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	0.3178	2.32**
βGARCH	0.7456	10.34***
γleverage	-0.1367	-0.99
λ₁tau intercept	0.0000	0.05
λ₂forecast adj.	0.4223	3.70***
λ₃tau persistence	0.5616	5.85***

Parameter	Value	t-statistic
m window Rolling window length	21
α ARCH Response to squared shocks	0.3178	2.32**
β GARCH Volatility persistence	0.7456	10.34***
γ leverage Additional response to negative shocks	-0.1367	-0.99
λ₁ tau intercept Baseline long-term coefficient	0.0000	0.05
λ₂ forecast adj. Forecast performance sensitivity	0.4223	3.70***
λ₃ tau persistence Long-term factor persistence	0.5616	5.85***

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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