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
mwindow	21
αARCH	0.1863	4.02***
βGARCH	0.8534	18.90***
γleverage	-0.1863	-2.74***
λ₁tau intercept	1.0304	0.17
λ₂forecast adj.	0.9996	2.08**
λ₃tau persistence	0.0004	1.39

Parameter	Value	t-statistic
m window Rolling window length	21
α ARCH Response to squared shocks	0.1863	4.02***
β GARCH Volatility persistence	0.8534	18.90***
γ leverage Additional response to negative shocks	-0.1863	-2.74***
λ₁ tau intercept Baseline long-term coefficient	1.0304	0.17
λ₂ forecast adj. Forecast performance sensitivity	0.9996	2.08**
λ₃ tau persistence Long-term factor persistence	0.0004	1.39

V-Lab

Generic Engineering ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Generic Engineering Analyses