Introduction to Quantitative Investment, 201310


Introduction to Quantitative Investment 2013, videos, one year access, a password will be sent to you: USD $300.00

$300.00Add to cart



This course introduces students to quantitative investment. A “quant” portfolio manager or a trader usually starts with an intuition or a vague trading idea. Using mathematics, s/he turns the intuition into a mathematical trading model for analysis, back testing and refinement. When the quantitative investment model proves to be likely profitable after passing rigorous statistical tests, the portfolio manager implements the model on a computer system for automatic execution. In short, quantitative investment is the process where ideas are turned into mathematical models and then coded into computer programs for systematic trading. It is a science where mathematics and computer science meet. In this course, students study investment strategies from the popular academic literature and learn the fundamental mathematics and IT aspects of this emerging field. After satisfactorily completing this course, the students will have an overview of the necessary quantitative, computing, and programming skills in quantitative investment.


Course Outline

There are a total of 8 lectures, each running for 3 hours.

Session Topics Readings Videos
1 Technical analysis: linear trading rules Lecturer handout YouTube
2 (lab) Programming a hidden Markov chain, a trend following strategy Lecturer handout Adobe
3 Trading basket construction Lecturer handout Adobe
4 (lab) Programming a cointegration model; basket creation; parameter sensitivity analysis Adobe
5 Optimal trading strategies Lecturer handout Adobe
6 (lab) Programming a trading strategy; parameter calibration Lecturer handout Adobe
7 Portfolio optimization & risk management Lecturer handout Adobe (part 1)
Adobe (part 2)
Adobe (part 3)
8 (lab) Programming to optimize a portfolio


Recommended For

  • Portfolio managers who wish to apply their mathematical and statistical strengths in the trading arena
  • Algorithmic traders who seek a deeper appreciation of mathematics and programming
  • Regulators, risk managers and auditors who need a good understanding of the nature of quantitative analysis
  • Anyone who aspires to become a quantitative trader


Preferred Background

  • Some experience in trading is preferred but not essential
  • University level mathematics and statistics
  • Programming experience


Recommended Readings

Numerical Method’s collection of Quantitative/Algorithmic Trading Literature


Student Projects


Student Feedback



Prof. Haksun Li

Prof. Haksun Li is the CEO of Numerical Method Inc., a quantitative trading research and analytic consulting company, which serves brokerage houses and funds all over the world, multinational corporations, very high net worth individuals and gambling groups. Prior to this, Prof. Li was a quantitative trader/quantitative analyst with multiple investment banks. He has worked in New York, London, Tokyo, Singapore and Hong Kong. Prof. Li has a B.S. and M.S. in Pure and Financial Mathematics from the University of Chicago, an M.S. and a Ph.D. in Computer Science & Engineering from the University of Michigan, Ann Arbor. Prof. Haksun Li is/was an adjunct professor with multiple universities. He taught at the National University of Singapore (Mathematics), Nanyang Technological University (Business School), FuDan University (Economics), as well as Hong Kong University of Science and Technology (Mathematics).


Language of Instruction




  • Online class available
  • Peking University, Beijing China, PRC



RMB 20,000.00 for classroom participation or USD 3,200.00 for online participation.



  • Online: Oct 1, Oct 2, Oct 8, Oct 9, Oct 15, Oct 16, Oct 22, Oct 23, 8 – 11pm, EST (New York time) 2013
  • Peking University: Oct 19, Oct 20, Oct 26, Oct 27, Nov 2, Nov 3, Nov 9, Nov 10, 2013, 2 – 5pm CST (Beijing time)


For Enquiries:

Please email


Introduction to Quantitative Investment 2013, videos, one year access, a password will be sent to you: USD $300.00

$300.00Add to cart