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	0.5812	4.52***
αARCH	0.1092	7.65***
βGARCH	0.8293	33.23***

γ₁	-1.0398	-4.97***
γ₂	1.2803	4.21***
γ₃	-0.3777	-1.87*
γ₄	-0.0602	-0.28
γ₅	0.5520	3.08***
γ₆	-0.3662	-2.91***
γ₇	0.0082	0.08
γ₈	-0.0246	-0.24
γ₉	-0.3036	-1.98**

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.5812	4.52***
α ARCH Response to squared shocks	0.1092	7.65***
β GARCH Volatility persistence	0.8293	33.23***

γ₁	-1.0398	-4.97***
γ₂	1.2803	4.21***
γ₃	-0.3777	-1.87*
γ₄	-0.0602	-0.28
γ₅	0.5520	3.08***
γ₆	-0.3662	-2.91***
γ₇	0.0082	0.08
γ₈	-0.0246	-0.24
γ₉	-0.3036	-1.98**

V-Lab

Primis Financial Corp Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Primis Financial Corp Analyses