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	0.4889	4.12***
αARCH	0.1001	9.34***
βGARCH	0.8783	66.47***

γ₁	-0.4862	-7.91***
γ₂	0.7962	8.80***
γ₃	-0.5703	-8.87***
γ₄	0.4752	6.89***
γ₅	-0.4049	-5.07***
γ₆	0.1260	0.89

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.4889	4.12***
α ARCH Response to squared shocks	0.1001	9.34***
β GARCH Volatility persistence	0.8783	66.47***

γ₁	-0.4862	-7.91***
γ₂	0.7962	8.80***
γ₃	-0.5703	-8.87***
γ₄	0.4752	6.89***
γ₅	-0.4049	-5.07***
γ₆	0.1260	0.89

V-Lab

Kawasaki Setsubi Kogyo Co Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Kawasaki Setsubi Kogyo Co Analyses