Ionut Florescu (ifloresc)

Ionut Florescu

Research Professor

School of Business

Babbio Center 603
(201) 216-8909

Research

Probability and Statistics, Mathematics of Finance, Stochastic Processes, Stochastic Volatility Models.

General Information

Dr. Ionut Florescu is a Research Professor in Financial Engineering. He also serves as Director of the Financial Analytics program, and Director of the Hanlon Financial Systems Lab at Stevens. His research interest is concentrated primarily in the area of Stochastic Processes and applications to Finance, however his work is about applying sound mathematical modeling techniques to any area of science and engineering such as: Computer Vision, Cryptography, Geophysical Studies, Ocean studies, Weather forecasting, Biomedical Engineering, etc.

Dr. Florescu is working at Stevens since 2005, right after he obtained his Ph.D. in Statistics from Purdue University in December 2004. His education include a Bachelors in Mathematics (1996) and a Masters' in Stochastic Processes (1997) from University of Bucharest, Romania as well as a Masters in Computational Finance (Dec. 2001) from Purdue University.

Experience

Stevens Institute of Technology, Financial Engineering, Research Professor, Director of the Hanlon Financial Systems Laboratories, Director of the Financial Technology and Analytics program 2019 - present.

Stevens Institute of Technology, Financial Engineering, Research Associate Professor, Director of the Hanlon Financial Systems Lab 2012 - 2019.

Stevens Institute of Technology, Department of Mathematical Sciences, U.S.A. Assistant Professor Fall 2005 - Spring 2012.

Purdue University, Department of Statistics, U.S.A. Visiting Assistant Professor, Spring 2005. Teaching Assistant, Fall 1998 - Fall 2004.

Romanian Academy, Center for Mathematical Statistics, Bucharest, Romania. Research Assistant, Fall 1997 - Spring 1998.

University of Bucharest, Department of Physics, Romania. Lecturer, Fall 1997 - Spring 1998.

Institutional Service

  • FE Ph.D. committee Member
  • FA committee Chair
  • APAR Academic Planning and Resources Committee Member
  • FE Ph.D. Comprehensive Exam Committee Chair
  • Budget Advisory Committee Member
  • Faculty Senate Member
  • Academic Planning and Resources committee Chair
  • BI&A Committee Member
  • Faculty Senate Member
  • RETCOM member Member
  • Graduate Curriculum Committee Member
  • Faculty Senate Member

Professional Service

  • Mathematics (MSCI) Associate Editor
  • Frontiers in Applied Mathematics and Statistics, Mathematical Finance Associate Editor
  • Data Science in Finance and Economics Associate Editor
  • High Frequency Journal Editor in Chief
  • HF Finance and Data Analytics Main Conference Organizer

Innovation and Entrepreneurship

Ph.D. major advisor (graduated students):

Dan Wang, Thesis: Application of Deep Learning to Corporate Credit Rating, Ph.D. in Financial Engineering, December 2021, Current Position: Machine Learning and Data Science Lead at JP Morgan Asset Management

Thiago Winkler Alves, Thesis: A Laboratory Environment for Financial Markets, Ph.D. in Financial Engineering, August 2020, Current Position: Software Engineer at Interactive Brokers

Ziwen Ye, Thesis: Detecting, Analyzing and Categorizing Financial Events in High Frequency Trading and Its Application, Ph.D. in Financial Engineering, May 2020, Current Position: Postdoctoral Researcher at Tsinghua University School of Economics and Management, China

Parisa Golbayani Thesis: Application of statistical and machine learning techniques to detect rare events in high frequency financial data and assess corporate credit rating, Ph.D. in Financial Engineering, Dec 2019, Current Position: VP, Data Strategy & Analytics, RAMPP Quants, RBC Capital Markets

Amin Salighehdar Combining distinct measurements into a comprehensive indicator: a study in High Frequency finance and climatology, Ph.D. in Financial Engineering, June 2018, Current position: Vice President, Data Scientist Lead at JPMorgan Chase&Co

Honglei Zhao, Thesis: Pricing variance derivatives using trees, Ph.D. in Financial Engineering, May 2018, Current position: Morgan Stanley

Christopher Flynn, Thesis: Hurst parameter estimation of a discretely sampled Ito integral with fractional Brownian motion driven integrand, Ph.D. in Mathematical Sciences, Dec 2015. Current Position: Director of Machine Learning Systems at SimpleBet.

