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

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Presentation transcript:

IEF 217a: Computer Simulations and Risk Assessment 1)Blake LeBaron 3) 4)TA: Ritirupa Samanta

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

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

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

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

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 ( /web)

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

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

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

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

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

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

Financial Meltdowns

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

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

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

Stress Testing

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

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

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