CBOE Volatility Index

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
ωconst	1.2376	4.86***
αARCH	0.1916	10.26***
βGARCH	0.7857	46.68***

γ₁	-0.3826	-2.06**
γ₂	0.6425	2.08**
γ₃	-0.4021	-1.41
γ₄	0.3246	1.18
γ₅	-0.6566	-2.35**
γ₆	1.1485	4.52***
γ₇	-0.9992	-5.89***

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.2376	4.86***
α ARCH Response to squared shocks	0.1916	10.26***
β GARCH Volatility persistence	0.7857	46.68***

γ₁	-0.3826	-2.06**
γ₂	0.6425	2.08**
γ₃	-0.4021	-1.41
γ₄	0.3246	1.18
γ₅	-0.6566	-2.35**
γ₆	1.1485	4.52***
γ₇	-0.9992	-5.89***

V-Lab

Bangladesh Dhaka Stock Exchange Broad Index Zero Slope Spline-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

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