qgarch_moments

Computes the sample mean, variance, skewness, and excess kurtosis
for a numeric series, along with simple standard errors.

Fits quadratic generalized autoregressive conditional
heteroskedasticity-in-mean (QGARCH-M) models motivated by Campbell and
Hentschel (1992). The package supports models with lambda fixed at zero,
lambda restricted to a function of the remaining parameters, lambda
estimated freely, and a threshold extension with state-dependent lambda.
It also provides tools for starting values, estimation, forecasting,
likelihood-ratio testing, moment diagnostics, and replication with the
included monthly U.S. stock market dataset.

Sanghyun Hong

qgarch

Quadratic GARCH-in-Mean Models for Volatility Feedback

Jedrzej Bialkowski

Moritz Wagner

qgarch_moments function

<dl><dt>x</dt>
<dd>A numeric vector or a one-column data frame containing the series.</dd>
<dt>scale_mean_variance</dt>
<dd>A finite scalar used to rescale the reported mean
and variance and their standard errors.</dd></dl>

Arguments

Compute sample moments for a series — qgarch_moments

<dl>

<dt>x</dt>
<dd>A numeric vector or a one-column data frame containing the series.</dd>


<dt>scale_mean_variance</dt>
<dd>A finite scalar used to rescale the reported mean
and variance and their standard errors.</dd>

</dl>

qgarch_moments: Compute sample moments for a series

Description

Usage

Value

Arguments