1. IEF 217a: Computer Simulations and Risk Assessment 1)Blake LeBaron 2)blebaron@brandeis.edu 3)www.brandeis.edu/~blebaron/classes/ief217a 4)TA: Ritirupa Samanta

2. Introduction 1)Description 2)Prerequisites 3)Readings 4)Computer issues 5)Grading 6)Outline

3. What is this course? 1)Computer 2)Probability/Statistics 3)Finance 4)Psychology/Philosophy

4. Topics 1)Computational tools 2)Probability basics 3)Finance applications 1)Value-at-Risk 2)Stress testing 3)Multiperiod investments 4)Dynamic trading strategies 5)Liquidity risk

5. Prerequisites 1)Required: 1)IEF 205 (basic finance knowledge) 2)Or Econ 171 for BA/MA students 2)Recommended: 1)Probability/Statistics 2)Computer skills (enthusiasm) 3)Who can take this course? 1)2 nd year MA, MBAi 2)MSF, BA/MA 3)2 nd year and beyond Ph.D

6. Readings/Software 1)Books 1)Jorion, Value at Risk 2)Sigmon and Davis, Matlab Primer 2)Papers 1)Brandeis Electronic Reserves 2)Password “gambles” 3)Software 1)Matlab (personal version) 2)Internet (email/web)

7. Computer Issues 1)Personal Computer (Windows) 2)Matlab student edition (cd rom: bookstore) 3)Can also use Sachar machines 4)Programs from course website

8. Grading 1)Problem sets (25%) 2)Midterm exam (30%) 3)Group project (20%) 4)Take home final (25%)

9. Course Outline 1)Introduction and philosophy 2)Tools 3)Risk measures 4)Financial meltdowns 5)Value-at-Risk 6)VaR methods 7)VaR extensions 8)Stress testing 9)Time, dynamics, and uncertainty 10)More finance examples 11)Advanced monte-carlo methods 12)Liquidity risk

10. Introduction and philosophy 1)Basic ideas of probability 2)Quantifying risky situations 1)Expected values/St. Petersburg paradox 2)Variance 3)Histograms/distributions 3)Further questions about risk 1)Frank Knight: Risk versus uncertainty 2)Ellsberg paradox 4)Computing power and risk assessment

11. Tools 1)The Matlab computer language 2)Probability basics 3)Sampling, monte-carlo, and bootstrapping

12. Risk Measures 1)Histograms 2)Variance 3)Beta 4)Value-at-Risk (VaR) 5)Expected utility 6)Time and risk 7)Chaos and complexity 8)Types of risk

13. Financial Meltdowns

14. Value-at-Risk 1)Computing VaR 2)Interpreting VaR 3)Time scaling 4)Regulation and VaR 5)Estimation errors

15. VaR Methods 1)Delta normal 2)Historical simulation 3)Monte-carlo 4)Bootstrap

16. VaR Extensions 1)Testing VaR 2)VaR and portfolios 3)VaR and changing volatility

17. Stress Testing

18. Time, Dynamics, and Uncertainty 1)Multiperiod investments 2)Retirement problems 3)Dynamic trading strategies

19. Further Financial Examples 1)Short positions and VaR 2)Exotic option pricing 3)Portfolio selection

20. Final Topics 1)Advanced monte-carlo tools 2)Liquidity risk