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	0.9459	3.14***
αARCH	0.1408	10.36***
βGARCH	0.8244	47.63***

γ₁	-0.7751	-7.78***
γ₂	1.0449	6.48***
γ₃	-0.3193	-2.70***
γ₄	0.1211	1.40
γ₅	-0.1363	-2.03**
γ₆	0.1488	2.23**
γ₇	-0.1609	-2.48**
γ₈	-0.0553	-0.87
γ₉	0.3468	5.35***
γ₁₀	-0.3008	-3.85***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.9459	3.14***
α ARCH Response to squared shocks	0.1408	10.36***
β GARCH Volatility persistence	0.8244	47.63***

γ₁	-0.7751	-7.78***
γ₂	1.0449	6.48***
γ₃	-0.3193	-2.70***
γ₄	0.1211	1.40
γ₅	-0.1363	-2.03**
γ₆	0.1488	2.23**
γ₇	-0.1609	-2.48**
γ₈	-0.0553	-0.87
γ₉	0.3468	5.35***
γ₁₀	-0.3008	-3.85***

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Turkiye Sise ve Cam Fabrikalari AS Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

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