Evolutionary selection of forecasting and quantity decision rules in experimental asset markets

Jiahua Zhu, Te Bao and Wai Mun Chia

Journal of Economic Behavior & Organization, 2021, vol. 182, issue C, 363-404

Abstract: Bao et al. (2017) find that bubbles are less likely to emerge in experimental asset markets when subjects make price forecasts only (Learning to Forecast treatment, LtF) than when they make trading quantity decisions (Learning to Optimize treatment, LtO) or both price forecasts and quantity decisions (mixed treatment). This paper provides two explanations for this difference. First, the subjects in the LtO and mixed treatment usually have a high intensity of choice parameter, which leads them to switch faster between the decision rules and a greater fraction of the population to choose the destabilizing strong trend-following rule. Second, the actual quantity decision may deviate substantially and persistently from the conditionally optimal level given the price forecasts in the mixed treatment, which amplifies the price deviation from the fundamental value. Our findings are helpful for understanding the root of financial bubbles and financial crisis, and designing policies to stabilize the market.

Keywords: Asset bubble; Heuristic switching model; Learning to forecast; Learning to optimize; Experimental economics (search for similar items in EconPapers)
JEL-codes: C91 C92 D83 D84 G01 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167268119303488
Full text for ScienceDirect subscribers only

Related works:
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:eee:jeborg:v:182:y:2021:i:c:p:363-404

DOI: 10.1016/j.jebo.2019.11.005

Access Statistics for this article

Journal of Economic Behavior & Organization is currently edited by Houser, D. and Puzzello, D.

More articles in Journal of Economic Behavior & Organization from Elsevier
Bibliographic data for series maintained by Catherine Liu ().