Signal Decay

Signal decay refers to the gradual loss of predictive power of an investment signal over time. A factor or indicator that once generated strong returns may weaken as market participants discover and exploit it. Decay can occur for several reasons: increased competition, structural market changes, or evolving investor behavior. As more capital chases the same signals, opportunities become crowded and returns compress. In quantitative research, signal decay is monitored by tracking performance across rolling periods and out-of-sample windows. Declining hit rates, rising drawdowns, or reduced alpha may indicate that a signal is losing effectiveness. To combat decay, systematic frameworks emphasize diversification across multiple signals rather than reliance on a single idea. Regular model review and adaptive weighting also help maintain relevance. Some signals decay slowly, others abruptly. This uncertainty makes continuous validation essential. Static models are vulnerable, while adaptive systems tend to be more resilient. Understanding signal decay shifts the focus from finding “perfect” indicators to building processes that evolve. Sustainable quant investing is about managing changing edges, not assuming permanence.