DAVID SWEET

• Teaching

  • Experimental Optimization in Quantitative Trading
      Guest lecture for Robo-Advisors & Systematic Investing, Prof. Vasant Dhar, NYU Stern School of Business, April 2024
  • Experimental Optimization
      Course for the AI and Data Analytics masters program at Yeshiva University, Summer 2023
  • Experimentation in Trading
      Guest lecture for Robo-Advisors & Systematic Investing, Prof. Vasant Dhar, NYU Stern School of Business, April 2023
  • Experimental optimization
      Course for the DAV masters program at Yeshiva University, Spring 2022
  • Experimental Optimization
      Guest lecture for Data Driven Organizations, Prof. Andrew Catlin, Yeshiva University, Fall 2021
  • Predictive Models
      Course in the AI masters program at Yeshiva University, Summer 2021
  • Guest lectures for Trading Strategies and Systems, Prof. Vasant Dhar, NYU Stern School of Business
    • Optimization of High-Frequency Trading Systems, Spring 2019
    • Optimization of High-Frequency Trading Systems, Spring 2018
    • Optimization of High-Frequency Trading Systems, Spring 2017
    • High Frequency Trading, Fall & Spring 2014

• Books

  • D. Sweet, Experimentation for Engineers: From A/B Testing to Bayesian Optimization (Manning Publications, 2023)
    • Get the code from GitHub
    • Order from and read online at Manning books
    • Order paperback or Kindle version from Amazon
    • Article from Yeshiva University, Katz School blog.
  • D. Sweet, et. al., KDE 2.0 Programming (MacMillan Publishing, 2000). [pdf]
  • Contributing author, Chs. 34-38, N. Wells, Special Edition: Using KDE (MacMillan Publishing, 2000).

• Papers

  • J. Ren, D. Sweet, Optimal Initialization of Batch Bayesian Optimization, Preprint arXiv:2404.17997 (2024).
  • D. Sweet, E. Ott, and J. A. Yorke, Topology in chaotic scattering, Nature 399, 315 (1999).
    • MoMath Exhibit (2018), (2024)
    • Related articles (2000)
  • D. Sweet, H. E. Nusse, J. A. Yorke, Stagger-and-Step Method: Detecting and Computing Chaotic Saddles in Higher Dimensions, Physical Review Letters 86, 2261 (2001).
  • More ...

• Podcasts & Presentations

  • Motivation to Experiment, a talk for AI for Good
  • Practical AI: Recommender systems and high-frequency trading
  • Datacast: Chaos Theory, High-Frequency Trading, and Experimentations at Scale
  • Test Guild Performance: Tuning Up with David Sweet
  • DevDiscuss: What a Quantitative Trader Can Teach You About A/B Testing and Beyond