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	3.7282	9.32***
αARCH	0.1171	5.46***
βGARCH	0.8351	34.42***

γ₁	0.0122	1.00
γ₂	-0.0098	-0.47
γ₃	0.0080	0.31
γ₄	-0.0145	-0.39
γ₅	0.0077	0.23
γ₆	0.0102	0.51
γ₇	-0.0404	-1.12

Parameter	Value	t-statistic
ω const Unconditional variance weight	3.7282	9.32***
α ARCH Response to squared shocks	0.1171	5.46***
β GARCH Volatility persistence	0.8351	34.42***

γ₁	0.0122	1.00
γ₂	-0.0098	-0.47
γ₃	0.0080	0.31
γ₄	-0.0145	-0.39
γ₅	0.0077	0.23
γ₆	0.0102	0.51
γ₇	-0.0404	-1.12

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