Recognition-Based and Familiarity-Based Portfolio Strategies - An Experimental Study
Empirical evidences show that investors tend to be biased toward investing in domestic (home bias) and local (local bias) stocks. Familiarity is considered to be one of the reasons. A similar concept was proposed by Goldstein and Gigerenzer (1999, 2002), known as the recognition heuristic: "when choosing between two objects, of which only one is recognized, choose the recognized. Investors recognize or are familiar with local stocks, expect them to provide higher returns and, therefore, invest more in such stocks". We conducted an experiment in Jena, Germany to test whether subjects show local bias and use recognition-based and familiarity-based portfolio strategies. We categorized them into an experienced and an inexperienced group; in addition, we used two data periods, i.e., bull market and bear market, to see if they behave differently in the two markets. Results show that all participants invested more of their endowments in the stock market in bull rather than bear market. All participants showed greater familiarity with local stocks. However, the experienced participants only invested more in local rather than recognized and familiar stocks; on the contrary, the inexperienced participants invested more in recognized and familiar but not local stocks. Our experiment shows no evidence that familiarity is a reason for local bias.
|Date of creation:||16 Feb 2011|
|Date of revision:|
|Contact details of provider:|| Postal: Carl-Zeiss-Strasse 3, 07743 JENA|
Phone: +049 3641/ 9 43000
Fax: +049 3641/ 9 43000
Web page: http://www.jenecon.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Greiner, Ben, 2004. "An Online Recruitment System for Economic Experiments," MPRA Paper 13513, University Library of Munich, Germany.
When requesting a correction, please mention this item's handle: RePEc:jrp:jrpwrp:2011-010. 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: (Markus Pasche)
If references are entirely missing, you can add them using this form.