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	0.4852	4.14***
αARCH	0.1006	9.35***
βGARCH	0.8774	65.81***

γ₁	-0.4897	-7.97***
γ₂	0.8025	8.88***
γ₃	-0.5758	-8.96***
γ₄	0.4794	6.94***
γ₅	-0.4042	-5.03***
γ₆	0.1206	0.86

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.4852	4.14***
α ARCH Response to squared shocks	0.1006	9.35***
β GARCH Volatility persistence	0.8774	65.81***

γ₁	-0.4897	-7.97***
γ₂	0.8025	8.88***
γ₃	-0.5758	-8.96***
γ₄	0.4794	6.94***
γ₅	-0.4042	-5.03***
γ₆	0.1206	0.86

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