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	0.8213	3.19***
αARCH	0.2843	8.23***
βGARCH	0.7150	20.75***

γ₁	0.5984	1.10
γ₂	-1.3692	-1.83*
γ₃	0.9581	3.12***
γ₄	-0.1525	-0.49
γ₅	0.1468	0.42
γ₆	-0.8411	-2.43**
γ₇	1.9192	5.07***
γ₈	-6.4724	-10.17***
γ₉	12.8893	9.68***
γ₁₀	-10.6194	-6.85***

Parameter	Value	t-statistic
ω const Unconditional variance weight	0.8213	3.19***
α ARCH Response to squared shocks	0.2843	8.23***
β GARCH Volatility persistence	0.7150	20.75***

γ₁	0.5984	1.10
γ₂	-1.3692	-1.83*
γ₃	0.9581	3.12***
γ₄	-0.1525	-0.49
γ₅	0.1468	0.42
γ₆	-0.8411	-2.43**
γ₇	1.9192	5.07***
γ₈	-6.4724	-10.17***
γ₉	12.8893	9.68***
γ₁₀	-10.6194	-6.85***

V-Lab

Suryamas Dutamakmur (Pt) Spline ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Suryamas Dutamakmur (Pt) Analyses