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	41
αARCH	0.2675	4.22***
βGARCH	0.8052	44.01***
γleverage	-0.2675	-3.84***
λ₁tau intercept	10.0000	0.09
λ₂forecast adj.	0.0000	0.01
λ₃tau persistence	0.9423	20.84***

Parameter	Value	t-statistic
m window Rolling window length	41
α ARCH Response to squared shocks	0.2675	4.22***
β GARCH Volatility persistence	0.8052	44.01***
γ leverage Additional response to negative shocks	-0.2675	-3.84***
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.09
λ₂ forecast adj. Forecast performance sensitivity	0.0000	0.01
λ₃ tau persistence Long-term factor persistence	0.9423	20.84***

V-Lab

Krka Dd Nova Mesto ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Krka Dd Nova Mesto Analyses