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	56
αARCH	0.0702	10.09***
βGARCH	0.8879	76.57***
γleverage	0.0549	3.64***
λ₁tau intercept	3.2097	0.62
λ₂forecast adj.	0.0588	2.64***
λ₃tau persistence	0.9412	41.72***

Parameter	Value	t-statistic
m window Rolling window length	56
α ARCH Response to squared shocks	0.0702	10.09***
β GARCH Volatility persistence	0.8879	76.57***
γ leverage Additional response to negative shocks	0.0549	3.64***
λ₁ tau intercept Baseline long-term coefficient	3.2097	0.62
λ₂ forecast adj. Forecast performance sensitivity	0.0588	2.64***
λ₃ tau persistence Long-term factor persistence	0.9412	41.72***

V-Lab

SES SA ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other SES SA Analyses