What is the difference between linear and non-linear

autoregressive models? Which models can/cannot be estimated

by the OLS?

2. How to interpret coefficients in the linear model if variables are

in logs? Interpreting coefficients on dummies.

3. OLS estimates are BLUE. Explain it. Does it affect the residuals

in your model?

4. Can we compare autoregressive models with different left-hand

sides?

5. What is R2? What does it measure?

6. White's test for heteroscedasticity.

7. CAPM. Why do we need the CAPM? How can we formulate the

CAMP using an autoregressive model? What does an intercept

show? What does a BETA measure? Do these coefficients relate

to market efficiency? How to interpret coefficients of the FamaFrench model?

8. Suppose you are provided with a print-screen from Eviews.

Explain what t-statistics and p-values tell you. Which

hypotheses do they test? What is F-statistics? What is AIC and

BIC?

9. ARMA models. How ACF and PACF look for these models.

10. VAR. How to interpret coefficients? What do IRFs and

VDs allow us to do? The concept of Granger causality.

11. Non-stationary models. What is stationarity? What is a

deterministic/stochastic trend? Which models should we

consider if we expect stochastic trends in data? What to do if a

data set contains deterministic trend(s)?

12. How do the ADF and Phillips Perron tests work? Which

one is better for heteroskedastic variables?

13. Cointegration. What does it mean? Do you expect returns

of different assets to be co-integrated? When should we use the

Johansen test? Which signs should cointegrating parameters

ALPHA and BETA have? Make sure that you can explain the

Johansen test from an Eviews output. How this is related to the

expectation theory of term structure?

14. Volatility models. What is heteroscedasticity? GARCH,

GJR GARCH, EGARCH. An interpretation of model

parameters. Which method should we use to estimate these

models. What is historical volatility? What does a News Impact

Curve tell us?

15. MGARCH models. VECH, BEKK, DCC, CCC. Which

model is more parsimonious? How volatility matrix from these

models should look like?

16. Which problems you might encounter when you use

monthly returns in a regression.