- PhD (2007) Columbia University (Computer Science (Computational Finance))
- MS (2003) Columbia University (Financial Engineering)
- Other (2002) CFA Institute (Chartered Financial Analyst (CFA) Program)
- PhD (1993) University of Notre Dame (Economics)
Business and financial Analytics, Algorithmic Trading, Market Microstructure, International Finance, and Risk Management
Professor Germán Creamer’s research addresses applications of machine learning and social network (business analytics) algorithms to solve business problems, with an emphasis on finance. Among the areas in which he has been active: algorithmic trading, asset pricing based on news and corporate social networks (behavioral finance), energy trade networks, development of balanced scorecard for boards of directors, discovery of organizational hierarchy based on social networks and electronic communications, identity recognition and risk management, forecasting, risk management, and health economics.
In the area of algorithmic trading, Professor Creamer has introduced boosting as a proper method to combine and select financial indicators and generate trading rules. In the area of asset pricing, he has included social network indicators to forecast price trends. In the area of organizational structures, he has pioneered in the adoption of alternating decision trees to uncover relationships and factors that affect the organizational structure. In the area of identity recognition, he has designed algorithms to identify customers, work that received a patent.
2019-20 Visiting Scholar, Stern School of Business, NYU, NY
2003- Adjunct Associate Professor/lecturer, Columbia University, NY
1998-2002 Professor of finance and Associate Director for Research, Goldring Institute of International Business (1998-2002), Tulane University, New Orleans
1993-1995 Associate Professor, Latin American Faculty of Social Sciences (FLACSO) - Ecuador
He has also taught at Central University of Finance and Economics (China), UIBE (China) and in several Latin American business schools
2006-2009 Senior Manager – Manager, American Express. Information Management & Enterprise-wide Risk Management; Risk, Information and Banking Department. Design of enterprise systems capabilities for marketing and risk. Application of econometric and machine learning algorithms to consolidate, segment, analyze credit risk, and forecast consumers’ behavior.
1996-98 Finance Manager, Pacific Bank Financial Group, Ecuador. Implemented a strategic planning and management information system that incorporated financial and non-financial perspectives (balanced scorecard).
1992-93 Program Officer. United Nations Development Programme, Ecuador. Formulated, executed, and evaluated development programs funded by international organizations, such as the World Bank.
1991 Economic Consultant, United Nations Development Programme, Ministry of Development, Equatorial Guinea
1990-91 Economic Advisor to the President of Ecuador, United Nations Development Programme. Advised governments on macroeconomic policies and finance
- Finance Member
- Business Intelligence and Analytics Member
- Quantitative Finance Member
- Finance Chair
- Finance Committee, Board of Trustees Member
- Academic Coordinator, Master of Finance Chair
- Coordinator of the Assurance of Learning process for the Master of Finance Chair
- Main newspapers from Ecuador (El Universo) and Venezuela (El Nacional), and several top news websites from Venezuela: La Patilla, Noticiero Digital, and Reporte Catolico. Op-ed columnist
- Journal of Financial Data Science. Advisory board member
- Eastern Economics Association Conference. Program committee member
- ACM International Conference on AI in Finance. Program committee member
- Artificial Intelligence in Finance, a specialty of Frontiers in Artificial Intelligence. Review Editor
- Quantitative Finance Journal. Editor special issue
2017-2019 CEAI (RegTech and FinTech group of companies), advisor and research collaboration on problems of cyber-security, risk management and portfolio optimization using machine learning algorithms. http://ceai.io
2005 Abacus (hedge fund). Econometric and statistical analysis for investment and portfolio optimization.
2003 Magic Works (hedge fund). Evaluated trading strategies based on text analytics and machine learning.
Consultant for the United Nations, World Bank, and US Agency for International Development.
