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	0.1130	4.28***
βGARCH	0.8167	26.78***
γleverage	-0.0121	-0.41
λ₁tau intercept	0.1571	0.82
λ₂forecast adj.	0.8219	15.84***
λ₃tau persistence	0.1781	12.89***

Parameter	Value	t-statistic
m window Rolling window length	21
α ARCH Response to squared shocks	0.1130	4.28***
β GARCH Volatility persistence	0.8167	26.78***
γ leverage Additional response to negative shocks	-0.0121	-0.41
λ₁ tau intercept Baseline long-term coefficient	0.1571	0.82
λ₂ forecast adj. Forecast performance sensitivity	0.8219	15.84***
λ₃ tau persistence Long-term factor persistence	0.1781	12.89***

V-Lab

China Yangtze Power Co Ltd ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other China Yangtze Power Co Ltd Analyses