My Lecture Note in Basic Econometrics

Topic: Returns; Volatility; The Nature of Regression Analysis

1. Investment returns
    (i) Expected returns from portfolio
    (ii) Two geometric average method for calculation
         (a) Product and root
         (b) Anti-log (average)
2. Investment risk
    (i) Volatility: Two techniques to determining
         (a) Historical volatility - past price change (backward looking)
         (b) Implied volatility - current option prices (forward looking)
    (ii) Geometric average method for calculation
         - Standard deviation
    (iii) Two ways to deal with changing (or stochastic) volatility
          (a) Use less historic daily data (one month)
          (b) Model the changing volatility
3. Important characteristics of data
    (i) Trends
         (a) Linear relationship
         (b) Non-linear relationship
    (ii) Propensity to deviate from those trends
         - Variance in the residuals
    (iii) "Hidden" relationship which improve predictability
          (a) Interactions
          (b) Autocorrelation
4. The Population Regression Function (PRF)
     (i) Equation: E(Y) = Beta1 + (Beta2 * X)
     (ii) Parameters
          (a) Intercept, Beta1
          (b) Slope, Beta2