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
mwindow	26
αARCH	0.2727	2.39**
βGARCH	0.0000	0.00
γleverage	-0.2727	-1.25
λ₁tau intercept	10.0000	0.03
λ₂forecast adj.	0.8342	2.14**
λ₃tau persistence	0.1658	0.98

Parameter	Value	t-statistic
m window Rolling window length	26
α ARCH Response to squared shocks	0.2727	2.39**
β GARCH Volatility persistence	0.0000	0.00
γ leverage Additional response to negative shocks	-0.2727	-1.25
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.03
λ₂ forecast adj. Forecast performance sensitivity	0.8342	2.14**
λ₃ tau persistence Long-term factor persistence	0.1658	0.98

V-Lab

Viking Kagit Seluloz As ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Viking Kagit Seluloz As Analyses