How volatility evolves over time

How illiquidity evolves over time

{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

Spline Coefficients

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
ωconst	1.2404	2.35**
αARCH	0.2688	7.48***
βGARCH	0.7308	21.08***

γ₁	0.8140	0.40
γ₂	-2.2029	-0.99
γ₃	2.0040	1.92*
γ₄	-0.0428	-0.05
γ₅	-5.0711	-1.45
γ₆	13.3587	1.42
γ₇	-17.4169	-1.47
γ₈	14.3147	1.62
γ₉	-7.7932	-1.68*
γ₁₀	1.7773	1.10

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.2404	2.35**
α ARCH Response to squared shocks	0.2688	7.48***
β GARCH Volatility persistence	0.7308	21.08***

γ₁	0.8140	0.40
γ₂	-2.2029	-0.99
γ₃	2.0040	1.92*
γ₄	-0.0428	-0.05
γ₅	-5.0711	-1.45
γ₆	13.3587	1.42
γ₇	-17.4169	-1.47
γ₈	14.3147	1.62
γ₉	-7.7932	-1.68*
γ₁₀	1.7773	1.10

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