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	1.7279	5.00***
αARCH	0.1886	7.13***
βGARCH	0.6543	17.96***

γ₁	-0.8371	-1.96*
γ₂	1.4656	2.08**
γ₃	-0.9817	-2.19**
γ₄	0.5242	1.77*
γ₅	0.0188	0.08
γ₆	-0.6536	-2.90***
γ₇	0.9496	4.76***
γ₈	-0.5291	-2.52**
γ₉	-0.4029	-1.57
γ₁₀	1.0516	2.71***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.7279	5.00***
α ARCH Response to squared shocks	0.1886	7.13***
β GARCH Volatility persistence	0.6543	17.96***

γ₁	-0.8371	-1.96*
γ₂	1.4656	2.08**
γ₃	-0.9817	-2.19**
γ₄	0.5242	1.77*
γ₅	0.0188	0.08
γ₆	-0.6536	-2.90***
γ₇	0.9496	4.76***
γ₈	-0.5291	-2.52**
γ₉	-0.4029	-1.57
γ₁₀	1.0516	2.71***

V-Lab

Stride Property Group Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Stride Property Group Analyses