India NSE Volatility Index

CBOE Emerging Market Markets 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	4.4635	2.08**
αARCH	0.3072	6.29***
βGARCH	0.6913	68.34***

γ₁	-4.5216	-0.19
γ₂	20.9702	0.73
γ₃	-52.8951	-5.58***
γ₄	97.6757	21.08***
γ₅	-132.7889	-34.00***
γ₆	133.8481	19.97***
γ₇	-102.5135	-14.51***
γ₈	63.2209	3.89***
γ₉	-31.9770	-2.22**

Parameter	Value	t-statistic
ω const Unconditional variance weight	4.4635	2.08**
α ARCH Response to squared shocks	0.3072	6.29***
β GARCH Volatility persistence	0.6913	68.34***

γ₁	-4.5216	-0.19
γ₂	20.9702	0.73
γ₃	-52.8951	-5.58***
γ₄	97.6757	21.08***
γ₅	-132.7889	-34.00***
γ₆	133.8481	19.97***
γ₇	-102.5135	-14.51***
γ₈	63.2209	3.89***
γ₉	-31.9770	-2.22**

V-Lab

Ashika Global Securities Ltd Zero Slope Spline-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Ashika Global Securities Ltd Analyses