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	0.4905	4.10***
αARCH	0.1002	9.36***
βGARCH	0.8784	66.72***

γ₁	-0.4863	-7.88***
γ₂	0.7967	8.76***
γ₃	-0.5712	-8.84***
γ₄	0.4767	6.88***
γ₅	-0.4080	-5.08***
γ₆	0.1349	0.94

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.4905	4.10***
α ARCH Response to squared shocks	0.1002	9.36***
β GARCH Volatility persistence	0.8784	66.72***

γ₁	-0.4863	-7.88***
γ₂	0.7967	8.76***
γ₃	-0.5712	-8.84***
γ₄	0.4767	6.88***
γ₅	-0.4080	-5.08***
γ₆	0.1349	0.94

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