Kristina Krsteva, Thesis: Estimation and optimization of linear multi-factor models of stock returns and detection of an underlying regime-switching process, Ph.D. in Mathematical Sciences, Dec 2014. Current position: Vice-President at Goldman Sachs

Dragos Bozdog, Thesis: A study of rare events in high-frequency financial data, Ph.D. in Financial Engineering, Dec 2014. Current position: Deputy Director Hanlon Lab at Stevens Institute of Technology

Thomas Lonon, Thesis: Option Pricing Utilizing a Jump Diffusion Model with a Log Mixture Normal Jump Distribution, Ph.D. in Mathematical Sciences, May 2013. Current position: Teaching Associate Professor at Stevens Institute of Technology.

Forrest Levin. Thesis: Monte Carlo estimation of stochastic volatility for stock values and potential applications to temperature and seismographic data, Ph.D. in Mathematical Sciences, May 2010. Current position: Adjunct Instructor at Nassau Community College

Darryl Neil Penenberg. Thesis: Statistical tests for the autoregressive structure in a time series, Ph.D. in Mathematical Science, May 2010, (co-advisor with D. Dentcheva). Current position: CEO and owner at DNP Consultants

Ph.D. major advisor: Dan Wang (2022), Zhiyuan Yao, William Long (2024, both co-supervising with Chihoon Lee), Francesco Fabozzi (2024), Zhi Chen (2025, co-supervising with Zach Feinstein), You (Eric) Wang (2026, co-supervising with Zhenyu Cui)

Ph.D. Committee member: Ludmyla Rekeda (Ph.D. Mathematics 2005), Viorel Dragnea (Ph.D. Computer Sciences 2011), Laurentiu Sega (Ph.D. Mathematics, Purdue University, 2011), Luis Ortega (Ph.D. Financial Engineering, Stevens, 2013), Kristi Lee Luttrell (Ph.D., Mathematical Sciences, Stevens, 2013), Laksmhi Iswara Chandra Vidyasagar (Ph.D., Mathematical Sciences, Stevens, 2013), Eduardo Osorio (Ph.D. Mathematics, Rutgers, 2014), Eli Wolfhagen (Ph.D. mathematics, Stevens, 2015), May Wang Chao (Ph.D. Physics, Stevens, 2015), Monika M. Heinig (Ph.D. Mathematics, Stevens, 2015) Ph.D. Bartosz Luczynski (Ph.D. Computer Science, Stevens, 2015), Greg Stock (Ph.D. Mathematical Sciences, Stevens, 2017), Gary Engler (Ph.D. Mathematical Sciences, Stevens, 2017), Ying Zheng (Ph.D. Mathematical Sciences, Stevens, 2020), Qiang Wu (Ph.D. Operations Research, Rutgers University, 2018), Serkan Alkan (Ph.D. Financial Engineering, Stevens, 2019), Ying Zhang, (Ph.D. Mathematics, July 2020), Alexis Doucette (Ph.D. Mathematical Sciences, 2022).

Master theses major advisor:

Zhi Chen, FE August 2021 ``A sparsity algorithm with applications to corporate credit rating",
Siqi Jiang, BI\&A, May 2021 ``Multi-source default probability prediction framework applying attention mechanism'',
Sriram Kashyap Prasad, FE Dec 2020, ``Dynamic High Frequency trading algorithm'',
Timothy Stanton, FE Dec 2019, ``Predicting CRISPR Cas-9 Negative Selection Outcomes from sgRNA Sequences'',
Nikhil Nirhale, FE May 2018, `Estimation of the Hurst exponent in fractional Brownian motion driven volatility using high frequency data and option prices''
David Carnahan, FE May 2015,``Does a 130/30 Tangency Strategy give higher returns than a Long Only Strategy in the Chinese Stock Market''

Master Theses reader: Thomas Surowiec (Masters' Mathematics 2006), Gregory Stock (Masters' Mathematics 2007), Yuri Aldrich (Masters' Financial Engineering 2007), Hongwei Qiu (Masters' FE 2010), Dhananjay Salgaocar (Masters FE, 2019), Yunfeng Liu (Masters FE, 2019), Agathe Sadeghi (Masters' FE, 2020), Ruizhi Hao (Masters FE, 2021), Chung Chen (Masters FE, 2021), Qingyun Pei (Masters FE, 2022), Margarita Zaika (Masters FE, 2022).


