Is an investor stolen their profits by mimic investors? Investigated by an agent-based model

Battle Count: 82

The paper directly addresses a fundamental concern in quantitative trading: strategy crowding and its impact on alpha decay. The finding that technical strategy crowding amplifies market instability (positive feedback) while fundamental strategy crowding stabilizes markets (negative feedback) has direct implications for strategy diversification, capacity analysis, and alpha decay modeling. However, the simplified model assumptions limit direct applicability to real trading systems. The insights are more qualitative/conceptual than quantitatively actionable.

The model involves implementing a continuous double auction mechanism, 1000+ agents with stochastic order placement, and up to 99 additional agents with specific trading rules. The agent logic is relatively simple (single-parameter strategies), but the market microstructure simulation (order matching, price formation, order cancellation) requires careful implementation. The 20 million time-step simulation is computationally intensive. Overall moderate complexity for a simulation study.

The paper provides detailed simulation parameters (δP, P_f, n, weights, τ_max, σ_ε, P_d, t_c, n_a, t_a, t_e) and describes the agent decision rules (Eq. 1-3) and order placement mechanisms. However, no code or data repository is provided. The base model is referenced to a Springer book (Mizuta and Yagi, 2025), which may contain additional implementation details. Reproduction would require implementing the continuous double auction mechanism and agent logic from scratch based on the described rules.