Concentration and variability of forecasts in artificial investment games: an online experiment on WeChat
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Concentration and variability of forecasts in artificial investment games: an online experiment on WeChat Xiu Chen1 · Fuhai Hong2 · Xiaojian Zhao3,4 Received: 6 November 2017 / Revised: 26 September 2019 / Accepted: 1 November 2019 © Economic Science Association 2019
Abstract This paper is the first to use the WeChat platform, one of the largest social networks, to conduct an online experiment of artificial investment games. We investigate how people’s forecasts about the financial market and investment decisions are shaped by whether they can observe others’ forecasts and whether they engage in public or private investment decisions. We find that with forecast sharing, subjects’ forecasts converge but in different directions across groups; consequently, forecast sharing does not lead to better forecasts nor more individually rational investment decisions. Whether or not subjects engage in public investment decisions does not significantly affect forecasts or investment. Keywords Forecast · Investment · Online experiment · WeChat JEL Classification C90 · D83 · D84 · G11
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s1068 3-019-09632-z) contains supplementary material, which is available to authorized users. * Xiu Chen [email protected] Fuhai Hong [email protected] Xiaojian Zhao [email protected] 1
Southern University of Science and Technology, Shenzhen, China
2
Department of Economics, Lingnan University, Tuen Mun, Hong Kong
3
Monash University, Clayton, Australia
4
Chinese University of Hong Kong (Shenzhen), Shenzhen, China
13
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X. Chen et al.
1 Introduction Information and communication technologies have drastically improved information accessibility and transparency at the grassroot level. With these technologies, people are free to communicate and share information without barriers. For many real-world economic or political decisions such as shopping and voting, people typically share information and opinions before taking actions. While the actions taken are quite often unobservable, the advancement of technologies has greatly facilitated the pre-play communications. Take the financial market for example. An individual’s investment decisions are usually private and hard to observe, but investors’ attitudes are often exchanged through online or offline gossips before actual moves are made. Financial economists (e.g. Antweiler and Frank 2004; Chen et al. 2014) have started to use textual analysis to study the emerging role of social media in financial markets, and found that shared opinions as soft information can predict performance in financial markets. In this paper, we report findings from an online experiment where subjects made unobservable investment decisions but were allowed to share their forecasts on the financial market. Our experiment investigates whether communication causes convergence in individuals’ forecasts about the financial market and how this influences individuals’ subsequent investment decisions.
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