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

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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
ωconst	1.6180	3.49***
αARCH	0.1842	6.77***
βGARCH	0.7354	23.99***

γ₁	-0.6035	-2.73***
γ₂	0.9731	2.43**
γ₃	-0.6513	-2.01**
γ₄	0.5904	1.88*
γ₅	-0.4353	-1.93*
γ₆	0.1305	1.21
γ₇	-0.0193	-0.27
γ₈	0.0257	0.39
γ₉	-0.0572	-0.88
γ₁₀	0.0408	0.47

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.6180	3.49***
α ARCH Response to squared shocks	0.1842	6.77***
β GARCH Volatility persistence	0.7354	23.99***

γ₁	-0.6035	-2.73***
γ₂	0.9731	2.43**
γ₃	-0.6513	-2.01**
γ₄	0.5904	1.88*
γ₅	-0.4353	-1.93*
γ₆	0.1305	1.21
γ₇	-0.0193	-0.27
γ₈	0.0257	0.39
γ₉	-0.0572	-0.88
γ₁₀	0.0408	0.47

V-Lab

Krka Dd Nova Mesto Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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