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	1.7918	4.82***
αARCH	0.1837	9.37***
βGARCH	0.8143	39.30***

γ₁	0.2334	1.27
γ₂	-1.2584	-3.44***
γ₃	0.5205	0.35
γ₄	3.2550	0.76
γ₅	-4.3287	-0.97
γ₆	1.5608	0.88
γ₇	0.2175	0.70
γ₈	-0.5107	-2.44**
γ₉	0.6975	3.48***
γ₁₀	-0.6361	-2.49**

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.7918	4.82***
α ARCH Response to squared shocks	0.1837	9.37***
β GARCH Volatility persistence	0.8143	39.30***

γ₁	0.2334	1.27
γ₂	-1.2584	-3.44***
γ₃	0.5205	0.35
γ₄	3.2550	0.76
γ₅	-4.3287	-0.97
γ₆	1.5608	0.88
γ₇	0.2175	0.70
γ₈	-0.5107	-2.44**
γ₉	0.6975	3.48***
γ₁₀	-0.6361	-2.49**

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Harrisons Malyalam Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Harrisons Malyalam Ltd Analyses