Be Water: An Evolutionary Proof for Trend-Following

Paper: arXiv 2603.29593

Authors: Yijia Chen

Abstract

The proliferation of diverse, high-leverage trading instruments in modern financial markets presents a complex, “noisy” environment, leading to a critical question: which trading strategies are evolutionarily viable? To investigate this, we construct a large-scale agent-based model, “MAS-Utopia,” comprising 10,000 agents with five distinct archetypes. This society is immersed in five years of high-frequency data under a counterfactual baseline: zero transaction friction and a robust Unconditional Basic Income (UBI) safety net. The simulation reveals a powerful evolutionary convergence. Strategies that attempt to fight the market’s current - namely Mean-Reversion (“buy-the-dip”) - prove structurally fragile. In contrast, the Trend-Following archetype, which adapts to the market’s flow, emerges as the dominant phenotype. Translating this finding, we architect an LLM-driven system that emulates this successful logic. Our findings offer profound implications, echoing the ancient wisdom of “Be Water”: for investors, it demonstrates that survival is achieved not by rigid opposition, but by disciplined alignment with the prevailing current; for markets, it critiques tools that encourage contrarian gambling; for society, it underscores the stabilizing power of economic safety nets.

Complexity vs Empirical Score

• Math Complexity: 3.5/10
• Empirical Rigor: 6.5/10
• Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper presents a highly novel agent-based modeling framework (MAS-Utopia) using five years of high-frequency data to demonstrate the evolutionary dominance of trend-following strategies. While conceptual and light on deep closed-form mathematical derivations, the empirical simulation scale and integration with an LLM-driven architecture provide strong practical relevance. The overall narrative is exceptionally clear, tying agent behavior back to structural market stability.

Research Flowchart

  flowchart TD
    A[Research Question: Which trading strategies are evolutionarily viable?] --> B[Data Input: 5 Years High-Frequency Multi-Asset Market Data]
    B --> C[Simulation: MAS-Utopia Agent-Based Model<br>10,000 Agents, 5 Archetypes, Zero Friction + UBI]
    C --> D[Evolutionary Convergence Analysis]
    D --> E[Key Finding: Mean-Reversion Fails, Trend-Following Dominates]
    E --> F[Translation: LLM-Driven System Emulating Trend-Following Logic]
    F --> G[Outcomes & Implications: Market Alignment, Structural Safety Nets]

Cited References (17)

1. Asset pricing under endogenous expectations in an artificial stock market (1997)
2. Econophysics: kinetic exchange models of wealth distribution (2013)
3. Trading is hazardous to your wealth: The common stock investment performance of individual investors (2000)
4. Capital in the twenty-first century (2014)
5. Prospect theory: An analysis of decision under risk (1979)
6. On persistence in mutual fund performance (1997)
7. Why stock markets crash: critical events in complex financial systems (2003)
8. Common risk factors in the returns on stocks and bonds (1993)

0 of 17 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.