Effect of social trading networks and incentives in experimental asset market

• Main Author: Lee, Aiko Ying
• Other Authors: Yohanes Eko Riyanto
• Format: Final Year Project
• Language: English
• Published: 2018
• Subjects: DRNTU::Humanities
• Online Access: http://hdl.handle.net/10356/73798
• Institution: Nanyang Technological University

Social trading is a novel way of online trading in which social networks providesthe major sourceof information for making financial decisions. The emergence of social trading platforms provides an avenue for traders to exchange strategies, discuss the impact of market events and even copying the trading actions of fellow users within the community. Social trading platforms such as eToro, Oandaand ZuluTrade, amongst many others, have experienced an unprecedented surge in popularity and prominence in recent years as they allow traders to harness the wisdom of the crowd in making investment decisions. In 2017, it was reported that Etoro had 9 million users globally and over $1 billion worth of customer deposits in just that year alone.One of the most salient features characterizing these platforms is that it allows traders to automatically copy the trading actions ofother top traders of their own choice. This provides an opportunity for novice traders to mimic the strategies of more experienced traders. Given how widespread such copying function is being increasingly utilized all over the world, it is of great interest to investigate how copying affects market outcomes as well as individual trading behavior.Currently, there is a dearth of research on the effects of social trading and copying. Hence, this study hopes to shed some light on the efficiency of such rapidly-emerging alternatives to traditional forms of investment options available to traders at large. This paper also examines how allowing traders within a social trading network to delegate part of their wealth to other top-performing traders affect outcome variables at the market level as well as individual level. At the individual level, we investigate how risk-taking behavior of delegatees varies under different incentives/compensation schemes. This is important given the fact that many real world financial contracts are written such that there is a misalignment of principal-agent incentives, to the extent that it induces excessive risk-taking on the part of the agent, bringing about far-reaching repercussions on the economy. An experimental approach is used to address these questions as it affords us a controlled environment to establish causal effects where using empirical data would be less appropriate due to numerous confounding variables in real world financial markets. This study and experimental design is motivated by the seminal paper of Smith et al. (1998) (hereafter SSW), where the occurrence of bubbles and crashes runs contrary to the efficient market hypothesis put forth by Fama (1970) which asserts that stocks should always be traded at their fair value, thus eliminating any possibility of arbitrage. Although there is copious research involving various modifications of SSW in the past decades, such as allowing short selling, tournament incentives, not allowing buyers to resell stocks, etc., there is a gap in the literature on the effects of the fast emerging trend of social trading networks on financial markets.This study contributes to a wider literature by building on the existing tools and framework of experimental asset markets to examine an emerging trend that is expected to gain even stronger prominence in the near future.Using an experimental setting, this paper investigates how compensation schemes affect delegated traders’ behavior and market outcomes under social settings.More specifically, we vary the extent to which delegated traders are liable for gains, as well as losses. Certain contracts are found to induce excessive risk-taking on the part of the delegate. Our work provides insights for policies that can potentially limit excessive risk taking in the financial industry.