predict.stochvolTMB

Takes a <code>stochvolTMB</code> object and produces draws from the predictive distribution of the latent volatility 
and future log-returns.

Parameter estimation for stochastic volatility models using maximum likelihood. The latent log-volatility is
integrated out of the likelihood using the Laplace approximation. The models are fitted via 'TMB' (Template Model
Builder) (Kristensen, Nielsen, Berg, Skaug, and Bell (2016) <doi:10.18637/jss.v070.i05>).

Jens Wahl

stochvolTMB

Likelihood Estimation of Stochastic Volatility Models

predict.stochvolTMB function

<dl><dt>object</dt>
<dd>A <code>stochvolTMB</code> object returned from <code>estimate_parameters</code>.</dd>
<dt>steps</dt>
<dd>Integer specifying number of steps to predict.</dd>
<dt>nsim</dt>
<dd>Number of draws from the predictive distribution.</dd>
<dt>include_parameters</dt>
<dd>Logical value indicating if fixed parameters 
should be simulated from their asymptotic distribution, i.e. 
multivariate normal with inverse hessian as covariance matrix.</dd>
<dt>...</dt>
<dd>Not is use.</dd></dl>

Arguments

Predict future returns and future volatilities — predict.stochvolTMB

<dl>

<dt>object</dt>
<dd>A <code>stochvolTMB</code> object returned from <code>estimate_parameters</code>.</dd>


<dt>steps</dt>
<dd>Integer specifying number of steps to predict.</dd>


<dt>nsim</dt>
<dd>Number of draws from the predictive distribution.</dd>


<dt>include_parameters</dt>
<dd>Logical value indicating if fixed parameters 
should be simulated from their asymptotic distribution, i.e. 
multivariate normal with inverse hessian as covariance matrix.</dd>


<dt>...</dt>
<dd>Not is use.</dd>

</dl>

predict.stochvolTMB: Predict future returns and future volatilities

Description

Usage

Value

Arguments