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	0.6911	0.68
αARCH	0.2368	0.02
βGARCH	0.7632	0.05

γ₁	-0.5902	-0.01
γ₂	0.7860	0.01

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.6911	0.68
α ARCH Response to squared shocks	0.2368	0.02
β GARCH Volatility persistence	0.7632	0.05

γ₁	-0.5902	-0.01
γ₂	0.7860	0.01

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Trend Gyo As Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Trend Gyo As Analyses