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	41
αARCH	0.0704	8.94***
βGARCH	0.9132	96.00***
γleverage	-0.0704	-7.76***
λ₁tau intercept	10.0000	0.25
λ₂forecast adj.	1.0000	38.44***
λ₃tau persistence	0.0000	0.01

Parameter	Value	t-statistic
m window Rolling window length	41
α ARCH Response to squared shocks	0.0704	8.94***
β GARCH Volatility persistence	0.9132	96.00***
γ leverage Additional response to negative shocks	-0.0704	-7.76***
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.25
λ₂ forecast adj. Forecast performance sensitivity	1.0000	38.44***
λ₃ tau persistence Long-term factor persistence	0.0000	0.01

V-Lab

Ryerson Holding Corp ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Ryerson Holding Corp Analyses