🤖 AI Summary
This study investigates whether strategy homogenization erodes returns for original investors, addressing ongoing debates about the market impact of imitation behavior. By constructing an extended agent-based artificial financial market model that incorporates adjustable proportions of fundamentalist and technical traders, the paper provides the first empirical examination of how strategy imitation differentially affects the returns of distinct investor types. The findings reveal that while an increase in fundamentalist imitators enhances price stability, it simultaneously reduces their own returns; conversely, a growing population of technical imitators amplifies price volatility yet boosts their profitability. These results uncover an asymmetric return mechanism between the two strategies under group expansion, offering novel evidence for understanding the risks associated with market homogenization.
📝 Abstract
Some investors say increasing investors with the same strategy decreasing their profits per an investor. On the other hand, some investors using technical analysis used to use same strategy and parameters with other investors, and say that it is better. Those argues are conflicted each other because one argues using with same strategy decreases profits but another argues it increase profits. However, those arguments have not been investigated yet. In this study, the agent-based artificial financial market model(ABAFMM) was built by adding "additional agents"(AAs) that includes additional fundamental agents (AFAs) and additional technical agents (ATAs) to the prior model. The AFAs(ATAs) trade obeying simple fundamental(technical) strategy having only the one parameter. We investigated earnings of AAs when AAs increased. We found that in the case with increasing AFAs, market prices are made stable that leads to decrease their profits. In the case with increasing ATAs, market prices are made unstable that leads to gain their profits more.