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	1.0520	5.32***
αARCH	0.3106	13.98***
βGARCH	0.6871	31.33***

γ₁	-1.4794	-0.61
γ₂	6.1692	1.44
γ₃	-9.3225	-2.35**
γ₄	8.3334	2.82***
γ₅	-8.6208	-4.71***
γ₆	7.6387	3.94***
γ₇	-3.6650	-1.86*
γ₈	1.8168	1.26
γ₉	-0.6451	-0.57
γ₁₀	1.8143	1.02

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.0520	5.32***
α ARCH Response to squared shocks	0.3106	13.98***
β GARCH Volatility persistence	0.6871	31.33***

γ₁	-1.4794	-0.61
γ₂	6.1692	1.44
γ₃	-9.3225	-2.35**
γ₄	8.3334	2.82***
γ₅	-8.6208	-4.71***
γ₆	7.6387	3.94***
γ₇	-3.6650	-1.86*
γ₈	1.8168	1.26
γ₉	-0.6451	-0.57
γ₁₀	1.8143	1.02

V-Lab

Rama Steel Tubes Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Rama Steel Tubes Ltd Analyses