Compute the MSE, MAE and MAPE for all 3 models which you estimated. According to each of these criteria, which model forecasts best and which model forecasts worst?

Present your Eviews equation estimation output as it would be in published academic papers.

Question 1 (30 points)

Consider the observations for the FTSE 100 stock index return series for the period ranging from 2000 to 2015. Build an appropriate ARMA model and test for ARCH effects in the series of daily returns.

Question 2 (50 points)

Using the observations for years 2000 to 2015, estimate the following models from the GARCH family, selecting the appropriate lags:

GARCH with normal innovations
GJR with normal innovations
a specification of your choice

always using as the conditional mean equation the ARMA specification that you identified in Question 1 above.

For each of these models, forecast the daily volatility (square root of variance) for the last two years in your sample. Plot your forecasts against the actual realizations of the variable (realised volatility proxy), as well as the forecast errors (i.e. actual – forecast). Interpret the results.

Question 3 (20 points)

Compute the MSE, MAE and MAPE for all 3 models which you estimated. According to each of these criteria, which model forecasts best and which model forecasts worst?

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Compute the MSE, MAE and MAPE for all 3 models which you estimated. According to each of these criteria, which model forecasts best and which model forecasts worst?

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