EconPapers    
Economics at your fingertips  
 

Tests for Serial Dependence in Static, Non-Gaussian Factor Models

Gabriele Fiorentini () and Enrique Sentana ()

Working Papers from CEMFI

Abstract: We derive simple algebraic expressions for score tests of serial correlation in the levels and squares of common and idiosyncratic factors in static factor models with (semi) parametrically specified elliptical distributions even though one must generally compute the likelihood by simulation. We also robustify our Gaussian tests against nonnormality. The orthogonality conditions resemble the orthogonality conditions of models with observed factors but the weighting matrices reflect their unobservability. Our Monte Carlo exercises assess the finite sample reliability and power of our proposed tests, and compare them to other existing procedures. Finally, we apply our methods to monthly US stock returns.

Keywords: ARCH; Financial returns; Kalman filter; LM tests; Non-Gaussian state space models; Predictability. (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 C32 C38 C46 C58 (search for similar items in EconPapers)
Date: 2012-10
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2) Track citations by RSS feed

Downloads: (external link)
https://www.cemfi.es/ftp/wp/1211.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cmf:wpaper:wp2012_1211

Access Statistics for this paper

More papers in Working Papers from CEMFI Contact information at EDIRC.
Bibliographic data for series maintained by Araceli Requerey ().

 
Page updated 2022-10-02
Handle: RePEc:cmf:wpaper:wp2012_1211