Financial Econometrics — DU Bachelor of Business Administration (Financial Investment Analysis) Previous Year Question Papers

a) Explain the classical linear regression model. b) Discuss how OLS estimatl.on can be problematic when applied to financial time series data. a) Derive and interpret the ARCH(1) model. b) Describe the steps involved in estimating an ARCH model and testing for ARCH effects. a) Discuss the limitat].ons of applying OLS to financial tl.me series data. (8 marks) b) The following regression output was obtained from modelling daily returns (in %) of a stock: With standard errors: i) Interpret the model. ii) Test the significance of the lagged return at the 5% level. iii) What does this model suggest about market efficiency? (10 marks) a) Discuss the concept and importance of forecastl.ng in financial econometrics. b) Compare and contrast univariate vs. multivariate time series forecastl.ng methods. a) What is a Vector Autoregression (VAR) model? Discuss its application in financial modeling. b) How would you determine the optl.mal lag length in a VAR model? a) Define cointegration. How is it different from correlation? b) Describe the Engle-Granger two-step method for testing cointegration. d) How can cointegration be useful in modeling long-term relationships in fi.nance (e.g., stock indices, interest rates)? (6 x 3 = 18 marks) a) What is a unit root? Explain why testing for unit roots is important in financial econometrics. (6 b) Given the following ADF regression result for the time series Yt The standard error of the coefficient on Yt.1 is 0.25. i) Conduct a t-test for stationarity at the 5% significance level (use critical value = -2.9). ii) State the null and alternative hypotheses. iii) What transformatl.on would you suggest based on the result? (12 marks)