forceval |

Evaluate different forecasts of a series, and perform the forecast combination test.

Syntax

series.forceval(options) forecast_data

You should specify the forecast data to be evaluated by entering a list of objects as forecast_data. The list may be a list of series objects, a group object, a series naming pattern (such as “f*” to indicate all series starting with the letter “F”), or a list of equation objects.

If a list of equations is entered, EViews will automatically forecast from those equation objects over the evaluation sample (the current workfile sample).

Options

mean | Include the Mean averaging method. |

trmean | Include the Trimmed mean averaging method. |

median | Include the Median averaging method. |

ols | Include the Least-squares averaging method. |

mse | Include the Mean Square Error averaging method. |

mseranks | Include the MSE ranks averaging method. |

aic | Include the Smoothed AIC weights averaging method. Only applicable if forecast_data is a list of equation objects. |

sic | Include the Bayesian model averaging method. Only applicable if forecast_data is a list of equation objects. |

trim=num | Set the level of trimming for the Trimmed mean method. Num should be a number between 1 and 100. Only applicable if the “trmean” option is used. |

msepwr=int | Set the power to which the MSE values are raised in the MSE ranks method. Only applicable if the “mseranks” option is used. |

s | Use a static (rather than dynamic) forecast when computing the forecasts over the training sample. Only applicable if forecast_data is a list of equation objects. |

trainsmpl=arg | Specify the sample used for calculating the averaging weights. Only applicable if the “ols”, “mse”, “mseranks”, “aic” or “sic” options are used. |

testname=arg | Save the combination test statistics into a matrix named arg. |

statname=arg | Save the names of the best performing forecasts into an svector named arg. |

Example

The commands

wfopen elecdmd.wf1

elecdmd.forcval(trainsmpl="2012M1 2012M12", mean, mse, mseranks, msepwr=2) elecf_fe*

open the workfile elecdmd.wf1 and then perform forecast evaluation using the actual series ELECDMD, and the forecast series specified by the naming pattern ELECF_FE*.

The averaging methods Mean, MSE and MSE Ranks are used, with the power of the MSE Ranks method set at “2”. A training sample of 2012M1 to 2012M12 is used to calculate the weights in the MSE and MSE Ranks methods.

Cross-references

See “Forecast Evaluation” for additional discussion.

See also Series::forcavg.