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	76
αARCH	0.7831	0.44
βGARCH	0.4619	1.35
γleverage	-0.5000	-0.17
λ₁tau intercept	10.0000	0.00
λ₂forecast adj.	0.9707	1.02
λ₃tau persistence	0.0293	0.46

Parameter	Value	t-statistic
m window Rolling window length	76
α ARCH Response to squared shocks	0.7831	0.44
β GARCH Volatility persistence	0.4619	1.35
γ leverage Additional response to negative shocks	-0.5000	-0.17
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.00
λ₂ forecast adj. Forecast performance sensitivity	0.9707	1.02
λ₃ tau persistence Long-term factor persistence	0.0293	0.46

V-Lab

Cynca Nordic AB ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Cynca Nordic AB Analyses