Senior design project advisor:

Colin Baker, Robert Gummer, Yuri Veksler, David Yi, Michael Dooley, ``Investigating the suitability of ESG corporate rating'', 2021-2022
Bharddwaj Vemulapalli, Markus Zebrowski, Nikhil Shah, Sean Martin, Parsh Jain, ``SHIFT: Determining the Costs of Correlation'', 2020-2021
Michael J Di Pentima, Peter A Demkowicz, Christopher M Albano, Simon Mandel, ``Using volatility as a factor in portfolio construction'', 2020-2021
Sidharth Peri, Ella Crabtree, Jeffrey Eng, ``Determining the factors that influence the efficacy of a trading strategy'', Summer 2021
Xu, Binquan, ``Credit rating research'', University of Liverpool, Summer 2021
Apeksha Jain, Dec 2018, ``Feature selection in Credit Rating'', undergraduate thesis for Birla Institute of Technology and Science (BITS) Pilani, Goa Campus (co-advising with Mayanik Goel)
Matthew Murphy, Mike Wezyk, Arthur Krivoruk, Andrew Kubis, Laramie Regalado, ``Robo Advisor'', 2017-2018.
Morgan Baron, Kirk Deligiannis, Colin Harrier, Matt Hochberger, Boris Kocherov "Design of a Vision Guided Robotic Vehicle", 2007-2008, (co-advising with G. Kamberov and R. Stolkin), won the award for the best senior design project at Stevens 2008;
Alicia Welden and Fabian Michalczewski, ``Hierarchical scaling of forest dynamics to the landscape level: modeling of forest stand dynamics'' (2011) (co-advising with Nikolay Strigul),
Joe Trinsey ``Comprehensive Statistics for the game of Voleyball'' (2009)

Honors and Awards

I.W. Burr award for academic excellence and quality of the thesis research, May 2005.

Purdue Research Foundation Grant, Purdue University, August 2003 - December 2004.

Puskas Memorial Fellowship for the Academic Year 2002-2003, Purdue University Merit Scholarship, 1991-1997, University of Bucharest, Romania.

Grants, Contracts and Funds

NSF CRAFT [Center for Research toward Advancing Financial Technologies], "Extending, simulating and scaling decentralized exchanges made by automated market makers.", Co-PI, with Z. Feinstein (PI) and I. Barac (Co-PI), June 1 2023 - May 31 2024, ($100,000 )

ERASMUS+ Mobility Award, to give an 8 hour lecture to AUEB, November 21-25, 2022

NJ Opportunity Meets Innovation, Challenge Grant (NJ), 2021-2022 ($10,000)

CAPCO research grant to support creation of a market exchange replica to serve for research and teaching, 2020-2022 ($120,000)

UBS research grant to support corporate credit rating using machine learning research, 2018-2019, ($60,000)

Ignition Grant from Stevens Institute of Technology, PI, Aug 2017 - July 2018, ($12,000)

CME Foundation grant to support the research projects at the Financial Systems Center at Stevens, PI, July 2017-Dec 2017, $100,000

CME Foundation grant to support the research projects at the Financial Systems Center at Stevens, PI, April 2015-Dec 2016, $85,000

Investor Responsibility Research Center (IRRC) Institute grant for developing a white paper on the current status and future of the High Frequency Traders in the financial markets, co-PI, Aug 2013-Feb 2014, $59,940

Nvidia grant to develop GPU compute infrastructure based on Nvidia Tesla cards, and recognition of Stevens Institute as a Research Center in CUDA, PI, 8 GPU cards donated, market value at $28,000.

