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

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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	1.4278	1.72*
αARCH	0.1610	4.76***
βGARCH	0.8377	24.89***

γ₁	0.0243	0.01
γ₂	-2.4002	-0.44
γ₃	5.7306	1.96**
γ₄	-10.2559	-2.69***
γ₅	17.2142	2.42**
γ₆	-16.7658	-2.53**
γ₇	8.6396	2.58***
γ₈	-1.2954	-0.54
γ₉	-2.9710	-1.08
γ₁₀	2.6497	0.92

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.4278	1.72*
α ARCH Response to squared shocks	0.1610	4.76***
β GARCH Volatility persistence	0.8377	24.89***

γ₁	0.0243	0.01
γ₂	-2.4002	-0.44
γ₃	5.7306	1.96**
γ₄	-10.2559	-2.69***
γ₅	17.2142	2.42**
γ₆	-16.7658	-2.53**
γ₇	8.6396	2.58***
γ₈	-1.2954	-0.54
γ₉	-2.9710	-1.08
γ₁₀	2.6497	0.92

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