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How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

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Value at Risk (VaR) estimates the maximum loss at a given confidence level. Expected Shortfall (ES) estimates the average loss beyond VaR.

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Param	Value	t-stat
mwindow	31
αARCH	0.1765	6.19***
βGARCH	0.4364	7.40***
γleverage	-0.0026	-0.05
λ₁tau intercept	0.0176	1.29
λ₂forecast adj.	0.9956	7.63***
λ₃tau persistence	0.0000	0.00

Parameter	Value	t-statistic
m window Rolling window length	31
α ARCH Response to squared shocks	0.1765	6.19***
β GARCH Volatility persistence	0.4364	7.40***
γ leverage Additional response to negative shocks	-0.0026	-0.05
λ₁ tau intercept Baseline long-term coefficient	0.0176	1.29
λ₂ forecast adj. Forecast performance sensitivity	0.9956	7.63***
λ₃ tau persistence Long-term factor persistence	0.0000	0.00

V-Lab

Peruvian New Sol MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Peruvian New Sol Analyses