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	1.2407	0.17
αARCH	0.0826	0.02
βGARCH	0.9174	0.17

γ₁	-0.0895	-0.01
γ₂	0.1188	0.01
γ₃	-0.0487	-0.02

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.2407	0.17
α ARCH Response to squared shocks	0.0826	0.02
β GARCH Volatility persistence	0.9174	0.17

γ₁	-0.0895	-0.01
γ₂	0.1188	0.01
γ₃	-0.0487	-0.02

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