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	3.7797
αARCH	0.1447
βGARCH	0.8553

γ₁	-4.8928
γ₂	8.6522
γ₃	-10.8531
γ₄	12.1611
γ₅	-0.2273
γ₆	-15.1988
γ₇	19.6883
γ₈	-12.7694
γ₉	1.0473
γ₁₀	2.9199

Parameter	Value	t-statistic
ω const Unconditional variance weight	3.7797
α ARCH Response to squared shocks	0.1447
β GARCH Volatility persistence	0.8553

γ₁	-4.8928
γ₂	8.6522
γ₃	-10.8531
γ₄	12.1611
γ₅	-0.2273
γ₆	-15.1988
γ₇	19.6883
γ₈	-12.7694
γ₉	1.0473
γ₁₀	2.9199

V-Lab

Stakk Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Stakk Ltd Analyses