不同战略评价方案的市场行为与绩效
Market behavior and performance of different strategy evaluation schemes
摘要：
战略评估方案是任何基于代理的市场模型中的关键因素，因为它们决定了代理的战略偏好，从而决定了他们的行为模式。本研究探讨代理商所采用的策略评估方案如何结合市场环境影响其绩效。在价格由外生决定的股票市场中，我们观察了三种策略评估方案，即历史依赖的财富博弈、趋势反对的少数人博弈和趋势跟随的多数人博弈的绩效。该价格直接采用真实的股票市场指数，或者用$\le 2$阶的马尔可夫链生成。每个计划的成功是由配备该计划的交易者积累的平均财富来量化的。财富游戏，从历史中学习，显示出相对良好的表现，除非市场高度不可预测。多数博弈在一个由长期持续的价格上涨或下跌主导的时尚市场中是成功的。另一方面，少数人博弈适用于具有持续之字形价格模式的市场。我们还讨论了在策略的评分过程中实施有限记忆的后果。我们的研究结果表明，在何种市场环境下，每一个评估方案是适当的模拟真实的市场交易者的行为。
英文摘要：
Strategy evaluation schemes are a crucial factor in any agent-based market model, as they determine the agents' strategy preferences and consequently their behavioral pattern. This study investigates how the strategy evaluation schemes adopted by agents affect their performance in conjunction with the market circumstances. We observe the performance of three strategy evaluation schemes, the history-dependent wealth game, the trend-opposing minority game, and the trend-following majority game, in a stock market where the price is exogenously determined. The price is either directly adopted from the real stock market indices or generated with a Markov chain of order $\le 2$. Each scheme's success is quantified by average wealth accumulated by the traders equipped with the scheme. The wealth game, as it learns from the history, shows relatively good performance unless the market is highly unpredictable. The majority game is successful in a trendy market dominated by long periods of sustained price increase or decrease. On the other hand, the minority game is suitable for a market with persistent zig-zag price patterns. We also discuss the consequence of implementing finite memory in the scoring processes of strategies. Our findings suggest under which market circumstances each evaluation scheme is appropriate for modeling the behavior of real market traders.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
