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	2.0606	4.67***
αARCH	0.3017	8.01***
βGARCH	0.6970	18.71***

γ₁	0.6789	0.84
γ₂	-7.5573	-7.07***
γ₃	14.9996	3.95***
γ₄	-11.4443	-3.12***
γ₅	5.3151	1.92*
γ₆	-4.6901	-1.40
γ₇	12.4248	1.59
γ₈	-19.1188	-1.93*
γ₉	11.8424	2.32**

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.0606	4.67***
α ARCH Response to squared shocks	0.3017	8.01***
β GARCH Volatility persistence	0.6970	18.71***

γ₁	0.6789	0.84
γ₂	-7.5573	-7.07***
γ₃	14.9996	3.95***
γ₄	-11.4443	-3.12***
γ₅	5.3151	1.92*
γ₆	-4.6901	-1.40
γ₇	12.4248	1.59
γ₈	-19.1188	-1.93*
γ₉	11.8424	2.32**

V-Lab

Til Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Til Ltd Analyses