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	2.9068	2.10**
αARCH	0.2937	6.10***
βGARCH	0.7038	14.73***

γ₁	-1.6587	-3.51***
γ₂	2.8534	3.41***
γ₃	-1.9079	-3.07***
γ₄	1.4913	3.50***
γ₅	-1.1456	-2.73***
γ₆	-0.0937	-0.25
γ₇	1.0309	1.98**
γ₈	-3.5254	-1.84*
γ₉	10.1484	2.17**

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.9068	2.10**
α ARCH Response to squared shocks	0.2937	6.10***
β GARCH Volatility persistence	0.7038	14.73***

γ₁	-1.6587	-3.51***
γ₂	2.8534	3.41***
γ₃	-1.9079	-3.07***
γ₄	1.4913	3.50***
γ₅	-1.1456	-2.73***
γ₆	-0.0937	-0.25
γ₇	1.0309	1.98**
γ₈	-3.5254	-1.84*
γ₉	10.1484	2.17**

V-Lab

MCR SA Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other MCR SA Analyses