Heterogeneous Trader Responses to Macroeconomic Surprises: Simulating Order Flow Dynamics

ArXiv ID: 2505.01962 “View on arXiv”

Authors: Haochuan Wang

Abstract

Understanding how market participants react to shocks like scheduled macroeconomic news is crucial for both traders and policymakers. We develop a calibrated data generation process DGP that embeds four stylized trader archetypes retail, pension, institutional, and hedge funds into an extended CAPM augmented by CPI surprises. Each agents order size choice is driven by a softmax discrete choice rule over small, medium, and large trades, where utility depends on risk aversion, surprise magnitude, and liquidity. We aim to analyze each agent’s reaction to shocks and Monte Carlo experiments show that higher information, lower aversion agents take systematically larger positions and achieve higher average wealth. Retail investors under react on average, exhibiting smaller allocations and more dispersed outcomes. And ambient liquidity amplifies the sensitivity of order flow to surprise shocks. Our framework offers a transparent benchmark for analyzing order flow dynamics around macro releases and suggests how real time flow data could inform news impact inference.

Keywords: agent-based modeling, CAPM, macroeconomic shocks, softmax discrete choice, order flow analysis, Multi-Asset

Complexity vs Empirical Score

• Math Complexity: 6.0/10
• Empirical Rigor: 3.0/10
• Quadrant: Lab Rats
• Why: The paper employs advanced mathematical concepts like softmax discrete choice, an extended CAPM with macroeconomic shocks, and Monte Carlo simulations, which indicates a moderately high math complexity. However, it is entirely simulation-based with no real backtesting, datasets, or implementation details, resulting in low empirical rigor.

  flowchart TD
    A["Research Goal: <br> Model heterogeneous macro shock responses"] --> B["Methodology: <br> Extended CAPM + Agent-Based Modeling"]
    
    B --> C{"Data / Inputs"}
    C --> C1["Trader Archetypes:<br>Retail, Pension, Institutional, Hedge"]
    C --> C2["Macro Shocks:<br>CPI Surprises"]
    C --> C3["Market Conditions:<br>Ambient Liquidity"]
    
    C --> D["Computation:<br>Softmax Discrete Choice Rule"]
    D --> E["Simulation:<br>Monte Carlo Order Flow Dynamics"]
    
    E --> F["Key Outcomes"]
    F --> F1["High Info/Low Aversion:<br>Larger Positions, Higher Wealth"]
    F --> F2["Retail Investors:<br>Under-react, Dispersed Outcomes"]
    F --> F3["Liquidity Effect:<br>Amplifies Shock Sensitivity"]