EconPapers    
Economics at your fingertips  
 

Stochastic dominance statistics for risk averters and risk seekers: an analysis of stock preferences for USA and China

Zhidong Bai, Hua Li, Michael McAleer and Wing-Keung Wong

Quantitative Finance, 2015, vol. 15, issue 5, 889-900

Abstract: We derive the limiting process of stochastic dominance statistics for risk averters as well as for risk seekers when the underlying processes are dependent or independent. We take account of the dependency of the partitions and propose a bootstrap method to decide the critical point. In addition, we illustrate the applicability of the stochastic dominance statistics for both risk averters and risk seekers to analyse the dominance relationship between the Chinese and US stock markets in the entire period as well as the sub-periods before and after the crises, including the internet bubble and the recent sub-prime crisis. The findings could be used to draw inferences on the preferences of risk averters and risk seekers in investing in the Chinese and US stock markets. The results also enable us to examine whether there are arbitrage opportunities in these markets, and whether these markets are efficient and investors are rational.

Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (61)

Downloads: (external link)
http://hdl.handle.net/10.1080/14697688.2014.943273 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Stochastic Dominance Statistics for Risk Averters and Risk Seekers: An Analysis of Stock Preferences for USA and China (2012) Downloads
Working Paper: Stochastic Dominance Statistics for Risk Averters and Risk Seekers: An Analysis of Stock Preferences for USA and China (2012) Downloads
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:taf:quantf:v:15:y:2015:i:5:p:889-900

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20

DOI: 10.1080/14697688.2014.943273

Access Statistics for this article

Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral

More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-22
Handle: RePEc:taf:quantf:v:15:y:2015:i:5:p:889-900