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Compare GJR-GARCH with EGARCH

Previously you have fitted a GJR-GARCH and EGARCH model with Bitcoin return time series. In this exercise, you will compare the estimated conditional volatility from the two models by plotting their results.

The GJR-GARCH model estimated volatility is saved in gjrgm_vol, and EGARCH model estimated volatility is saved in egarch_vol. You will plot them together with actual Bitcoin return observations, which can be accessed by column ”Return” in bitcoin_data.

This exercise is part of the course

GARCH Models in Python

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Exercise instructions

  • Plot the actual Bitcoin returns.
  • Plot GJR-GARCH estimated volatility.
  • Plot EGARCH estimated volatility.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Plot the actual Bitcoin returns
plt.plot(bitcoin_data['____'], color = 'grey', alpha = 0.4, label = 'Price Returns')

# Plot GJR-GARCH estimated volatility
plt.plot(____, color = 'gold', label = 'GJR-GARCH Volatility')

# Plot EGARCH  estimated volatility
plt.plot(____, color = 'red', label = 'EGARCH Volatility')

plt.legend(loc = 'upper right')
plt.show()
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