Program Committee member (additional): ACM International Conference on AI in Finance, 2021, 2021; Eastern Economics Association meetings, 2011-15, 18, 19, 20, 21; International Conference on Behavioral, Economic, and Socio-Cultural Computing, 2017, 2018.International Symposium on Methodologies for Intelligent Systems, 2017, 2018.Duke Forest Conference: Economics in the era of natural computationalism and big data, Duke University, Durham, NC, 2016. Computing in Economics and Finance Conference, Society for Computational Economics, Taipei, Taiwan, 2015. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, 2015. High Frequency Finance and Data Analytics Conference, Hoboken, NJ, 2011, 2019.
Knight's Capital Prize for Best Use of Data in the annual Algorithmic Trading competition run by the University College London, 2011.
Bright Idea Award, Stillman School of Business at Seton Hall University and the New Jersey Policy Research Organization,
2010 American Express Leadership Award on Innovation, 2007.
Biography published since 1998 at: “Who’s Who in the World”, “Who’s Who in Finance and Industry”, “Who’s Who in America?”, “Who’s Who in American Education “ (2004-; Marquis)-). Albert Nelson Marquis Lifetime Achievement Award (2018) (Marquis).
MacArthur Foundation / Institute of Peace Studies.Scholarship, University of Notre Dame, 1989.
Institute for the Study of World Politics Scholarship, 1989.
Kellogg Institute, University of Notre Dame, 1989.
Fulbright Scholar, 1986.
- American Finance Association Member
- Eastern Economics Association Member
Prepared proposal that led to the development of the Hanlon Financial System Lab: a $500,000+, multi-functional, institute level trading lab dedicated to the research and teaching of financial markets.
Publicis, Machine Learning in Digital Marketing, 2019-20 ($9,600)
Co-PI, Improving the Quality of Service and Reducing Costs for Medicaid Patients in Safety Net Hospitals, Nicholson Foundation, 2017-18 ($154,160).
Prepared proposal for the CFA University Affiliation Program (2016).
A hybrid algorithm to forecast energy futures, Stevens Institute, 2014 ($20,000).
Effects of news sentiment on volatility and return, Howe School Alliance of Technology Management, 2012 ($5,000).
News, corporate network and the Put Call ratio, Howe School Alliance of Technology Management, 2011 ($5,000).
Board of Regents, State of Louisiana, grant for establishing a “Risk Management System of Latin American Capital Markets”, 1999-2002.
Methods, systems, and computer program products for generating data quality indicators for relationships in a database, Publication number: US 2009/0094237 A1, Issued patent: US8060502 (Issue date Nov 15, 2011).
- Creamer, G.; Kim, K. S.; Reynolds, C. W. (1997). El Ecuador en el mercado mundial: el regionalismo abierto y la participacion del Ecuador en el Grupo Andino, el Tratado de Libre Comercio de Norteamerica y la Cuenca del Pacifico (vol. 49). Corporacion Editora Nacional.
- Castelnuovo, A.; Creamer, G.; Creamer, G. (1987). La desarticulacion del mundo andino. Quito: Abya-Yala Press - Pontificia Universidad Catolica del Ecuador.
- Creamer, G. (2019). Nonlinear forecasting of energy futures. Intelligent Methods and Big Data in Industrial Applications (pp. 3--14). Springer, Cham.
- Creamer, G.; Creamer, B. (2016). A nonlinear lead lag dependence analysis of energy futures: Oil, coal, and natural gas. Handbook of high-frequency trading and modelling in finance (pp. 61--71).
- Creamer, G. (2012). Using boosting for financial analysis and trading. Handbook of Modeling High Frequency Data in Finance. Wiley.
- Collado Soto, R. A.; Creamer, G. (2016). Time series forecasting with a learning algorithm: an approximate dynamic programming approach. 22nd International Conference on Computational Statistics (COMPSTAT).
- Creamer, G. (2016). Trading network and systemic risk in the energy market. 2016 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC) (pp. 1--6).
- Creamer, G.; Creamer, B. (2014). A non-linear dependence analysis of oil, coal and natural gas futures with Brownian distance correlation. Lakkaraju et al. Energy Market Prediction: Papers from the AAAI Fall Symposium. Technical Report FS-14-02, Washington DC (pp. 9--14).
- Creamer, B.; Creamer, G. (2013). Efficiency and trade network analysis of the electricity market: 1985-2005. 2013 International Conference on Social Computing (pp. 936--939).
