Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

Importance of macroeconomic variables for variance prediction: a GARCH-MIDAS approach

In English

Författare

Summary, in English

This paper applies the GARCH-MIDAS (Mixed Data Sampling) model to examine whether information contained in macroeconomic variables can help to predict short-term and long-term components of the return variance. A principal component analysis is used to incorporate the information contained in various variables. Our results show that including low-frequency macroeconomic information in the GARCH-MIDAS model improves the prediction ability of the model, particularly for the long-term variance component. Moreover, the GARCH-MIDAS model augmented with the first principal component outperforms all other specifications, indicating that the constructed principal component can be considered a good proxy of the business cycle.

Publiceringsår

2013

Språk

Engelska

Sidor

600-612

Publikation/Tidskrift/Serie

Journal of Forecasting

Volym

32

Issue

7

Dokumenttyp

Artikel i tidskrift

Förlag

John Wiley & Sons Inc., John Wiley & Sons Inc.

Ämne

  • Probability Theory and Statistics

Nyckelord

  • Mixed data sampling
  • Long-term variance component
  • Macroeconomic variables
  • Principal component
  • Variance prediction

Status

Inpress

ISBN/ISSN/Övrigt

  • ISSN: 1099-131X