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	5.0000	0.13
αARCH	0.0000	0.00
βGARCH	0.9574	45.34***
γleverage	0.0807	4.10***

Parameter	Value	t-statistic
ω const Unconditional variance weight	5.0000	0.13
α ARCH Response to squared shocks	0.0000	0.00
β GARCH Volatility persistence	0.9574	45.34***
γ leverage Additional response to negative shocks	0.0807	4.10***

V-Lab

GPI for Urban Growth Asymmetric ILLIQ Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other GPI for Urban Growth Analyses