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	0.1584	14.21***
βGARCH	0.7736	66.73***
γleverage	0.1356	10.48***
λ₁tau intercept	7.1002	0.00
λ₂forecast adj.	0.1714	8.20***
λ₃tau persistence	0.8273	40.20***

Parameter	Value	t-statistic
m window Rolling window length	31
α ARCH Response to squared shocks	0.1584	14.21***
β GARCH Volatility persistence	0.7736	66.73***
γ leverage Additional response to negative shocks	0.1356	10.48***
λ₁ tau intercept Baseline long-term coefficient	7.1002	0.00
λ₂ forecast adj. Forecast performance sensitivity	0.1714	8.20***
λ₃ tau persistence Long-term factor persistence	0.8273	40.20***

V-Lab

Vizsla Silver Corp ILLIQ-MFMEM Liquidity Analysis

Date Range:

News Impact Curve

Illiquidity Forecast

Parameter Estimates

Other Vizsla Silver Corp Analyses