Award 2012, Berlin
Winter Simulation Conference
·
Honorary Mention of
the Best Student Paper Award, 2012, Proceedings of IEEE Computational Intelligence in
Financial Engineering and Economics Conference, New York
·
Summer Fellowship
2010, University of Virginia
·
Scholarship 2009, Department
of Systems Engineering, University of Virginia
·
Emerging Leader Award 2009,
Northrop Grumman
·
Peak Performance Award 2005, Northrop Grumman
·
Timely Performance Award 2004, Northrop Grumman
Affiliations:
American Finance Association (AFA)
The Institute for Operations Research and the Management Sciences (INFORMS)
Institute
of Electrical and Electronic Engineers (IEEE Computational Intelligence
Society)
Teaching:
| FE 570 | |
| FE 610 | |
| FE 670 | |
| FE 622 |
Students Graduated:
Sheung Yin Kevin Mo, Ph.D. in Financial Engineering “Modeling the Impact of News and Social Media to Financial Markets”, Stevens Institute of Technology, Graduated May, 2015. Quantitative Management Associates, NJ, SE Best Doctoral Dissertation Award (2015)
Anqi Liu, “Financial Market Irrationality Detection and Trading Signals”, Ph.D. in Financial Engineering at Stevens Institute of Technology, Graduated May, 2017. Cardiff University, School of Mathematics, UK.
Qiang Song, “Relative Strength Based Portfolio Optimization Methods in Investment”, Ph.D. in Financial Engineering at Stevens Institute of Technology, Graduated August, 2017. Citi Group NYC.
Xiaodi Zhu, “Incomplete Information Revelation through Mining of Semantic Structures of Financial Statements and Unstructured Financial Disclosures”, Ph.D. in Financial Engineering at Stevens Institute of Technology, Graduated May, 2018. School of Business, New Jersey City University, US, SoB Best Doctoral Dissertation Award (2018).
Students on Track:
Saud Al Mahldi, “Reinforcement Learning and Recurrent Reinforcement Learning Based Portfoio Optimization”, Ph.D. in Financial Engineering at Stevens Institute of Technology, TBD
Xingjia Zhang, “Financial Systemic Risk Modeling with Agent-Based Behavioral Approach”, Ph.D. in Financial Engineering at Stevens Institute of Technology, TBD
Yangyang Yu, “An Inverse Reinforcement Learning Approach to Market’s Reaction to News Shocks”, Ph.D. in Financial Engineering at Stevens Institute of Technology, TBD
Gregory Cerisi, “Investor Overreaction/Underreaction Formed Yield Curve Premium Strategies”, Ph.D. in Financial Engineering at Stevens Institute of Technology, TBD.
Jeffrey Chuke Mo, “Financial Market Behavior Modeling Using Mean Field Games”, Ph.D. in Financial Engineering at Stevens Institute of Technology, TBD.
Patents:
Apparatus and Methods For Detecting Financial Statement Anomalies (U.S. Provisional Patent)