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	0.9321	3.13***
αARCH	0.1409	10.32***
βGARCH	0.8237	47.19***

γ₁	-0.7806	-7.76***
γ₂	1.0508	6.47***
γ₃	-0.3214	-2.69***
γ₄	0.1265	1.45
γ₅	-0.1444	-2.11**
γ₆	0.1542	2.26**
γ₇	-0.1549	-2.35**
γ₈	-0.0731	-1.16
γ₉	0.3600	5.70***
γ₁₀	-0.3097	-4.10***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.9321	3.13***
α ARCH Response to squared shocks	0.1409	10.32***
β GARCH Volatility persistence	0.8237	47.19***

γ₁	-0.7806	-7.76***
γ₂	1.0508	6.47***
γ₃	-0.3214	-2.69***
γ₄	0.1265	1.45
γ₅	-0.1444	-2.11**
γ₆	0.1542	2.26**
γ₇	-0.1549	-2.35**
γ₈	-0.0731	-1.16
γ₉	0.3600	5.70***
γ₁₀	-0.3097	-4.10***

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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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