How volatility evolves over time

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{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	1.3220	3.71***
αARCH	0.1411	14.57***
βGARCH	0.8451	84.07***

γ₁	0.0581	0.47
γ₂	-0.1526	-0.79
γ₃	-0.0366	-0.26
γ₄	0.4860	4.64***
γ₅	-0.7163	-6.69***
γ₆	0.4634	4.30***
γ₇	0.0483	0.46
γ₈	-0.4947	-3.43***
γ₉	0.8030	2.57**
γ₁₀	-0.7442	-1.53

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.3220	3.71***
α ARCH Response to squared shocks	0.1411	14.57***
β GARCH Volatility persistence	0.8451	84.07***

γ₁	0.0581	0.47
γ₂	-0.1526	-0.79
γ₃	-0.0366	-0.26
γ₄	0.4860	4.64***
γ₅	-0.7163	-6.69***
γ₆	0.4634	4.30***
γ₇	0.0483	0.46
γ₈	-0.4947	-3.43***
γ₉	0.8030	2.57**
γ₁₀	-0.7442	-1.53

V-Lab

Nagahori Corp Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Nagahori Corp Analyses