IEF 217a: Computer Simulations and Risk Assessment
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Transcript of IEF 217a: Computer Simulations and Risk Assessment
IEF 217a: Computer Simulations and Risk Assessment
1) Blake LeBaron
3) www.brandeis.edu/~blebaron/classes/ief217a
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 applications1) 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/Statistics2) Computer skills (enthusiasm)
3) Who can take this course?1) 2nd year MA, MBAi2) MSF, BA/MA3) 2nd year and beyond Ph.D
Readings/Software
1) Books1) Jorion, Value at Risk
2) Sigmon and Davis, Matlab Primer
2) Papers1) Brandeis Electronic Reserves
2) Password “gambles”
3) Software1) Matlab (personal version)
2) Internet (email/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 philosophy2) Tools3) Risk measures4) Financial meltdowns5) Value-at-Risk6) VaR methods7) VaR extensions8) Stress testing9) Time, dynamics, and uncertainty10) More finance examples11) Advanced monte-carlo methods12) Liquidity risk
Introduction and philosophy
1) Basic ideas of probability2) Quantifying risky situations
1) Expected values/St. Petersburg paradox2) Variance3) Histograms/distributions
3) Further questions about risk1) Frank Knight: Risk versus uncertainty2) Ellsberg paradox
4) Computing power and risk assessment
Tools
1) The Matlab computer language2) Probability basics3) Sampling, monte-carlo, and bootstrapping
Risk Measures
1) Histograms2) Variance3) Beta4) Value-at-Risk (VaR)5) Expected utility6) Time and risk7) Chaos and complexity8) Types of risk
Financial Meltdowns
Value-at-Risk
1) Computing VaR2) Interpreting VaR3) Time scaling4) Regulation and VaR5) Estimation errors
VaR Methods
1) Delta normal2) Historical simulation3) Monte-carlo4) Bootstrap
VaR Extensions
1) Testing VaR2) VaR and portfolios3) VaR and changing volatility
Stress Testing
Time, Dynamics, and Uncertainty
1) Multiperiod investments2) Retirement problems3) Dynamic trading strategies
Further Financial Examples
1) Short positions and VaR2) Exotic option pricing3) Portfolio selection
Final Topics
1) Advanced monte-carlo tools2) Liquidity risk