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	0.3988	1.70*
αARCH	0.0830	3.09***
βGARCH	0.8559	16.17***

γ₁	1.8950	0.72
γ₂	-4.2705	-1.08
γ₃	4.4701	1.84*
γ₄	-4.1851	-2.19**
γ₅	4.7842	1.72*
γ₆	-4.5140	-1.68*
γ₇	2.8337	1.49
γ₈	0.0503	0.03
γ₉	-2.9411	-1.26
γ₁₀	2.0011	0.80

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.3988	1.70*
α ARCH Response to squared shocks	0.0830	3.09***
β GARCH Volatility persistence	0.8559	16.17***

γ₁	1.8950	0.72
γ₂	-4.2705	-1.08
γ₃	4.4701	1.84*
γ₄	-4.1851	-2.19**
γ₅	4.7842	1.72*
γ₆	-4.5140	-1.68*
γ₇	2.8337	1.49
γ₈	0.0503	0.03
γ₉	-2.9411	-1.26
γ₁₀	2.0011	0.80

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