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	46
αARCH	0.0887	5.49***
βGARCH	0.7930	25.09***
γleverage	-0.0887	-1.65*
λ₁tau intercept	3.1845	1.34
λ₂forecast adj.	0.9666	32.58***
λ₃tau persistence	0.0090	7.79***

Parameter	Value	t-statistic
m window Rolling window length	46
α ARCH Response to squared shocks	0.0887	5.49***
β GARCH Volatility persistence	0.7930	25.09***
γ leverage Additional response to negative shocks	-0.0887	-1.65*
λ₁ tau intercept Baseline long-term coefficient	3.1845	1.34
λ₂ forecast adj. Forecast performance sensitivity	0.9666	32.58***
λ₃ tau persistence Long-term factor persistence	0.0090	7.79***

V-Lab

Bank of New York Mellon Corp/The ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Bank of New York Mellon Corp/The Analyses