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	0.7454	3.27***
αARCH	0.0893	6.28***
βGARCH	0.8571	36.32***

γ₁	-0.4001	-2.41**
γ₂	0.7847	3.46***
γ₃	-0.8036	-6.04***
γ₄	0.6672	5.19***
γ₅	-0.3699	-3.20***
γ₆	0.2309	2.04**
γ₇	-0.3147	-1.90*

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.7454	3.27***
α ARCH Response to squared shocks	0.0893	6.28***
β GARCH Volatility persistence	0.8571	36.32***

γ₁	-0.4001	-2.41**
γ₂	0.7847	3.46***
γ₃	-0.8036	-6.04***
γ₄	0.6672	5.19***
γ₅	-0.3699	-3.20***
γ₆	0.2309	2.04**
γ₇	-0.3147	-1.90*

V-Lab

Tenryu SAW MFG Co Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Tenryu SAW MFG Co Analyses