The Impact of Artificial Intelligence & Machine Learning on the Alternatives Industry

On July 16, 2019 the New York Alternative Investment Roundtable featured a panel on artificial intelligence and machine learning and their impact on the alternative investment industry.

Following is a list of resources produced by some of the individuals who took part in the panel. The list was compiled by Rick Roche, managing director of Little Harbor Advisors, who moderated the panel.

Olga Kokareva – Quanstellation. Profile on TabbForum:


Paul Lucek – Ridgedale Advisors, LP.

  • “Quantitative Approaches to Capturing Commodity Risk Premiums {Commodity Convergent/Divergent Solutions}, 2013. Request a copy for Paul at Ridgedale Advisors.
  • “HFOF Allocations Using a Convergent and Divergent Strategy Approach”, Mark Rosenberg et al., The Journal of Alternative Investments, Summer 2004.
  • Keywan Rasekhschaffe, PhD – Gresham Investment Management LLC.
  • “Machine Learning for Stock Selection” by Keywan Rasekhschaffe, PhD and Bob Jones at System Two Advisors, Mar 4, 2019. Available at Social Science Research Network:


Gordon Ritter, PhD – Professor, Buy-side Quant/PM:

  • Gordon Ritter’s search results on Social Science Research Network (SSRN) six papers:
  • “Machine Learning for Trading”, Gordon Ritter, PhD Aug 14, 2017. Available at SSRN:
  • “Microstructure Trading with a Long-Term Utility Function”, co-authored by Gordon Ritter and Elie Benveniste, Oct 24, 2017
  • Big Data and Machine Learning in Quantitative Investment, Tony Guida, editor, John Wiley & Sons, 2019, Chapter 12, “Reinforcement Learning in Finance” p. 225-250)


Rick’s Recommended Reads for AI/Machine Learning in Investment Management:

  • JP Morgan’s 280-page rpt. – Big Data & AI Strategies: Machine Learning & Alternative Data Approach to Investing. (May 2017). Handiwork of JPM’s Quant Team led by Marko Kolanovic, PhD.
  • Inside the Black Box, A Simple Guide to Quantitative and High Frequency Trading, Rishi Narang, Wiley Finance Book, 2nd edition, 2013
  • Dark Pools: The Rise of the Machine Traders and the Rigging of the U.S. Stock Market, by Scott Patterson, Crown Business, 2013
  • The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It, Scott Patterson, Crown Business, 2010
  • A Man for All Markets: From Las Vegas to Wall Street, How I Beat the Dealer and the Market, Edward O. Thorp, PhD, Penguin Random House, 2017
  • Machine, Platform, Crowd, by Andrew McAfee and Erik Brynjolfsson, W. W. Norton & Company, 2017
  • Advances in Financial Machine Learning, Marcos Lopez de Prado, PhD, John Wiley & Sons, 2019
  • Prediction Machines, Agrawal, J. Gans, A, Goldfarb, HBR Press, 2018
  • “How to Pick a Quantitative Hedge Fund” by Man FRM, Sep 2017
  • “Rise of the Robots: Inside the World’s Fastest-Growing Hedge Funds”, Dani Burger, Bloomberg, July 28, 2017