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	0.8373	2.41**
αARCH	0.1947	9.68***
βGARCH	0.7753	37.02***

γ₁	-9.9301	-2.16**
γ₂	14.5656	1.81*
γ₃	-4.1382	-0.83
γ₄	-1.9431	-0.95
γ₅	2.4680	2.14**
γ₆	-1.8339	-1.99**
γ₇	1.3818	1.56
γ₈	-0.0888	-0.10
γ₉	-2.2768	-2.48**
γ₁₀	4.2683	3.91***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.8373	2.41**
α ARCH Response to squared shocks	0.1947	9.68***
β GARCH Volatility persistence	0.7753	37.02***

γ₁	-9.9301	-2.16**
γ₂	14.5656	1.81*
γ₃	-4.1382	-0.83
γ₄	-1.9431	-0.95
γ₅	2.4680	2.14**
γ₆	-1.8339	-1.99**
γ₇	1.3818	1.56
γ₈	-0.0888	-0.10
γ₉	-2.2768	-2.48**
γ₁₀	4.2683	3.91***

V-Lab

Syngen Biotech Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

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