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Corepoint Partners

Expert Services and Consulting in Quantitative Finance and Financial Data Science

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  • Home
  • Past Engagements
    • Expert Witness
    • Financial Data Science
    • Consulting
  • About Us
    • Leadership
    • Publications
  • Contact Us

Publications


Selected Journal Articles 

“Black-Litterman and Beyond: The Bayesian Paradigm in Investment Management,” P. Kolm, G. Ritter, and J. Simonian, The Journal of Portfolio Management (to appear), 2021

“Factor Investing with Black-Litterman-Bayes: Incorporating Factor Views and Priors in Portfolio Construction,” P. Kolm and G. Ritter, The Journal of Portfolio Management, 47 (2), 113-126, 2020

“Deep Reinforcement Learning for Option Replication and Hedging,” J. Du, M. Jin, P. Kolm, G. Ritter, Y. Wang, and B. Zhang, The Journal of Financial Data Science, 2 (4), 44-57, 2020

“Greedy Online Classification of Persistent Market States Using Realized Intraday Volatility Features,” P. Nystrup, P. Kolm, and E. Lindström, The Journal of Financial Data Science, 2 (3), 25-39, 2020

“Modern Perspectives on Reinforcement Learning in Finance,” P. Kolm and G. Ritter, Journal of Machine Learning in Finance, 1 (1), 2020

“Dynamic Replication and Hedging: A Reinforcement Learning Approach,” P. Kolm and G. Ritter, The Journal of Financial Data Science, 1 (1), 159-171, 2020

“On the Bayesian Interpretation of Black–Litterman,” P. Kolm and G. Ritter, European Journal of Operational Research, 258 (2), 564-572, 2017

“60 Years of Portfolio Optimization: Practical Challenges and Current Trends,” P. Kolm, R. Tütüncü, F. Fabozzi, European Journal of Operational Research, 234 (2), 356-371, 2014

“Multiperiod Portfolio Selection and Bayesian Dynamic Models,” P. Kolm and G. Ritter, Risk, 28 (3), 50-54, 2014

“Hidden Noise Structure and Random Matrix Models of Stock Correlations,” I. Dimov, P. Kolm, L. Maclin, D. Shiber, Quantitative Finance, 12 (4), 567-572, 2012

Selected Books and Book Chapters

“Robo-Advisory: From Investing Principles and Algorithms to Future Developments,” A. Grealish and P. Kolm, to appear in the book Machine Learning in Financial Markets: A Guide to Contemporary Practice, Cambridge University Press, 2021

Mathematical Techniques in Finance, An Introduction, A. Sadr, John Wiley & Sons, 2021

“Smart Beta Investing for the Masses: The Case for a Retail Offering,” L. Huang and, P. Kolm, in the book Equity Smart Beta and Factor Investing for Practitioners, 395-410, John Wiley & Sons, 2019

“Cash Bonds and Futures”; “Interest Rate Swaps”; “Interest Rate Options” chapters in Capital Markets: Evolution of the Financial Ecosystem, Strumeyer et al., John Wiley & Sons, 2017

Quantitative Equity Investing: Techniques and Strategies, F. Fabozzi, S. Focardi, P. Kolm, John Wiley & Sons, 2010

Interest Rate Swaps and Their Derivatives, A Practitioner’s Guide, A. Sadr, John Wiley & Sons, 2009

Robust Portfolio Optimization and Management, F. Fabozzi, P. Kolm, D. Pachamanova, S. Focardi, John Wiley & Sons, 2007

Financial Modeling of the Equity Market: From CAPM to Cointegration, F. Fabozzi, S. Focardi, P. Kolm, John Wiley & Sons, 2006

Trends in Quantitative Finance, F. Fabozzi, S. Focardi, P. Kolm, CFA Research Foundation, 2006

Selected White Papers

“A Computationally Efficient Methodology for Computing Option-Adjusted Measures for Bond Futures Contracts,” A. Sadr and C. Xu, 2021

“Feature Selection in Jump Models,” P. Nystrup, P. Kolm, and E. Lindström, 2021

“On the Impact of Publicly Available News and Information Transfer to Financial Markets,” M. Jazbec, B. Pásztor, F. Faltings, N. Antulov-Fantulin, and P. Kolm, 2021

“Alternative Data in Investment Management: Usage, Challenges and Valuation,” G. Ekster and P. Kolm, Challenges and Valuation, 2020

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