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	26
αARCH	0.1110	8.68***
βGARCH	0.7512	28.48***
γleverage	-0.1110	-3.68***
λ₁tau intercept	10.0000	0.37
λ₂forecast adj.	0.0701	5.65***
λ₃tau persistence	0.9299	75.79***

Parameter	Value	t-statistic
m window Rolling window length	26
α ARCH Response to squared shocks	0.1110	8.68***
β GARCH Volatility persistence	0.7512	28.48***
γ leverage Additional response to negative shocks	-0.1110	-3.68***
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.37
λ₂ forecast adj. Forecast performance sensitivity	0.0701	5.65***
λ₃ tau persistence Long-term factor persistence	0.9299	75.79***

V-Lab

NSI NV ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other NSI NV Analyses