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	3.7545	9.49***
αARCH	0.1172	5.39***
βGARCH	0.8319	32.84***

γ₁	0.0074	0.48
γ₂	0.0044	0.18
γ₃	-0.0163	-0.84
γ₄	0.0250	1.78*
γ₅	-0.0447	-2.36**
γ₆	0.0534	1.66*
γ₇	-0.0360	-1.30
γ₈	-0.0130	-0.32

Parameter	Value	t-statistic
ω const Unconditional variance weight	3.7545	9.49***
α ARCH Response to squared shocks	0.1172	5.39***
β GARCH Volatility persistence	0.8319	32.84***

γ₁	0.0074	0.48
γ₂	0.0044	0.18
γ₃	-0.0163	-0.84
γ₄	0.0250	1.78*
γ₅	-0.0447	-2.36**
γ₆	0.0534	1.66*
γ₇	-0.0360	-1.30
γ₈	-0.0130	-0.32

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