Why should we learn about the non-linearity in the financial econometrics?

• because of the leverage effects: where the volatility tends to increase more significantly when the asset price increases than when the asset price decreases

• because financial data tends to be leptokurtosis: fat tails and excess peakedness

• the more complex it is, the higher the capabilities of the model to forecast

• all answer are correct

Calculating Volatility is...

• calculating implied volatility

• calculating historical volatility

• calculating conditional volatility

• no correct answe

Heteroscedasticity is..

• non-constant errors variance

• non-constant errors mean

• different data will gives different parameter

• type I error econometrics

how to calculate total risk?

• standard deviation

• Beta

• CAPM

• the error term of the model

the arch effect test results will be compared with...

• Chi square distribution table

• Z distribution table

• F distribution table

• student t- distribution table

what is the disadvantages of ARCH model?

• it's hard to determine the number of the lags

• the required number of lags might be large

• all answer are correct

• Non-negativity constraints might be violated

What is the main important property of GARCH?

• GARCH allow the conditional variance to be dependent upon previous own lags

• GARCH allow the implied variance to be dependent upon previous own lags

• GARCH allow the conditional variance to be dependent upon previous error lags

• all answers are correct

these are the extension of GARCH model, except:

• EGARCH

• GJR- TGARCH

• GARCHM

• GARCH-PERCENTILE

What can you conclude from this result?

• there are relationship between the dependent variable and it lags up to five lags

• the arch effect is present

• the arch effect is not significant

• all statements are correct

Which variable result should you pay attention to if you are concerned with the leverage effect?

• L1. egarch

• both L1.earch_a and L1.earch

• L1.earch_a

• L1.earch