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	31
αARCH	0.0985	9.09***
βGARCH	0.7870	21.26***
γleverage	-0.0985	-4.69***
λ₁tau intercept	10.0000	0.75
λ₂forecast adj.	0.1897	5.32***
λ₃tau persistence	0.8103	24.11***

Parameter	Value	t-statistic
m window Rolling window length	31
α ARCH Response to squared shocks	0.0985	9.09***
β GARCH Volatility persistence	0.7870	21.26***
γ leverage Additional response to negative shocks	-0.0985	-4.69***
λ₁ tau intercept Baseline long-term coefficient	10.0000	0.75
λ₂ forecast adj. Forecast performance sensitivity	0.1897	5.32***
λ₃ tau persistence Long-term factor persistence	0.8103	24.11***

V-Lab

Baillie Gifford Japan Trust PLC/The ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Baillie Gifford Japan Trust PLC/The Analyses