3% rules the market: herding behavior of a group of investors, asset market volatility, and return to the group in an ag
- PDF / 2,478,565 Bytes
- 22 Pages / 439.37 x 666.142 pts Page_size
- 75 Downloads / 161 Views
3% rules the market: herding behavior of a group of investors, asset market volatility, and return to the group in an agent-based model Sunyoung Lee1 · Keun Lee2,3 Received: 18 February 2019 / Accepted: 21 August 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract This study presents an agent-based model of capital markets by adopting simple trading rules for bounded rational agents who maintain different expectations regarding a tipping point at which price starts to change its direction from rising (falling) to falling (rising). The effect of herding behavior on the volatility of stock market prices and the rate of return to the herding group are investigated by dividing agents into one or more groups. Herding behavior by a group of agents leads to high market volatility and high return for the agents in the group. Maximum rate of return is reached when the group size is approximately 3% of the total number of agents. This finding is consistent with the actual degree of herding behavior in markets found by empirical studies. However, the rates of return decrease when the group size exceeds 3%, and the premium of the herding group tends to disappear when the group size reaches a certain level (20%) compared with that of non-herding groups. Reducing the number of groups (or increasing the average size of the herding groups) leads to high price volatility. Keywords Instability · Capital market · Tipping point · Herding behavior · Agent-based model · Rate of return JEL Classification G1 · N2
B
Keun Lee [email protected] Sunyoung Lee [email protected]
1
Korea Military Academy, Seoul, Korea
2
Seoul National University, Seoul, Korea
3
Institute for Statistical Studies and Economics of Knowledge of the National Research University Higher School of Economics, Moscow, Russia
123
S. Lee, K. Lee
1 Introduction An increasing number of studies have used agent-based model (ABM) to analyze financial markets. In contrast with neoclassical economic models that assume the optimizing behavior of agents, ABMs assume routine-based or adaptive behavioral rules for heterogeneous instead of homogenous agents (Bonabeau 2002; Yoon and Lee 2009; Thurner 2011). Since the pioneering work of the Santa Fe Artificial Stock Market model followed by Palmer et al. (1994) and LeBaron et al. (1999), other ABMs on financial markets have been developed, and they confirm that asset prices can display bubbles, crashes, and volatility clustering (Chiarella and Iori 2002; Chiarella et al. 2006, 2009; Malek and Ezzeddine 2011). This study uses the ABM approach to investigate the impact of herding behavior on financial instability and the rate of return to the herding group. Baddeley (2010) defined herding behavior as “the phenomenon of individuals deciding to follow others and imitating group behavior rather than deciding independently and atomistically on the basis of their own private information.” Herding behavior has recently become an important issue related to various phenomena in the financial market. The causes
Data Loading...
