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	1.1972	0.63
αARCH	0.5854	0.02
βGARCH	0.4146	0.01

γ₁	8.7901	0.14
γ₂	-10.1904	-0.05
γ₃	-20.2308	-0.09
γ₄	52.2981	0.19
γ₅	-120.2118	-0.07
γ₆	159.2845	0.06
γ₇	16.3096	0.01
γ₈	-199.3075	-0.04
γ₉	161.4629	0.04

Parameter	Value	t-statistic
ω const Unconditional variance weight	1.1972	0.63
α ARCH Response to squared shocks	0.5854	0.02
β GARCH Volatility persistence	0.4146	0.01

γ₁	8.7901	0.14
γ₂	-10.1904	-0.05
γ₃	-20.2308	-0.09
γ₄	52.2981	0.19
γ₅	-120.2118	-0.07
γ₆	159.2845	0.06
γ₇	16.3096	0.01
γ₈	-199.3075	-0.04
γ₉	161.4629	0.04

V-Lab

Oriental System Technology Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Oriental System Technology Analyses