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How volatility evolves over time

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{name} Model Equation

How returns affect tomorrow's volatility

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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	56
αARCH	0.5000	6.40***
βGARCH	0.6948	30.39***
γleverage	-0.5000	-6.40***
λ₁tau intercept	0.0000	0.00
λ₂forecast adj.	0.7332	6.69***
λ₃tau persistence	0.0000	0.00

Parameter	Value	t-statistic
m window Rolling window length	56
α ARCH Response to squared shocks	0.5000	6.40***
β GARCH Volatility persistence	0.6948	30.39***
γ leverage Additional response to negative shocks	-0.5000	-6.40***
λ₁ tau intercept Baseline long-term coefficient	0.0000	0.00
λ₂ forecast adj. Forecast performance sensitivity	0.7332	6.69***
λ₃ tau persistence Long-term factor persistence	0.0000	0.00

V-Lab

Renatus Tactical Acqu Corp I MF2-GARCH Volatility Analysis

Date Range:

News Impact Curve

Volatility Forecast

Parameter Estimates

Other Renatus Tactical Acqu Corp I Analyses