Syllabus and Lecture Notes
CF101: Introduction to Computational Finance

Tentative Syllabus:

1. Introduction
   what is computational finance?
   Synergy between computation and finance
2. Return and Risk
   Basic book-keeping
   Leverage
   Impact of profit and loss
3. Data science
   How do financial data look like?
   How to interpret them?
   How to turn data into information, and information into knowledge?
   This includes daily closing prices, stylized facts
4. Portfolio optimization in project selection
   Introduction to combinatorial explosion, a major limitation in computation
   (If there is time:)
   Portfolio optimization in finance
   Markowitz model and its limitations
   What happens when these assumptions are relaxed
5. Big data in finance
   What are their implications?
   How to handle them?
   Event-based approach to financial big data
6. Algorithmic trading
   How does a trading program look like?
   Why algorithmic trading?
   What is high frequency trading?
   Introduction to Directional Changes based algorithms
7. Modelling, simulation and machine learning
   What is modelling?
   Why modelling?
   How could simulation help?
   How machine learning makes all the difference
8. Machine learning, an introduction
   What can one 'learn' with computers?
   How to measure success in learning
9. Computational Finance in the real world
   subject to availability of external speakers
   Note that this lecture will be scheduled to fit the external expert's availability
10. Computational finance, applications and the future
    Where computational finance have made an impact?
    What is on the horizon?

Reading List

• Tsang, E.P.K., Economic markets need warning system to avert crashes, New Scientist, 18 April 2012
• Tsang, E.P.K., Computational intelligence determines effective rationality, International Journal on Automation and Control, Vol.5, No.1, January 2008, 63-66
• Tsang, E.P.K., Forecasting -- where computational intelligence meets the stock market, Frontiers of Computer Science in China, Springer, 2009, 53-63
• Tsang, E.P.K., New ways to understand financial markets, Working Paper WP046-10, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, October 2010
• Tsang, E.P.K., Computation in finance: potentials and limitations, Working Paper WP047-10, Centre for Computational Finance and Economic Agents (CCFEA), University of Essex, November 2010