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	36
αARCH	0.1642	9.10***
βGARCH	0.8444	46.20***
γleverage	-0.1641	-7.35***
λ₁tau intercept	10.0000	0.45
λ₂forecast adj.	0.9880	10.33***
λ₃tau persistence	0.0053	13.75***

Parameter	Value	t-statistic
m window Rolling window length	36
α ARCH Response to squared shocks	0.1642	9.10***
β GARCH Volatility persistence	0.8444	46.20***
γ leverage Additional response to negative shocks	-0.1641	-7.35***
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.45
λ₂ forecast adj. Forecast performance sensitivity	0.9880	10.33***
λ₃ tau persistence Long-term factor persistence	0.0053	13.75***

V-Lab

Asia Medical and Agricultural Laboratory and Research Center PCL ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Asia Medical and Agricultural Laboratory and Research Center PCL Analyses