Paper: arXiv 2505.15611
Authors: Emilio Barucci, Yuheng Lan
Abstract
We deal with the optimal execution problem when the broker’s goal is to reach a performance barrier avoiding a downside barrier. The performance is provided by the wealth accumulated by trading in the market, the shares detained by the broker evaluated at the market price plus a slippage cost yielding a quadratic inventory cost. Over a short horizon, this type of remuneration leads, at the same time, to a more aggressive and less risky strategy compared to the classical one, and over a long horizon the performance turns to be poorer and more dispersed.
Complexity vs Empirical Score
- Math Complexity: 9.0/10
- Empirical Rigor: 2.0/10
- Quadrant: Lab Rats — theoretically deep, empirically untested
Why this score: The paper is mathematically dense, featuring continuous-time stochastic calculus, HJB equations, and closed-form derivations typical of theoretical quantitative finance. It lacks empirical backtests, real-world data, or implementation details, relying solely on analytical solutions and theoretical analysis.
Research Flowchart
flowchart TD A["Research Goal:<br>Optimal Execution with Performance Barriers"] B["Methodology:<br>Dynamic Programming & HJB Equation"] C["Inputs:<br>Market Data, Slippage & Inventory Costs"] D["Computation:<br>Optimal Strategy via Lagrange Multipliers"] E["Outcome 1:<br>Short-term: Aggressive but Low Risk"] F["Outcome 2:<br>Long-term: Poorer & Dispersed Performance"] A --> B B --> C C --> D D --> E D --> F