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	1.1471	5.93***
αARCH	0.1255	4.85***
βGARCH	0.7217	16.20***

γ₁	-0.8503	-2.78***
γ₂	0.3761	0.76
γ₃	1.0987	3.29***
γ₄	-0.4740	-2.29**
γ₅	-0.3414	-2.24**
γ₆	0.3012	2.02**
γ₇	-0.2842	-1.69*
γ₈	0.5479	3.05***
γ₉	-0.8351	-3.93***
γ₁₀	0.7853	2.31**

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1471	5.93***
α ARCH Response to squared shocks	0.1255	4.85***
β GARCH Volatility persistence	0.7217	16.20***

γ₁	-0.8503	-2.78***
γ₂	0.3761	0.76
γ₃	1.0987	3.29***
γ₄	-0.4740	-2.29**
γ₅	-0.3414	-2.24**
γ₆	0.3012	2.02**
γ₇	-0.2842	-1.69*
γ₈	0.5479	3.05***
γ₉	-0.8351	-3.93***
γ₁₀	0.7853	2.31**

V-Lab

Cadence Capital Ltd Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Cadence Capital Ltd Analyses