AI-Driven Alpha Decay: Algorithmic Homogenization, Reflexive Signal Erosion, and the Paradox of Intelligent Markets

Battle Count: 77

Directly addresses the core concern of quantitative trading: the decay of alpha and factor half-lives under increasing AI adoption. Provides a formal model for predicting when strategies will become obsolete, the sequential death of crowded factors (momentum first), the declining cross-sectional dispersion among quant funds, and the systemic fragility of homogeneous algorithmic strategies. The alpha half-life theorem (18 months current vs. 60 months pre-AI) is directly actionable for strategy lifecycle management. The Red Queen equilibrium explains the persistent underperformance of hedge funds since 2009. The efficiency-fragility tradeoff informs risk management decisions for AI-heavy portfolios.

The theoretical model involves multi-layer equilibrium analysis with Ornstein-Uhlenbeck processes, Kyle-type market microstructure, performative prediction feedback loops, and Nash game theory. The empirical validation requires calibrated simulations matching 13F portfolio data, hedge fund return distributions, and tick-level Flash Crash data. The identification strategies (IV with cloud cost instruments, staggered DiD around LLM releases, PCA-based homogeneity measurement) add econometric complexity. However, the core model is analytical rather than requiring large-scale computation. The main complexity lies in parameter calibration and the multi-layer feedback structure.

The paper uses publicly available data (SEC Form 13F, cloud pricing APIs, hedge fund databases) and provides detailed parameter calibrations. However, the core contribution is a theoretical model with calibrated simulations rather than a directly reproducible ML pipeline. No code repository is mentioned. The identification strategies (IV, DiD) are described in detail but not fully implemented with results. Supplementary Materials referenced but not included in the extract. Replication would require access to the full simulation code and proprietary hedge fund databases.