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	1.1077	4.25***
αARCH	0.2217	15.14***
βGARCH	0.7526	50.12***

γ₁	-0.4998	-2.86***
γ₂	1.0872	4.18***
γ₃	-1.6081	-8.31***
γ₄	1.6105	7.21***
γ₅	-0.8228	-3.27***
γ₆	0.8434	3.64***
γ₇	-0.9886	-5.15***
γ₈	0.0982	0.50
γ₉	0.5458	1.79*

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1077	4.25***
α ARCH Response to squared shocks	0.2217	15.14***
β GARCH Volatility persistence	0.7526	50.12***

γ₁	-0.4998	-2.86***
γ₂	1.0872	4.18***
γ₃	-1.6081	-8.31***
γ₄	1.6105	7.21***
γ₅	-0.8228	-3.27***
γ₆	0.8434	3.64***
γ₇	-0.9886	-5.15***
γ₈	0.0982	0.50
γ₉	0.5458	1.79*

V-Lab

Japan Reliance Service Corp Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Japan Reliance Service Corp Analyses