Select up to 5 explanatory variables (but not necessarily 5) and estimate the corresponding regression model to forecast volatility in June 2018. Briefly explain why these variables are selected. You...

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Answer To: Select up to 5 explanatory variables (but not necessarily 5) and estimate the corresponding...

Viswanathan answered on Jun 06 2020
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Select up to 5 explanatory variables (but not necessarily 5) and estimate the corresponding regression model to forecast volatility in June 2018. Briefly explain why these variables are selected. You need to ensure that the 3 regression model satisfies the underlying assumptions. You can use the full sample or a sub-sample to estimate your model. Please justify your sample selection and report the in-sample estimated coefficients in Table 1 below. Fill in the sample period and replace X’s with variable names.
Compare the forecasting performance of the best of DMA and Holt’s models against the linear regression in the hold-out period. Use the best model from above analyses to forecast volatility in June 2018. Based on daily returns in June, the team with the lowest forecast error gets 2 extra marks.
Single Exponential Smoothing
The results are given below
Forecasts
Period Forecast Lower Upper
219 18619.7 13341.1 23898.3
Holt’s Winter...
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