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Strategy evaluation schemes are a crucial factor in any agent-based marketmodel, as they determine the agents' strategy preferences and consequentlytheir behavioral pattern. This study investigates how the strategy evaluationschemes adopted by agents affect their performance in conjunction with themarket circumstances. We observe the performance of three strategy evaluationschemes, the history-dependent wealth game, the trend-opposing minority game,and the trend-following majority game, in a stock market where the price isexogenously determined. The price is either directly adopted from the realstock market indices or generated with a Markov chain of order $\le 2$. Eachscheme's success is quantified by average wealth accumulated by the tradersequipped with the scheme. The wealth game, as it learns from the history, showsrelatively good performance unless the market is highly unpredictable. Themajority game is successful in a trendy market dominated by long periods ofsustained price increase or decrease. On the other hand, the minority game issuitable for a market with persistent zig-zag price patterns. We also discussthe consequence of implementing finite memory in the scoring processes ofstrategies. Our findings suggest under which market circumstances eachevaluation scheme is appropriate for modeling the behavior of real markettraders.

Market behavior and performance of different strategy evaluation schemes