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	0.8765	2.59***
αARCH	0.1398	5.48***
βGARCH	0.6907	11.08***

γ₁	-34.7269	-5.40***
γ₂	49.1376	5.46***
γ₃	-9.1241	-2.35**
γ₄	-9.8093	-4.78***
γ₅	3.8359	2.40**
γ₆	5.4686	3.45***
γ₇	-6.7231	-4.25***
γ₈	2.4328	1.36
γ₉	-0.2075	-0.09
γ₁₀	0.1715	0.06

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.8765	2.59***
α ARCH Response to squared shocks	0.1398	5.48***
β GARCH Volatility persistence	0.6907	11.08***

γ₁	-34.7269	-5.40***
γ₂	49.1376	5.46***
γ₃	-9.1241	-2.35**
γ₄	-9.8093	-4.78***
γ₅	3.8359	2.40**
γ₆	5.4686	3.45***
γ₇	-6.7231	-4.25***
γ₈	2.4328	1.36
γ₉	-0.2075	-0.09
γ₁₀	0.1715	0.06

V-Lab

BTB Korea Co Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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