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
mwindow	126
αARCH	0.1595	4.54***
βGARCH	0.8147	37.41***
γleverage	0.0311	0.76
λ₁tau intercept	0.0000	0.00
λ₂forecast adj.	0.0212	0.61
λ₃tau persistence	0.9786	25.37***

Parameter	Value	t-statistic
m window Rolling window length	126
α ARCH Response to squared shocks	0.1595	4.54***
β GARCH Volatility persistence	0.8147	37.41***
γ leverage Additional response to negative shocks	0.0311	0.76
λ₁ tau intercept Baseline long-term coefficient	0.0000	0.00
λ₂ forecast adj. Forecast performance sensitivity	0.0212	0.61
λ₃ tau persistence Long-term factor persistence	0.9786	25.37***

V-Lab

GPI for Urban Growth ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other GPI for Urban Growth Analyses