- Creamer, B.; Creamer, G. (2013). Emissions abating technology adoption under the SO2 permit market: a social networks approach. 2013 International Conference on Social Computing (pp. 744--749).
- Creamer, G.; Ren, Y.; Nickerson, J. (2013). Impact of dynamic corporate news networks on asset return and volatility. 2013 International conference on social computing (pp. 809--814).
- Creamer, G.; Ren, Y.; Sakamoto, Y.; Nickerson, J. (2013). News and sentiment analysis of the european market with a hybrid expert weighting algorithm. 2013 International Conference on Social Computing (pp. 391--396).
- Xie, B.; Passonneau, R.; Wu, L.; Creamer, G. (2013). Semantic frames to predict stock price movement. Proceedings of the 51st annual meeting of the association for computational linguistics (pp. 873--883).
- Creamer, G. (2012). Portfolio Optimization and Corporate Networks: Extending the Black Litterman Model. International Conference on Complex Sciences (pp. 83--94).
- Creamer, G.; Ren, Y.; Nickerson, J. (2011). News, Corporate Network and Price Discovery. Workshop on Information in Networks (WIN). NYU Stern.
- Rowe, R.; Creamer, G.; Hershkop, S.; Stolfo, S. J. (2007). Automated social hierarchy detection through email network analysis. Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis (pp. 109--117).
- Creamer, G.; Rowe, R.; Hershkop, S.; Stolfo, S. J. (2007). Segmentation and automated social hierarchy detection through email network analysis. International Workshop on Social Network Mining and Analysis (pp. 40--58).
- Creamer, G.; Stolfo, S. (2006). A link mining algorithm for earnings forecast using boosting. Proceedings of the link analysis: dynamics and statics of large networks workshop on international conference on knowledge discovery and data mining (KDD), Philadelphia, PA.
- Stolfo, S. J.; Creamer, G.; Hershkop, S. (2006). A temporal based forensic analysis of electronic communication. Proceedings of the 2006 international conference on Digital government research (pp. 23--24).
- Creamer, G.; Freund, Y. (2004). Predicting performance and quantifying corporate governance risk for latin american adrs and banks. Proceedings of the Financial Engineering and Applications conference, MIT, Cambridge.
- Creamer, G.; Noe, T.; Spindt, P. (2000). Efficiency, performance and value-at-risk of Latin American banks in a process of economic integration. Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr)(Cat. No. 00TH8520) (pp. 92--96).
- Creamer, G. (1994). El programa de ajuste macroeconomico y la politica social en el Ecuador. Democracia y desarrollo. Memorias del VII Encuentro de Historia y realidad económica y social del Ecuador y América Latina (vol. 1, pp. 47--64). Cuenca, Ecuador.
- Creamer, G.; Houlihan, P. (2019). Leveraging Social Media to Predict Continuation and Reversal in Asset Prices. Computational Economics. Springer.
- Creamer, G.; Lee, C. (2019). A multivariate distance nonlinear causality test based on partial distance correlation: application to energy futures via SVM. Quantitative Finance: Special Issue on AI and Machine Learning in Finance (vol. 19, pp. 1531–1542).
- Ghoddusi, H.; Creamer, G.; Rafizadeh, N. (2019). Machine Learning in Energy Economics and Finance: A Review. Energy Economics (vol. 81, pp. 709-727).
- Houlihan, P.; Creamer, G. (2019). Leveraging a Call-Put Ratio as a Trading Signal. Quantitative Finance (5 ed., vol. 19, pp. 763-777).
- CREAMER, G.; Kazantsev, G.; Aste, T. (2019). Editors’ foreword for special issue Machine Learning and AI. Quantitative Finance (9 ed., vol. 19, pp. 1445-1448). HOBOKEN.
- Creamer, G.; Creamer, B. (2018). Emissions abating technology adoption in a coal trading network. Social Network Analysis and Mining (1 ed., vol. 8, pp. 1--12). Springer Vienna.
