Fin 285a: Computer Simulations and Risk Assessment

Blake LeBaron

Fall 2011

Lecture Notes

1. Introduction
   Course Introduction
   1. Demands for risk management tools
   2. Types of risk
2. Tools
   1. The Matlab computer language
      Danielson, appendix C
   2. Statistical tools and the financial bootstrap toolbox:
      1. Probability basics
         Danielson, appendix A
      2. Sampling, monte-carlo, and bootstrap
         
      3. Hypothesis tests
         American Scientist: Cosma Salizi, "The Bootstrap"
         Danielson, appendix A
3. Financial data review
   
   1. Financial data review
      Danielson, 1.1-1.2
   2. Stylized facts of financial data
      Danielson, 1.3-1.7
      NY Times: Sept 11, 2011, Market swings are becoming new standard
4. VaR analytics
   Danielson, 4.1-4.4
   1. VaR Basics
      
   2. VaR Issues
      
   3. Expected shortfall
      Danielson, 4.5
5. Estimating VaR
   Danielson, 5.1-5.3, 7.1,7.3.1
   1. Parametric methods
      
   2. Historical VaR
      
   3. Computational Methods
      
   4. Method comparisons
      Finger, How historical simulation made me lazy, Research Monthly, Riskmetrics, April 2006.
   5. Time aggregation
      Danielson, 4.6, 5.4
      Searching for lost decades
      LeBaron, Searching for Lost Decades, 2010.
   6. Extreme value theory
      Danielson, 9 (skim)
6. Volatility forecasting
   1. Modeling volatility
      Danielson, 2.1-2.3, 2.7-2.8
   2. Using volatility forecasts
      Danielson, 5.5
      
      1. Basic empirical conditional volatility
      2. Implied volatility and VIX
      3. High/low range information and realized volatility
7. Correlations and portfolios
   1. Correlations and portfolios
      Danielson, 7.4
   2. Copulas
      Danielson, 1.8
   3. Much ado about correlation
      New York Times, November 12th, handout: Markets in sync: Finding the downbeat
      Seeking alpha: Risk-on / risk-off trading
8. Fixed income and simple options
   Danielson, 7.2-7.3, light skim 6
   1. Bond and option pricing with simulation
   2. Options and partial risk hedges
9. Applications and examples
   1. Orange county
      Case: Orange county: Marthinsen, chapter 6
   2. Exotic options and path dependence
      
   3. Pairs trading
10. Default risk
    
    1. Measuring default risk
       
    2. Mortgages and structured products
       
    3. Case: The Gaussian Copula and residential mortgages
       Hull and White, The risk of tranches created from residential mortgages, Financial Analysts Journal, 66, No. 5, 2010.
       Salmon, F., Recipe for disaster: The formula that killed Wall Street. Wired Magazine (February 23), 2009.
11. Backtesting and stress testing
    Danielson, 8
12. More risks
    
    1. Operational risk
       Case: Barings Bank: Marthinsen, 7
    2. Liquidity risk
       Background: Hedge Funds
       Case: LTCM : Marthinsen, 8
       
13. Risk and regulation
    Summary, dangers, and crisis perspectives
    1. Danielson, 10
    2. Hull, The credit crunch of 2007: What went wrong? Why? What lessons can be learned?, University of Toronto, 2009.