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	21
αARCH	0.4597	1.01
βGARCH	0.7651	6.52***
γleverage	-0.4597	-1.02
λ₁tau intercept	10.0000	0.08
λ₂forecast adj.	1.0000	0.35
λ₃tau persistence	0.0000	0.01

Parameter	Value	t-statistic
m window Rolling window length	21
α ARCH Response to squared shocks	0.4597	1.01
β GARCH Volatility persistence	0.7651	6.52***
γ leverage Additional response to negative shocks	-0.4597	-1.02
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.08
λ₂ forecast adj. Forecast performance sensitivity	1.0000	0.35
λ₃ tau persistence Long-term factor persistence	0.0000	0.01

V-Lab

SP Setia Bhd Group ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other SP Setia Bhd Group Analyses