Lecture 1 Econometrics
Types of data (times series, cross-sectional, panel)
continuous and discrete data
cardinal, ordinal and nominal numbers
Statistical packages (returns in financial modelling, log returns)
Regression
Linear Regression/ Multiple Linear Regression
Ordinary Least Squares (OLS)
Population Regression function (PRF)
Lecture 2-3 Hypothesis Testing
T-test/ F-test
Confidence intervals
p-value
least squares assumptions
restricted and unrestricted regression
t and F-distribution
dummy variables
intercept / slope variables
interaction terms
Lecture 4-6 Testing Classical Assumptions
Gauss-Markov Theorem (OLS, BLUE)
Classic Assumption
Heteroscedasticity
White test
GQ test
Autocorrelation
Durbin-Watson test
Breusch-Godfrey test
Multicollinearity
Standard errors
Stability
Normality
Chow test
Econometric Model
Lecture 7-8 Time series analysis
White nose process
Autoregressive processes
Moving average processes
AR (1), MA (1), ARMA (1,1)
ARIMA Models
Stationarity
I(0), I(1), I(2)
Unit root testing
Autocorrelation and partial autocorrelation functions
Box-Jenkins approach
Forecasting
Exponential smoothing
Lecture 9-10 Volatility Modelling
Heteroscedasticity (revisited lec 4-6)
Ramsey’s RESET test
Concepts of volatility
Types of data (times series, cross-sectional, panel)
continuous and discrete data
cardinal, ordinal and nominal numbers
Statistical packages (returns in financial modelling, log returns)
Regression
Linear Regression/ Multiple Linear Regression
Ordinary Least Squares (OLS)
Population Regression function (PRF)
Lecture 2-3 Hypothesis Testing
T-test/ F-test
Confidence intervals
p-value
least squares assumptions
restricted and unrestricted regression
t and F-distribution
dummy variables
intercept / slope variables
interaction terms
Lecture 4-6 Testing Classical Assumptions
Gauss-Markov Theorem (OLS, BLUE)
Classic Assumption
Heteroscedasticity
White test
GQ test
Autocorrelation
Durbin-Watson test
Breusch-Godfrey test
Multicollinearity
Standard errors
Stability
Normality
Chow test
Econometric Model
Lecture 7-8 Time series analysis
White nose process
Autoregressive processes
Moving average processes
AR (1), MA (1), ARMA (1,1)
ARIMA Models
Stationarity
I(0), I(1), I(2)
Unit root testing
Autocorrelation and partial autocorrelation functions
Box-Jenkins approach
Forecasting
Exponential smoothing
Lecture 9-10 Volatility Modelling
Heteroscedasticity (revisited lec 4-6)
Ramsey’s RESET test
Concepts of volatility
