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	1.1018	4.24***
αARCH	0.2221	15.13***
βGARCH	0.7521	50.02***

γ₁	-0.5133	-2.92***
γ₂	1.1130	4.26***
γ₃	-1.6255	-8.33***
γ₄	1.6060	7.11***
γ₅	-0.8038	-3.16***
γ₆	0.8250	3.57***
γ₇	-0.9589	-5.03***
γ₈	0.0698	0.35
γ₉	0.5002	1.58

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1018	4.24***
α ARCH Response to squared shocks	0.2221	15.13***
β GARCH Volatility persistence	0.7521	50.02***

γ₁	-0.5133	-2.92***
γ₂	1.1130	4.26***
γ₃	-1.6255	-8.33***
γ₄	1.6060	7.11***
γ₅	-0.8038	-3.16***
γ₆	0.8250	3.57***
γ₇	-0.9589	-5.03***
γ₈	0.0698	0.35
γ₉	0.5002	1.58

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