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	116
αARCH	0.1711	14.76***
βGARCH	0.8366	79.71***
γleverage	-0.0270	-2.78***
λ₁tau intercept	1.8449	0.14
λ₂forecast adj.	0.0000	0.00
λ₃tau persistence	0.9993	76.91***

Parameter	Value	t-statistic
m window Rolling window length	116
α ARCH Response to squared shocks	0.1711	14.76***
β GARCH Volatility persistence	0.8366	79.71***
γ leverage Additional response to negative shocks	-0.0270	-2.78***
λ₁ tau intercept Baseline long-term coefficient	1.8449	0.14
λ₂ forecast adj. Forecast performance sensitivity	0.0000	0.00
λ₃ tau persistence Long-term factor persistence	0.9993	76.91***

V-Lab

Yamashita Health Care Hldgs ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Yamashita Health Care Hldgs Analyses