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	2.6036	2.95***
αARCH	0.2267	6.30***
βGARCH	0.7576	23.50***

γ₁	3.3382	0.66
γ₂	-26.2278	-2.61***
γ₃	49.8233	6.13***
γ₄	-32.8660	-7.07***
γ₅	3.0417	0.69
γ₆	5.6054	1.78*
γ₇	-2.6472	-1.03
γ₈	-2.4087	-0.85
γ₉	3.2127	1.11
γ₁₀	2.6708	0.78

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.6036	2.95***
α ARCH Response to squared shocks	0.2267	6.30***
β GARCH Volatility persistence	0.7576	23.50***

γ₁	3.3382	0.66
γ₂	-26.2278	-2.61***
γ₃	49.8233	6.13***
γ₄	-32.8660	-7.07***
γ₅	3.0417	0.69
γ₆	5.6054	1.78*
γ₇	-2.6472	-1.03
γ₈	-2.4087	-0.85
γ₉	3.2127	1.11
γ₁₀	2.6708	0.78

V-Lab

Tsi Co., Ltd. Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Tsi Co., Ltd. Analyses