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	106
αARCH	0.0804	7.75***
βGARCH	0.9302	113.31***
γleverage	-0.0804	-6.30***
λ₁tau intercept	0.3155	0.35
λ₂forecast adj.	0.0263	1.47
λ₃tau persistence	0.1297	5.27***

Parameter	Value	t-statistic
m window Rolling window length	106
α ARCH Response to squared shocks	0.0804	7.75***
β GARCH Volatility persistence	0.9302	113.31***
γ leverage Additional response to negative shocks	-0.0804	-6.30***
λ₁ tau intercept Baseline long-term coefficient	0.3155	0.35
λ₂ forecast adj. Forecast performance sensitivity	0.0263	1.47
λ₃ tau persistence Long-term factor persistence	0.1297	5.27***

V-Lab

Trisul Sa ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Trisul Sa Analyses