- Houlihan, P.; Creamer, G. (2017). Can sentiment analysis and options volume anticipate future returns?. Computational Economics (4 ed., vol. 50, pp. 669--685). Springer US.
- Houlihan, P.; Creamer, G. (2017). Risk Premium of Social Media Sentiment. The Journal of Investing (3 ed., vol. 26, pp. 21--28). Institutional Investor Journals Umbrella.
- Creamer, G. (2017). Network structure and market risk in the European equity market. IEEE Systems Journal (2 ed., vol. 12, pp. 1090--1098). IEEE.
- Creamer, G.; Ren, Y.; Sakamoto, Y.; Nickerson, J. (2016). A textual analysis algorithm for the equity market: The European case. The Journal of Investing (3 ed., vol. 25, pp. 105--116). Institutional Investor Journals Umbrella.
- Creamer, G. (2015). Can a corporate network and news sentiment improve portfolio optimization using the Black--Litterman model?. Quantitative Finance (8 ed., vol. 15, pp. 1405--1416). Taylor & Francis.
- Creamer, G. (2012). Model calibration and automated trading agent for euro futures. Quantitative Finance (4 ed., vol. 12, pp. 531--545). Taylor & Francis Group.
- Creamer, G. (2011). Linking entity resolution and risk. Eastern Economic Journal (1 ed., vol. 37, pp. 150--164). Palgrave Macmillan UK.
- Creamer, Germ\'an; Freund, Y. (2010). Automated trading with boosting and expert weighting. Quantitative Finance (4 ed., vol. 10, pp. 401--420). Taylor \& Francis.
- Creamer, G.; Freund, Y. (2010). Learning a board Balanced Scorecard to improve corporate performance. Decision Support Systems (4 ed., vol. 49, pp. 365--385). North-Holland.
- Creamer, G.; Freund, Y. (2010). Using boosting for financial analysis and performance prediction: application to s&p 500 companies, latin american adrs and banks. Computational Economics (2 ed., vol. 36, pp. 133--151). Springer US.
- Creamer, G.; Stolfo, S. (2009). A link mining algorithm for earnings forecast and trading. Data mining and knowledge discovery (3 ed., vol. 18, pp. 419--445). Springer US.
- Creamer, G. (2009). Using random forests and logistic regression for performance prediction of Latin American ADRS and banks. Journal of CENTRUM Cathedra (1 ed., vol. 2, pp. 24--36).
- Creamer, G.; Freund, Y. (2007). A boosting approach for automated trading. The Journal of Trading (3 ed., vol. 2, pp. 84--96). Institutional Investor Journals Umbrella.
- Creamer, G.; Stolfo, S.; others (2006). A Temporal Based Forensic Analysis of Electronic Communication. Digital Government Proceedings, San Diego, CA.
- Creamer, G. (2004). Open Regionalism in the Andean Community: Creation or Deviation of Commerce?. El Trimestre Economico (1 ed., vol. 71, pp. 45--71).
- Creamer, G. (2004). Regionalismo Abierto en la Comunidad Andina?` Creacion o Desviacion de Comercio?. El Trimestre Economico (pp. 45--71). El Fondo de Cultura Economica.
- Creamer, G. (2003). Open regionalism in the Andean Community: a trade flow analysis. World Trade Rev. (vol. 2, pp. 101).
- Creamer, G.; Leon, N.; Kenber, M.; Samaniego, P.; Buchholz, G. (1999). Efficiency of hospital cholera treatment in Ecuador. Revista Panamericana de Salud Publica (vol. 5, pp. 77--87). Organizacion Panamericana de la Salud.
QF301 Advanced financial time series & machine learning (former financial time series course)
QF302 Financial microstructure & trading strategies
FA590 Statistical Learning in Finance
BIA656/MGT787 Advanced Data Analytics and Machine Learning FIN620 Financial Econometrics
FIN705 Asset Pricing
FIN627 Investment Management
FE535 Introduction to Financial Risk Management
FE635 Financial Enterprise Risk Engineering
FE 670 Algorithmic trading strategies
FA 631 Investment, Portfolio Construction and Trading Analytics