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  3. GARCH Models in Python

Exercise

Fit a GARCH with skewed t-distribution

The default normal distribution assumption of the standardized residuals used in GARCH models are not representative of the real financial world. Fat tails and skewness are frequently observed in financial return data.

In this exercise, you will improve the GARCH model by using a skewed Student's t-distribution assumption. In addition, you will compare the model estimated volatility with that from a model with a normal distribution assumption by plotting them together.

A GARCH model with the default normal distribution assumption has been fitted for you, and its volatility estimation is saved in normal_vol.

Instructions 1/2

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  • Define a GARCH model skewt_gm with a skewed Student's t-distribution assumption.
  • Fit the model and save the result in skewt_result.