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	51
αARCH	0.3977	0.34
βGARCH	0.0000	0.00
γleverage	-0.3977	-0.19
λ₁tau intercept	10.0000	0.00
λ₂forecast adj.	0.1476	0.38
λ₃tau persistence	0.8524	4.41***

Parameter	Value	t-statistic
m window Rolling window length	51
α ARCH Response to squared shocks	0.3977	0.34
β GARCH Volatility persistence	0.0000	0.00
γ leverage Additional response to negative shocks	-0.3977	-0.19
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.00
λ₂ forecast adj. Forecast performance sensitivity	0.1476	0.38
λ₃ tau persistence Long-term factor persistence	0.8524	4.41***

V-Lab

Quercus Tfi Sa ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Quercus Tfi Sa Analyses