How volatility evolves over time

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{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	2.6268	2.37**
αARCH	0.1801	4.45***
βGARCH	0.6779	11.32***

γ₁	-1.7078	-0.88
γ₂	3.5387	1.25
γ₃	-3.4181	-2.41**
γ₄	3.0266	2.77***
γ₅	-3.0756	-2.18**
γ₆	3.0515	2.35**
γ₇	-2.1042	-2.75***
γ₈	0.9833	1.88*
γ₉	-0.3906	-0.58
γ₁₀	0.6371	0.50

Parameter	Value	t-statistic
ω const Unconditional variance weight	2.6268	2.37**
α ARCH Response to squared shocks	0.1801	4.45***
β GARCH Volatility persistence	0.6779	11.32***

γ₁	-1.7078	-0.88
γ₂	3.5387	1.25
γ₃	-3.4181	-2.41**
γ₄	3.0266	2.77***
γ₅	-3.0756	-2.18**
γ₆	3.0515	2.35**
γ₇	-2.1042	-2.75***
γ₈	0.9833	1.88*
γ₉	-0.3906	-0.58
γ₁₀	0.6371	0.50

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Bailador Technology Investments Limited Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Bailador Technology Investments Limited Analyses