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How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

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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	121
αARCH	0.1183	2.70***
βGARCH	0.0000	0.00
γleverage	-0.1183	-2.66***
λ₁tau intercept	7.9190	2.34**
λ₂forecast adj.	0.6377	5.11***
λ₃tau persistence	0.0000	0.00

Parameter	Value	t-statistic
m window Rolling window length	121
α ARCH Response to squared shocks	0.1183	2.70***
β GARCH Volatility persistence	0.0000	0.00
γ leverage Additional response to negative shocks	-0.1183	-2.66***
λ₁ tau intercept Baseline long-term coefficient	7.9190	2.34**
λ₂ forecast adj. Forecast performance sensitivity	0.6377	5.11***
λ₃ tau persistence Long-term factor persistence	0.0000	0.00

V-Lab

Shengfeng Development Ltd MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Shengfeng Development Ltd Analyses