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	0.7644	2.23**
αARCH	0.2063	5.38***
βGARCH	0.7907	23.67***

γ₁	-20.8030	-2.32**
γ₂	37.1057	2.25**
γ₃	-20.6746	-1.93*
γ₄	4.0353	1.18
γ₅	1.4538	1.00
γ₆	-4.1656	-2.30**
γ₇	6.8561	3.65***
γ₈	-10.4249	-5.76***
γ₉	13.2829	7.83***
γ₁₀	-11.5522	-5.53***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.7644	2.23**
α ARCH Response to squared shocks	0.2063	5.38***
β GARCH Volatility persistence	0.7907	23.67***

γ₁	-20.8030	-2.32**
γ₂	37.1057	2.25**
γ₃	-20.6746	-1.93*
γ₄	4.0353	1.18
γ₅	1.4538	1.00
γ₆	-4.1656	-2.30**
γ₇	6.8561	3.65***
γ₈	-10.4249	-5.76***
γ₉	13.2829	7.83***
γ₁₀	-11.5522	-5.53***

V-Lab

Pak Tak International Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Pak Tak International Analyses