Market Fluctuations Explained by Dividends and Investor Networks

Abstract

The inability of investors and academics to consistently predict, and understand the behavior of¯nancial markets has forced the search for alternative analytical frameworks. Analyzinḡ nancial markets as complex systems is a framework that has demonstrated great promises, with the use of agent-based models (ABMs) and the inclusion of network science playing an important role in increasing the relevance of the framework. Using an arti¯cial stock market created via an ABM, this paper provides a signi¯cant insight into the mechanisms that drive the returns in¯nancial markets, including periods of elevated prices and excess volatility. The paper demonstrates that the network topology that investors form and the dividend policy of¯rms signi¯cantly a®ect the behavior of the market. However, if investors have a bias to following their neighbors then the topology becomes redundant. By successfully addressing these issues this paper helps re¯ne and shape a variety of additional research tasks for the use of ABMs in uncovering the dynamics of¯nancial markets.

Understanding How Short‐Termism and a Dynamic Investor Network Affects Investor Returns: An Agent‐Based Perspective

“…Table 3 provides a summary of the baseline settings and parameter changes utilized for the various experiments. The settings were chosen to ensure a level of consistency against Harras & Sornette [37] and Oldham ( [23,27]). These papers reported that as the variable that determines the inclination of the investor to be influenced by their network increases-denoted by c 1 (see (1))-the price series begins to experience increased periods of volatility.…”

“…Allowing investors to interact with and receive information from other investors enables them to form an information network. The critical consequences of this process are that investor networks and financial networks in general have been found to be capable of affecting the behavior of the market ( [22][23][24]), and they explain trading volumes and the performance of investors ( [25,26]). Critically, this analysis has not been, nor can it be, considered in the models underwritten by a representative agent approach.…”