Track: Quantitative Finance

The Quantitative Finance track prepares students for the rapidly evolving sector of quantitative finance. It emphasizes the use of mathematical and statistical logic over investor discretion. Through a series of lessons, members will develop a range of skills, including risk management, an understanding of derivatives, and the strategy creation process. Students will learn about careers in quantitative finance and engage with industry professionals through guest lectures.

Leadership

Student Leaders

Industry Advisors

  • Dustin Hebrank
    Dustin Hebrank

    Chief Financial Officer, Gulf Winds International
    Dustin on LinkedIn

  • Guillermo Diaz
    Guillermo Diaz, MBA, CFA

    Partner, Chacon Diaz & Di Virgilio Wealth Management
    Guillermo on LinkedIn

  • James DiVirgilio
    James Di Virgilio, CIMA, CFP

    Co-Founder, Chacon Diaz & Di Virgilio Wealth Management
    James on LinkedIn


Activities

  • Algorithmic Strategy Workshops – Hands-on sessions for developing and testing trading algorithms.
  • Quantitative Analysis Competitions – Challenges where students can showcase their skills in statistical analysis and financial modeling.
  • Guest Lectures from Quant Experts – Talks by industry professionals on the latest quantitative finance techniques and career advice.
  • Machine Learning in Finance Seminars – Explorations of how AI and machine learning are changing the finance landscape.
  • Quantitative Tools Training – Practical sessions on using advanced tools like Python for financial analysis.
  • Simulation Trading Floor Exercises – Real-time trading simulations to provide experiential learning.
  • Research Publication Discussions – Groups to discuss and critique the latest quantitative finance research papers.
  • Mentorship Program with Alumni Quants – Opportunities for students to be mentored by alumni working in quantitative roles.
  • Investment Strategy Think Tanks – Regular meetings to discuss and develop investment strategies using quantitative methods.