NSF-1309861 Conference on Modeling High Frequency Data in Finance 5; Fall 2013; Hoboken, NJ, Principal Investigator, June 1, 2013 - May 31, 2014 ($40,000).

NSF-1209054 Conference on Modeling High Frequency Data in Finance 4; Summer 2012; Hoboken, NJ, Principal Investigator, April 1, 2012 - March 31, 2013 ($44,410).

NSF-1106027 Collaborative research: Conference on Modeling High Frequency Data in Finance III; Summer 2011; Hoboken, NJ, Principal Investigator, April 1, 2011 - March 31, 2012 ($30,960).

Proposal "Rare events and connection with crash phenomena", (PI) submitted to CFTC, with K. Khashanah and D. Bozdog, partially funded by the School of Systems and Enterprises for collaboration with U.S. Commodity Futures Trading Commission (CFTC) May 15 - Oct 15, 2011 ($10,000).

NSF-1007650 Conference on Modeling High Frequency Data in Finance II; Summer 2010; Hoboken, NJ, Principal Investigator, April 15, 2010 - March 31, 2011 ($25,000).

Other related awards received from International Mathematical Union (IMU), American Statistical Association (ASA), Institute of Mathematical Statistics (IMS).

NSF-0907371 Conference on Modeling High Frequency Data in Finance; Summer 2009; Hoboken, NJ, Principal Investigator, March 15, 2009 - February 28, 2010 ($15,000).

Other related awards received from International Mathematical Union (IMU), American Statistical Association (ASA), Institute of Mathematical Statistics (IMS) and International Association of Financial Engineers (IAFE).

Patents and Inventions

Real-time tracking of non-rigid objects in image sequences for which the background may be changing, with Rustam Stolkin, US 8374388 B2, Feb 12, 2013.

Contributor to Polymorphic tracked vehicle, US 8333256 B2, Dec 18,2012.

Selected Publications

Book

    Book Chapter

    1. Bozdog, D.; Florescu, I.; Khashanah, K.; Wang, J. (2011). A study of persistence of price movement using High Frequency Financial Data. Handbook of Modeling High-Frequency Data in Finance (pp. 27-46). Wiley.
      https://www.wiley.com/en-us/Handbook+of+Modeling+High+Frequency+Data+in+Finance-p-9780470876886.
    2. Bozdog, D.; Florescu, I.; Khashanah, K.; Qiu, H. (2011). Construction of Volatility Indices using a Multinomial Tree Approximation Method.. Handbook of Modeling High-Frequency Data in Finance (pp. 97-116).
      https://www.wiley.com/en-us/Handbook+of+Modeling+High+Frequency+Data+in+Finance-p-9780470876886.

    Conference Proceeding

    1. Lee, C.; Yao, Z.; Florescu, I. (2024). Control in Stochastic Environment with Delays: A Model-based Reinforcement Learning Approach. International Conference on Automated Planning and Scheduling (ICAPS 2024).
    2. Alves, T. W.; Florescu, I.; Calhoun, G.; Bozdog, D. (2020). SHIFT: A Highly Realistic Financial Market Simulation Platform. 6th International Symposium in Computational Economics and Finance, Paris 2020. arXiv.
      https://arxiv.org/abs/2002.11158.
    3. Mago, D.; Salighehdar, A.; Parekh, M.; Bozdog, D.; Florescu, I. (2018). Liquidity risk and asset movement evidence from brexit. 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings (vol. 2018-January, pp. 1-8).

