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	4.9565	2.66***
αARCH	0.3139	6.80***
βGARCH	0.6663	14.90***

γ₁	1.4823	0.37
γ₂	-26.7703	-3.15***
γ₃	58.9302	6.21***
γ₄	-38.6159	-4.38***
γ₅	0.5565	0.08
γ₆	5.6859	1.51
γ₇	-3.7350	-1.37
γ₈	3.0219	1.51
γ₉	2.4329	1.09

Parameter	Value	t-statistic
ω const Unconditional variance weight	4.9565	2.66***
α ARCH Response to squared shocks	0.3139	6.80***
β GARCH Volatility persistence	0.6663	14.90***

γ₁	1.4823	0.37
γ₂	-26.7703	-3.15***
γ₃	58.9302	6.21***
γ₄	-38.6159	-4.38***
γ₅	0.5565	0.08
γ₆	5.6859	1.51
γ₇	-3.7350	-1.37
γ₈	3.0219	1.51
γ₉	2.4329	1.09

V-Lab

Tsi Co., Ltd. Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Tsi Co., Ltd. Analyses