How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

How returns affect tomorrow's illiquidity

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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	0.6108	1.61
αARCH	0.1075	5.02***
βGARCH	0.8787	48.76***

γ₁	-2.6124	-1.45
γ₂	4.1753	1.46
γ₃	-1.9079	-1.17
γ₄	0.7882	0.82
γ₅	-2.4697	-3.90***
γ₆	3.4288	7.11***
γ₇	-1.1211	-2.72***
γ₈	-0.4464	-1.28
γ₉	0.1105	0.36
γ₁₀	0.2292	0.58

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.6108	1.61
α ARCH Response to squared shocks	0.1075	5.02***
β GARCH Volatility persistence	0.8787	48.76***

γ₁	-2.6124	-1.45
γ₂	4.1753	1.46
γ₃	-1.9079	-1.17
γ₄	0.7882	0.82
γ₅	-2.4697	-3.90***
γ₆	3.4288	7.11***
γ₇	-1.1211	-2.72***
γ₈	-0.4464	-1.28
γ₉	0.1105	0.36
γ₁₀	0.2292	0.58

V-Lab

Trisul Sa Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Trisul Sa Analyses