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Eric Zivot
Economics 483
Applied Econometric Modeling in Finance

Study Guide for Midterm and Final Exam

Fall 2003

Last updated: December 11, 2004

The final exam will cover all the material from the course syllabus. The final exam will be concept oriented but there will also be some calculation involved so bring a calculator. I will not ask you to do proofs or long derivations. The best place to start your studying is with the homework assignments. Solutions for the homework assignments are on the homework page. Check the Notes page for updates of the class lecture notes.

The exams will be closed book and closed note exam. However, I will allow one page (double sided) of handwritten or typed notes

Topics to be covered for the Midterm

  1. Return calculations
    1. simple and continuously compounded returns
    2. time aggregation
  2. Review of random variables
    1. Shape characteristics (mean, variance, skewness, kurtosis)
    2. quantiles
    3. normal distribution
    4. linear functions of random variables
    5. covariance and correlation
  3. Time Series Concepts
    1. covariance stationarity
    2. Autocorrelations
    3. MA(1) and AR(1) models
  4. Descriptive statistics
    1. histograms, boxplots, qq-plots
    2. sample statistics
  5. Constant expected return model
    1. model assumptions and interpretation
    2. relationship to random walk model
    3. estimation of parameters
    4. properties of estimators - bias and precision
    5. estimating standard errors - analytic formulas and the bootstrap
    6. confidence intervals
  6. Introduction to portfolio theory
    1. characteristics of portfolios with risky and riskless assets
    2. portfolio frontier
    3. efficient portfolios
    4. global minimum and tangency portfolios

Topics to be emphasized on the Final Exam

Portfolio Theory with Matrix Algebra

  • Compute portfolio expected return and variance using matrix algebra
  • Express Markowitz algorithm for finding efficient portfolios using matrix algebra
Single Index Model 
  • Can you interpret the single index regression: R = ai + bi*Rm + ei ?
  • How do you compute the covariance matrix using the single index model?
  • Estimating beta from observed return data
    • How do you use least square regression?
    • How do you interpret R-square from the regression?
    • How do you interpret the standard error of the regression?
    • How can you test simple hypotheses about a and b in the regression?
    • How are regression results for portfolios different than regression results for individual assets?
    • How do you compute the beta for a portfolio?
    • How do you interpret beta as a measure of portfolio risk? That is, what does it mean for an asset to have a beta less than 1, a beta greater than 1 and a beta equal to 1?
  • Suppose you compute the beta of an asset with respect to the tangency portfolio. What is the relationship between the expected return on the asset and the beta with respect to the tangency portfolio?
CAPM
  • What are the assumptions behind the CAPM?
  • What are the main implications of the CAPM?
  • What are the testable implications of the CAPM and how do you test them? How do you use the excess returns single index model Ri - rf = ai* + bi*(Rm - rf) + ei to test the CAPM?
  • What is the prediction test of the CAPM? 
  • What are some problems with the prediction test?
  • Can you interpret E[R] = rf + b*(E[Rm] - rf)?
  • What are the conclusion of some of the early tests of the CAPM?

Final Exams