1. The Role of Technology in Quantitative Trading Research AlgoQuant Haksun Li haksun.li@numericalmethod.com www.numericalmethod.com

2. Speaker Profile  Haksun Li  CEO, Numerical Method Inc.Numerical Method Inc.  Adjunct Assistant Professor, Dept. of Mathematics, National University of Singapore  Quantitative Trader/Analyst, BNPP, UBS  PhD, Computer Science, University of Michigan Ann Arbor  M.S., Financial Mathematics, University of Chicago  B.S., Mathematics, University of Chicago 2

3. The Ingredients in Quantitative Trading 3  Financial insights about the market  Mathematical skill for modeling and analysis  IT skill?

4. The Ideal 4-Step Research Process 4  Hypothesis  Start with a market insight  Modeling  Translate the insight in English into mathematics in Greek  Model validation  Backtesting  Analysis  Understand why the model is working or not

5. The Realistic Research Process 5  Clean data  Align time stamps  Read Gigabytes of data  Retuers’ EURUSD, tick-by-tick, is 1G/day  Extract relevant information  PE, BM  Handle missing data  Incorporate events, news and announcements  Code up the quant. strategy  Code up the simulation  Bid-ask spread  Slippage  Execution assumptions  Wait a very long time for the simulation to complete  Recalibrate parameters and simulate again  Wait a very long time for the simulation to complete  Recalibrate parameters and simulate again  Wait a very long time for the simulation to complete  Debug  Debug again  Debug more  Debug even more  Debug patiently  Debug impatiently  Debug frustratingly  Debug furiously  Give up  Start to trade

6. Research Tools – Very Primitive 6  Excel  Matlab/R/other scripting languages…  MetaTrader/Trade Station  RTS/other automated trading systems…

7. R/scripting languages Advantages 7  Most people already know it.  There are more people who know Java/C#/C++/C than Matlab, R, etc., combined.  It has a huge collection of math functions for math modeling and analysis.  Math libraries are also available in SuanShu (Java), Nmath (C#), Boost (C++), and Netlib (C).

8. R Disadvantages 8  TOO MANY!

9. Some R Disadvantages 9

10. R’s Biggest Disadvantage 10  You cannot be sure your code is right!

11. Productivity 11

12. Research Tool As Weapon in Trading Warfare 12 bare hand star traderExcelMatlab/R MT/TS AlgoQuant

13. AlgoQuant: Putting Together Ideas 13 moving average crossover portfolio optimization cointegration stoploss

14. AlgoQuant: In-Sample Calibration 14 (5, 250) (25, 250) (1, 2) ……

15. AlgoQuant: Out-Sample Backtesting 15 Historical data Monte Carlo simulation Bootstrapping Scenarios p&l distribution sensitivity analysis performance statistics

16. Industrial-Academic Collaboration 16  Where do the building blocks of ideas come from?  Portfolio optimization from Prof. Lai  Pairs trading model from Prof. Elliott  Optimal trend following from Prof. Dai  Moving average crossover from Prof. Satchell  Many more……

17. Free the Trader! 17 debugging programming data cleaning data extracting waiting calibrating backtesting