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	1.7314	3.80***
αARCH	0.1693	8.55***
βGARCH	0.8296	40.87***

γ₁	-1.7327	-2.07**
γ₂	1.9530	1.62
γ₃	0.8670	1.20
γ₄	-4.2487	-3.25***
γ₅	6.7249	3.41***
γ₆	-4.2309	-2.21**
γ₇	0.4468	0.27
γ₈	-0.0837	-0.11
γ₉	0.5926	1.23

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.7314	3.80***
α ARCH Response to squared shocks	0.1693	8.55***
β GARCH Volatility persistence	0.8296	40.87***

γ₁	-1.7327	-2.07**
γ₂	1.9530	1.62
γ₃	0.8670	1.20
γ₄	-4.2487	-3.25***
γ₅	6.7249	3.41***
γ₆	-4.2309	-2.21**
γ₇	0.4468	0.27
γ₈	-0.0837	-0.11
γ₉	0.5926	1.23

V-Lab

Youzan Technology Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Youzan Technology Ltd Analyses