R: GARCH Prediction Function

predict-methods {fGarch}

R Documentation

GARCH Prediction Function

Description

Predicts a time series from a fitted GARCH object.

Usage

## S4 method for signature 'fGARCH'
predict(object, n.ahead = 10, trace = FALSE, mse = c("cond","uncond"),plot=FALSE,nx=NULL,crit_val=NULL,conf=NULL,...)

Arguments

`n.ahead`	an integer value, denoting the number of steps to be forecasted, by default 10.
`object`	an object of class `fGARCH` as returned by the function `garchFit`.
`trace`	a logical flag. Should the prediction process be traced? By default `trace=FALSE`.
`mse`	If set to `"cond"`, `meanError` is defined as the conditional mean errors √{E_t[x_{t+h}-E_t(x_{t+h})]^2}. If set to `"uncond"`, it is defined as √{E[x_{t+h}-E_t(x_{t+h})]^2}.
`plot`	If set to `TRUE`, the confidence intervals are computed and plotted
`nx`	The number of observations to be plotted along with the predictions. The default is `round(n*0.25)`, where n is the sample size.
`crit_val`	The critical values for the confidence intervals when `plot` is set to `TRUE`. The intervals are defined as \hat{x}_{t+h} + `crit_val[2] * meanError` and \hat{x}_{t+h} + `crit_val[1] * meanError` if two critical values are provided and \hat{x}_{t+h} \pm `crit_val * meanError` if only one is given. If you do not provide critical values, they will be computed automatically.
`conf`	The confidence level for the confidence intervals if `crit_val` is not provided. By default it is set to 0.95. The critical values are then computed using the conditional distribution that was chosen to create the `object` with `garchFit` using the same `shape` and `skew` parameters. If the conditionnal distribution was set to `"QMLE"`, the critical values are computed using the empirical distribution of the standardized residuals.
`...`	additional arguments to be passed.

Value

returns a data frame with the foloowing columns: "meanForecast", meanError, and "standardDeviation".

The number of records equals the number of forecasting steps n.ahead.

Methods

object = "ANY": Generic function.
object = "fGARCH": Predict function for objects of class "fGARCH".

Author(s)

Diethelm Wuertz for the Rmetrics R-port.

Examples

## garchFit - 
   # Parameter Estimation of Default GARCH(1,1) Model:
   set.seed(123)
   fit = garchFit(~ garch(1, 1), data = garchSim(), trace = FALSE)
   fit

## predict -
   predict(fit, n.ahead = 10)
   predict(fit, n.ahead = 10,mse="uncond")

## predict with plotting: critical values = +- 2

   predict(fit, n.ahead = 10, plot=TRUE, crit_val=2)

## predict with plotting: automatic critical values 
## for different conditional distributions

  set.seed(321)
  fit2 = garchFit(~ garch(1, 1), data = garchSim(), trace = FALSE, cond.dist="sged")

## 95% confidence level
 predict(fit2,n.ahead=20,plot=TRUE) 

 set.seed(444)
 fit3 = garchFit(~ garch(1, 1), data = garchSim(), trace = FALSE, cond.dist="QMLE")

## 90% confidence level and nx=100

 predict(fit3,n.ahead=20,plot=TRUE,conf=.9,nx=100)

[Package fGarch version 2110.80.1 Index]