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	26
αARCH	0.1302	8.54***
βGARCH	0.7283	19.46***
γleverage	-0.1302	-2.48**
λ₁tau intercept	6.9700	1.33
λ₂forecast adj.	0.0663	6.52***
λ₃tau persistence	0.9337	95.12***

Parameter	Value	t-statistic
m window Rolling window length	26
α ARCH Response to squared shocks	0.1302	8.54***
β GARCH Volatility persistence	0.7283	19.46***
γ leverage Additional response to negative shocks	-0.1302	-2.48**
λ₁ tau intercept Baseline long-term coefficient	6.9700	1.33
λ₂ forecast adj. Forecast performance sensitivity	0.0663	6.52***
λ₃ tau persistence Long-term factor persistence	0.9337	95.12***

V-Lab

Kawasaki Setsubi Kogyo Co ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Kawasaki Setsubi Kogyo Co Analyses