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	2.3214	2.44**
αARCH	0.0561	4.25***
βGARCH	0.9218	43.55***

γ₁	-0.1519	-0.62
γ₂	0.7305	2.27**
γ₃	-1.2464	-6.55***
γ₄	0.9643	3.27***
γ₅	-0.2239	-0.54
γ₆	-0.2162	-0.58
γ₇	0.2416	0.89

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.3214	2.44**
α ARCH Response to squared shocks	0.0561	4.25***
β GARCH Volatility persistence	0.9218	43.55***

γ₁	-0.1519	-0.62
γ₂	0.7305	2.27**
γ₃	-1.2464	-6.55***
γ₄	0.9643	3.27***
γ₅	-0.2239	-0.54
γ₆	-0.2162	-0.58
γ₇	0.2416	0.89

V-Lab

Jsl Sa Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Jsl Sa Analyses