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	2.8491	2.08**
αARCH	0.2944	6.21***
βGARCH	0.7031	14.98***

γ₁	-1.6680	-3.51***
γ₂	2.8661	3.41***
γ₃	-1.9122	-3.07***
γ₄	1.4897	3.49***
γ₅	-1.1325	-2.68***
γ₆	-0.1128	-0.30
γ₇	1.0434	1.91*
γ₈	-3.4616	-1.80*
γ₉	10.2377	2.11**

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.8491	2.08**
α ARCH Response to squared shocks	0.2944	6.21***
β GARCH Volatility persistence	0.7031	14.98***

γ₁	-1.6680	-3.51***
γ₂	2.8661	3.41***
γ₃	-1.9122	-3.07***
γ₄	1.4897	3.49***
γ₅	-1.1325	-2.68***
γ₆	-0.1128	-0.30
γ₇	1.0434	1.91*
γ₈	-3.4616	-1.80*
γ₉	10.2377	2.11**

V-Lab

MCR SA Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other MCR SA Analyses