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	0.1868	4.55***
αARCH	0.2047	4.55***
βGARCH	0.4657	4.01***

γ₁	8.7956	1.38
γ₂	-8.1415	-0.76
γ₃	-14.0036	-1.54
γ₄	8.7085	1.13
γ₅	18.7042	2.57**
γ₆	-16.8968	-2.45**
γ₇	-9.3966	-1.43
γ₈	33.6402	5.49***
γ₉	-41.4912	-4.76***
γ₁₀	43.1939	3.01***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.1868	4.55***
α ARCH Response to squared shocks	0.2047	4.55***
β GARCH Volatility persistence	0.4657	4.01***

γ₁	8.7956	1.38
γ₂	-8.1415	-0.76
γ₃	-14.0036	-1.54
γ₄	8.7085	1.13
γ₅	18.7042	2.57**
γ₆	-16.8968	-2.45**
γ₇	-9.3966	-1.43
γ₈	33.6402	5.49***
γ₉	-41.4912	-4.76***
γ₁₀	43.1939	3.01***

V-Lab

PT Citra Buana Prasida TBK Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

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Parameter Estimates

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