Asymmetry, Loss Aversion, and Forecasting
AbstractConditional volatility models have been used extensively in finance to capture predictable variation in the second moment of returns. However, with recent theoretical literature emphasizing the loss-averse nature of agents, this paper considers models that capture time variation in the second lower partial moment. Utility-based evaluation is carried out on several approaches to modeling the conditional second-order lower partial moment. The findings show that when agents are loss averse, there are utility gains to be made from using models that explicitly capture this feature. These results link the theoretical discussion on loss aversion to empirical modeling.
Download InfoIf 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.
Bibliographic InfoArticle provided by University of Chicago Press in its journal Journal of Business.
Volume (Year): 79 (2006)
Issue (Month): 4 (July)
Contact details of provider:
Web page: http://www.journals.uchicago.edu/JB/
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Haas, Markus, 2009. "Persistence in volatility, conditional kurtosis, and the Taylor property in absolute value GARCH processes," Statistics & Probability Letters, Elsevier, vol. 79(15), pages 1674-1683, August.
- Tony Chieh-Tse Hou, 2012. "Return persistence and investment timing decisions in Taiwanese domestic equity mutual funds," Managerial Finance, Emerald Group Publishing, vol. 38(9), pages 873-891, September.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Journals Division).
If references are entirely missing, you can add them using this form.