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	1.0150	0.44
αARCH	0.1614	0.04
βGARCH	0.8386	0.20

γ₁	-0.5700	-0.37
γ₂	0.6515	0.39
γ₃	-0.1537	-1.02
γ₄	0.1790	0.65
γ₅	-0.2232	-0.63

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0150	0.44
α ARCH Response to squared shocks	0.1614	0.04
β GARCH Volatility persistence	0.8386	0.20

γ₁	-0.5700	-0.37
γ₂	0.6515	0.39
γ₃	-0.1537	-1.02
γ₄	0.1790	0.65
γ₅	-0.2232	-0.63

V-Lab

Buffalo Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Buffalo Co Ltd Analyses