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	1.2429	3.68***
αARCH	0.1863	3.39***
βGARCH	0.8136	14.75***

γ₁	-1.1528	-1.51
γ₂	-1.6539	-0.78
γ₃	4.7834	2.11**
γ₄	-2.8327	-1.38
γ₅	2.1237	0.71
γ₆	4.1813	1.78*
γ₇	-7.6785	-2.99***
γ₈	-2.3933	-0.57
γ₉	8.5964	1.49

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.2429	3.68***
α ARCH Response to squared shocks	0.1863	3.39***
β GARCH Volatility persistence	0.8136	14.75***

γ₁	-1.1528	-1.51
γ₂	-1.6539	-0.78
γ₃	4.7834	2.11**
γ₄	-2.8327	-1.38
γ₅	2.1237	0.71
γ₆	4.1813	1.78*
γ₇	-7.6785	-2.99***
γ₈	-2.3933	-0.57
γ₉	8.5964	1.49

V-Lab

Ral Yatirim Holding As Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Ral Yatirim Holding As Analyses