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	1.0482	4.55***
αARCH	0.1654	7.51***
βGARCH	0.8345	38.31***

γ₁	0.0324	0.05
γ₂	-0.7362	-1.13
γ₃	1.1621	5.45***
γ₄	-0.6454	-3.09***
γ₅	0.3681	2.20**
γ₆	-0.4834	-2.36**
γ₇	0.4924	1.84*
γ₈	-0.2006	-0.79
γ₉	0.0096	0.04
γ₁₀	0.0822	0.34

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0482	4.55***
α ARCH Response to squared shocks	0.1654	7.51***
β GARCH Volatility persistence	0.8345	38.31***

γ₁	0.0324	0.05
γ₂	-0.7362	-1.13
γ₃	1.1621	5.45***
γ₄	-0.6454	-3.09***
γ₅	0.3681	2.20**
γ₆	-0.4834	-2.36**
γ₇	0.4924	1.84*
γ₈	-0.2006	-0.79
γ₉	0.0096	0.04
γ₁₀	0.0822	0.34

V-Lab

3M India Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other 3M India Ltd Analyses