Source: Baek et al., arXiv:1002.4744 (abstract only). The abstract describes an agent-based model study, not a trading system. It does make one claim we can test. A trend-following ('majority game') scheme does better when prices move in sustained runs. A trend-opposing ('minority game') scheme does better when prices zig-zag. A 'wealth game' does well unless the market is highly unpredictable: it learns from history by scoring strategies on the wealth they built up over a limited memory. This hypothesis is the simplest version of that claim: a wealth-game selector choosing between two strategies. The majority strategy follows the sign of the last price step; the minority strategy fades it. It trades SPY.USEQ, an index series like the stock indices the paper used, on the commission-free USEQ venue, with daily bars since 1993 (about 1,650 non-overlapping 5-session steps). One step is 5 sessions, so the typical move per step (about 2%) is large compared with the ~0.04% round-trip cost. The paper used daily steps, and the full paper must confirm whether its result depends on step length. After each step, each strategy's hypothetical PnL for that step is added to its score, and the score keeps only the last 26 steps. The strategy trades the higher-scoring side if that score is above 0, and stays flat otherwise. Mechanism with instrument and timeframe removed: 'choose between follow-last-move and fade-last-move by each one's trailing realised score'. Expected flat share: 25-35% of steps. A second variant is pre-registered and scored separately: an order-2 wealth game using the 4 two-step-history lookup strategies. The full paper must confirm the exact scoring rule, the memory lengths tested, and the step size used on real indices.