ECON 424/AMATH 540:  Introduction to Computational Finance and Financial Econometrics

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Last updated: August 11, 2011

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
    6. characteristics of portfolios with risky assets
  3. Matrix Algebra
    1. Compute portfolio expected return and variance using matrix algebra
  4. Time Series Concepts
    1. covariance stationarity
    2. Autocorrelations
    3. MA(1) and AR(1) models
  5. Descriptive statistics
    1. histograms, boxplots, qq-plots
    2. sample statistics (univariate, bivariate, time series)
  6. Constant expected return model
    1. model assumptions and interpretation
    2. relationship to random walk model
    3. Monte Carlo simulation

Topics to be emphasized on the Final Exam

Constant expected return model
  1. estimation, standard errors and confidence intervals
  2. hypothesis testing (t-tests, normality tests, rolling estimation)

Introduction to portfolio theory

  • characteristics of portfolios with risky and riskless assets
  • portfolio frontier
  • efficient portfolios
  • global minimum and tangency portfolios
  • risk budgeting

Portfolio Theory with 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?

Final Exams