    Journal Article

    1. Mariani, M. C.; Tweneboah, O. K.; Bhuiyan, M. A.; Beccar-Varela, M. P.; Florescu, I. (2023). Classification of Financial Events and Its Effects on Other Financial Data. Axioms (4 ed., vol. 12).
    2. Alves, T. W.; Florescu, I.; Bozdog, D. (2023). Insights on the Statistics and Market Behavior of Frequent Batch Auctions. Special Issue "Statistical Methods of Analyzing Financial Equilibrium, Performance and Risk". Mathematics (5 ed., vol. 11). Basel: MDPI.
      https://www.mdpi.com/2227-7390/11/5/1223.
    3. Wang, D.; Chen, Z.; Florescu, I.; Wen, B. (2023). A sparsity algorithm for finding optimal counterfactual explanations: Application to corporate credit rating. Research in International Business and Finance (vol. 64).
    4. Wang, D.; Wang, T.; Florescu, I. (2022). Is Image Encoding Beneficial for Deep Learning in Finance?. IEEE Internet of Things Journal (8 ed., vol. 9, pp. 5617-5628).
    5. Chatterjee, R.; Florescu, I.; Gobayani, P.. A comparative study of forecasting Corporate Credit Ratings using Neural Networks, Support Vector Machines, and Decision Trees. The North American Journal of Economics and Finance (vol. 54, pp. 101251).
    6. Xiao, C.; Florescu, I.; Zhou, J. (2020). A comparison of pricing models for mineral rights: Copper mine in China. Resources Policy (vol. 65).
    7. Mariani, M. C.; Bhuiyan, M. A.; Tweneboah, O. K.; Beccar-Varela, M. P.; Florescu, I. (2020). Analysis of stock market data by using Dynamic Fourier and Wavelets techniques. Physica A: Statistical Mechanics and its Applications (vol. 537).
    8. Zhao, H.; Chatterjee, R.; Lonon, T.; Florescu, I. (2019). Pricing Bermudan Variance Swaptions Using Multinomial Trees. The Journal of Derivatives (3 ed., vol. 26, pp. 22--34). Institutional Investor Journals Umbrella.
      https://jod.pm-research.com/content/26/3/22.
    9. Ye, Z.; Florescu, I. (2019). Extracting information from the limit order book: New measures to evaluate equity data flow. High Frequency (1 ed., vol. 2, pp. 37-47). Wiley.
      http://dx.doi.org/10.1002/hf2.10029.
    10. Mariani, M. C.; Bhuiyan, M. A.; Tweneboah, O. K.; Gonzalez-Huizar, H.; Florescu, I. (2018). Volatility models applied to geophysics and high frequency financial market data. Physica A: Statistical Mechanics and its Applications (vol. 503, pp. 304-321).
    11. Zhao, Z.; Cui, Z.; Florescu, I. (2018). VIX derivatives valuation and estimation based on closed-form series expansions. International Journal of Financial Engineering (02 ed., vol. 05, pp. 1850020). World Scientific Pub Co Pte Lt.
      http://dx.doi.org/10.1142/s2424786318500202.
    12. Zhao, H.; Zhao, Z.; Chatterjee, R.; Lonon, T.; Florescu, I. (2017). Pricing Variance, Gamma, and Corridor Swaps Using Multinomial Trees. The Journal of Derivatives (2 ed., vol. 25, pp. 7--21). Institutional Investor Journals Umbrella.
      https://jod.pm-research.com/content/25/2/7.
    13. Salighehdar, A.; Liu, Y.; Bozdog, D.; Florescu, I. (2017). Cluster Analysis of Liquidity Measures in A Stock Market Using High Frequency Data. Journal of Management Science and Business Intelligence (2 ed., vol. 2, pp. 1-8). Houston, TX: Institute of Business Intelligence Information (IBII).
      http://ibii-us.org/Journals/JMSBI/V2N2/V2N2.html.
    14. Bozdog, D.; Florescu, I.; Khashanah, K.; Wang, J. (2011). Rare Events Analysis of High-Frequency Equity Data. Wilmott Journal (54 ed., vol. 2011, pp. 74-81).

    Poster presentation

    1. Luvishis, E.; Vemulapalli, B.; Walther, P.; Ronai, J.; Florescu, I. (2021). Financial Times Series Generation and Analysis with Generative Adversarial Network Algorithms. National Conference of Undergraduate Research Journal. NCUR 2021 .

    arX

    1. Alves, T. W.; Florescu, I.; Calhoun, G.; Bozdog, D. (2020). SHIFT: A Highly Realistic Financial Market Simulation Platform. 6th International Symposium in Computational Economics and Finance, Paris 2020. arXiv.
      https://arxiv.org/abs/2002.11158.