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	0.9966	6.31***
αARCH	0.1156	2.55**
βGARCH	0.8843	19.64***

γ₁	0.1831	0.65
γ₂	-0.4617	-0.98
γ₃	0.2332	0.96
γ₄	0.4284	0.65
γ₅	-0.7722	-0.84
γ₆	0.5989	0.87
γ₇	-0.2887	-0.81
γ₈	0.1262	0.82
γ₉	-0.0721	-0.55

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.9966	6.31***
α ARCH Response to squared shocks	0.1156	2.55**
β GARCH Volatility persistence	0.8843	19.64***

γ₁	0.1831	0.65
γ₂	-0.4617	-0.98
γ₃	0.2332	0.96
γ₄	0.4284	0.65
γ₅	-0.7722	-0.84
γ₆	0.5989	0.87
γ₇	-0.2887	-0.81
γ₈	0.1262	0.82
γ₉	-0.0721	-0.55

V-Lab

Bank of New York Mellon Corp/The Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Bank of New York Mellon Corp/The Analyses