UNIGE document Working paper
previous document  unige:86121  next document
add to browser collection
Title

A diagnostic criterion for approximate factor structure

Authors
Gagliardini, Patrick
Ossola, Elisa
Year 2016
Abstract We build a simple diagnostic criterion for approximate factor structure in large cross-sectional equity datasets. Given a model for asset returns with observable factors, the criterion checks whether the error terms are weakly cross-sectionally correlated or share at least one unobservable common factor. It only requires computing the largest eigenvalue of the empirical cross-sectional covariance matrix of the residuals of a large unbalanced panel. A general version of this criterion allows us to determine the number of omitted common factors. The panel data model accommodates both time-invariant and time-varying factor structures. The theory applies to random coefficient panel models with interactive fixed effects under large cross-section and time-series dimensions. The empirical analysis runs on monthly and quarterly returns for about ten thousand US stocks from January 1968 to December 2011 for several time-invariant and time-varying specifications. For monthly returns, we can choose either among time-invariant specifications with at least four financial factors, or a scaled three-factor time-varying specification. For quarterly returns, we cannot select macroeconomic models without the market factor.
Keywords Large panelApproximate factor modelAsset pricingModel selectionInteractive fixed effects
Identifiers
Full text
Structures
Research group Geneva Finance Research Institute (GFRI)
Citation
(ISO format)
GAGLIARDINI, Patrick, OSSOLA, Elisa, SCAILLET, Olivier. A diagnostic criterion for approximate factor structure. 2016 https://archive-ouverte.unige.ch/unige:86121

147 hits

47 downloads

Update

Deposited on : 2016-08-16

Export document
Format :
Citation style :