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	21
αARCH	0.3156	2.89***
βGARCH	0.6276	8.64***
γleverage	-0.3156	-2.07**
λ₁tau intercept	10.0000	0.72
λ₂forecast adj.	0.2212	1.05
λ₃tau persistence	0.7663	3.48***

Parameter	Value	t-statistic
m window Rolling window length	21
α ARCH Response to squared shocks	0.3156	2.89***
β GARCH Volatility persistence	0.6276	8.64***
γ leverage Additional response to negative shocks	-0.3156	-2.07**
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.72
λ₂ forecast adj. Forecast performance sensitivity	0.2212	1.05
λ₃ tau persistence Long-term factor persistence	0.7663	3.48***

V-Lab

E Data Teknoloji Pazarlama ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other E Data Teknoloji Pazarlama Analyses