algorithmic monodominance
Fitness Landscape
Algorithm strategy space with fitness intensity
Concentration Index
Top 5% fitness share as monodominance indicator
Gini Coefficient
Inequality measure across all strategies
Current Configuration
Phase Interpretation
Transitional regime: Fitness is beginning to concentrate. Some strategies are being squeezed out, but multiple peaks remain viable. The ecology is under stress but not yet collapsed.
From Concave to Convex Returns
Classical capitalism operates with mostly concave returns to scale: diminishing marginal gains, geographic fragmentation, and technological limits allow many firms to coexist. Algorithmic finance inverts this. Returns become strongly convex: more capital enables better models, better data, faster execution, which compounds into more capital. The fitness landscape transforms from a rolling terrain with many peaks into a sharpening spike where only the apex survives.
The Zero-Temperature Limit
Think of strategies as states in a Boltzmann distribution. Under normal capitalism, noise and bounded rationality spread probability mass across multiple good-enough strategies. Under ultra-optimized algorithmic competition, the system cools toward : probability mass concentrates on the single global maximum, and everyone else becomes effectively extinct. Your "only one can exist" is exactly this zero-temperature limit.
Niche Separation and Survival
The separation parameter controls how distinct different algorithmic niches are in strategy space. Even with high convexity, if niches are far enough apart, you can have several winners—each a local monopolist in their domain. When niches collapse together (low separation), competition becomes direct, and only the globally optimal strategy survives. This is why the transition to monodominance is not automatic: it requires both high convexity and niche collapse.
Background Slack and Ecosystem Dependence
The slack parameter represents the minimum fitness floor—how much room there is for marginal strategies to persist. With high slack, weak strategies can survive as liquidity providers, noise traders, or marginal participants. With no slack, the system becomes maximally harsh: any strategy below the optimal is driven to extinction. Paradoxically, the dominant algorithm needs this ecosystem: it requires counterparties, volatility, and a steady flow of inferior orders. Total annihilation would kill its own edge.
Concentration Metrics
The top-5% fitness share measures what fraction of total fitness is captured by the strongest strategies. The Gini coefficient measures inequality across the entire landscape. As you increase convexity and collapse niches, both metrics rise sharply—the signature of algorithmic monodominance. A Gini near 1 means almost all fitness is concentrated in a single point; a Gini near 0 means fitness is evenly distributed across many strategies.
What Dies Is Not Capitalism
RenTec-class algorithms do not end capitalism as a mode of production—they still operate on private capital, wage labour, and profit accumulation. What dies is capitalism as an ecology of many capitals: the ideological story of fair competition, price discovery by many participants, and equal opportunity. What replaces it is algorithmic rentier capitalism: same core logic, but with accumulation routed through opaque, closed, machine-driven systems that ordinary capital owners cannot realistically enter or understand.