sum_X_f

For details, see Eq. (20) of amendola_candila_gallo_2020;textualrumidas.

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Adds the MIxing-Data Sampling (MIDAS, Ghysels et al. (2007) <doi:10.1080/07474930600972467>) components to a variety of GARCH and MEM (Engle (2002) <doi:10.1002/jae.683>, Engle and Gallo (2006) <doi:10.1016/j.jeconom.2005.01.018>, and Amendola et al. (2024) <doi:10.1016/j.seps.2023.101764>) models, with the aim of predicting the volatility with additional low-frequency (that is, MIDAS) terms. The estimation takes place through simple functions, which provide in-sample and (if present) and out-of-sample evaluations. 'rumidas' also offers a summary tool, which synthesizes the main information of the estimated model. There is also the possibility of generating one-step-ahead and multi-step-ahead forecasts.

Vincenzo Candila

rumidas

Univariate GARCH-MIDAS, Double-Asymmetric GARCH-MIDAS and
MEM-MIDAS

sum_X_f function

<dl><dt>COEF</dt>
<dd>The sum of the parameters \(alpha\), \(\beta\), and \(\gamma/2\), if present.</dd>
<dt>DELTA</dt>
<dd>The AR coefficient.</dd>
<dt>H</dt>
<dd>The length of the multi-step-ahead predictions.</dd></dl>

Arguments

Summation function for the multi-step-ahead predictions of the GARCH--MIDAS models with the '--X' part. — sum_X_f

<dl>

<dt>COEF</dt>
<dd>The sum of the parameters \(alpha\), \(\beta\), and \(\gamma/2\), if present.</dd>


<dt>DELTA</dt>
<dd>The AR coefficient.</dd>


<dt>H</dt>
<dd>The length of the multi-step-ahead predictions.</dd>

</dl>

sum_X_f: Summation function for the multi-step-ahead predictions of the GARCH--MIDAS models with the '--X' part.

Description

Usage

Value

Arguments

References