Bayesian analysis of multi-group nonlinear structural equation models with application to behavioral finance
Structural equation models (SEMs) have been widely used to determine the relationships among certain observed and latent variables in behavioral finance. The purpose of this paper is to develop a Bayesian approach for analysing multi-group nonlinear SEMs. Using recently developed tools in statistical computing, such as the Gibbs sampler, we propose an efficient method to estimate parameters and select an appropriate model. The proposed method is used to investigate the relationships among all identified influential factors that have an impact on the motivation for insider trading within the framework of behavioral finance.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 12 (2012)
Issue (Month): 3 (September)
|Contact details of provider:|| Web page: http://www.tandfonline.com/RQUF20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/RQUF20|
When requesting a correction, please mention this item's handle: RePEc:taf:quantf:v:12:y:2012:i:3:p:477-488. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If references are entirely missing, you can add them using this form.