Calculates the model's long-run average volatility.

## Syntax

**GARCHM_VL** (**[α]**, [β])

**[α]**- Required. Are the parameters of the ARCH(p) component model: [αo α1, α2 … αp] (starting with the lowest lag).
**[β]**- Optional. Are the parameters of the GARCH(q) component model: [β1, β2 … βq] (starting with the lowest lag).

## Remarks

- The underlying model is described here.
- The time series is homogeneous or equally spaced.
- The GARCH-M long-run average variance is defined as:$$V_L=\frac{\alpha_o}{1-\sum_{i=1}^p\alpha_i-\sum_{j=1}^q\beta_j}$$
- The long-run variance is not affected by our choice of shock/innovation distribution.
- The number of parameters in the input argument - [α
_{o }α_{1,}α_{2 }… α_{p}] - determines the order of the ARCH component model. - The number of parameters in the input argument - [β
_{1,}β_{2 }… β_{q}] - determines the order of the GARCH component model.

## Files Examples

## Related Links

## References

- James Douglas Hamilton; Time Series Analysis, Princeton University Press; 1st edition(Jan 11, 1994), ISBN: 691042896.
- Tsay, Ruey S.; Analysis of Financial Time Series, John Wiley & SONS; 2nd edition(Aug 30, 2005), ISBN: 0-471-690740.

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