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	3.5712	4.71***
αARCH	0.1152	8.36***
βGARCH	0.8301	40.69***

γ₁	0.0926	0.53
γ₂	0.1767	0.66
γ₃	-0.5254	-2.82***
γ₄	0.3321	1.82*
γ₅	-0.3123	-1.54
γ₆	0.8055	4.95***
γ₇	-1.1251	-8.94***
γ₈	0.8314	4.31***
γ₉	-0.3111	-0.96

Parameter	Value	t-statistic
ω const Unconditional variance weight	3.5712	4.71***
α ARCH Response to squared shocks	0.1152	8.36***
β GARCH Volatility persistence	0.8301	40.69***

γ₁	0.0926	0.53
γ₂	0.1767	0.66
γ₃	-0.5254	-2.82***
γ₄	0.3321	1.82*
γ₅	-0.3123	-1.54
γ₆	0.8055	4.95***
γ₇	-1.1251	-8.94***
γ₈	0.8314	4.31***
γ₉	-0.3111	-0.96

V-Lab

Harima-Kyowa Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Harima-Kyowa Co Ltd Analyses