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	0.9195	5.08***
αARCH	0.1697	13.62***
βGARCH	0.8238	65.65***

γ₁	-0.1324	-5.80***
γ₂	0.1892	5.27***
γ₃	-0.0288	-0.86

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.9195	5.08***
α ARCH Response to squared shocks	0.1697	13.62***
β GARCH Volatility persistence	0.8238	65.65***

γ₁	-0.1324	-5.80***
γ₂	0.1892	5.27***
γ₃	-0.0288	-0.86

V-Lab

Yamashita Health Care Hldgs Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Yamashita Health Care Hldgs Analyses