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	0.3853	1.78*
αARCH	0.0789	2.92***
βGARCH	0.8522	14.10***

γ₁	2.0907	0.81
γ₂	-4.6474	-1.18
γ₃	4.7593	1.96**
γ₄	-4.2696	-2.23**
γ₅	4.5944	1.71*
γ₆	-4.0997	-1.61
γ₇	2.2788	1.27
γ₈	0.6902	0.40
γ₉	-3.6910	-1.71*
γ₁₀	3.9647	1.55

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.3853	1.78*
α ARCH Response to squared shocks	0.0789	2.92***
β GARCH Volatility persistence	0.8522	14.10***

γ₁	2.0907	0.81
γ₂	-4.6474	-1.18
γ₃	4.7593	1.96**
γ₄	-4.2696	-2.23**
γ₅	4.5944	1.71*
γ₆	-4.0997	-1.61
γ₇	2.2788	1.27
γ₈	0.6902	0.40
γ₉	-3.6910	-1.71*
γ₁₀	3.9647	1.55

V-Lab

Katana Capital Ltd/Fund Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Katana Capital Ltd/Fund Analyses