Paper: arXiv 2306.00599

Abstract

Portfolio managers’ orders trade off return and trading cost predictions. Return predictions rely on alpha models, whereas price impact models quantify trading costs. This paper studies what happens when trades are based on an incorrect price impact model, so that the portfolio either over- or under-trades its alpha signal. We derive tractable formulas for these misspecification costs and illustrate them on proprietary trading data. The misspecification costs are naturally asymmetric: underestimating impact concavity or impact decay shrinks profits, but overestimating concavity or impact decay can even turn profits into losses.

Complexity vs Empirical Score

  • Math Complexity: 8.5/10
  • Empirical Rigor: 7.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper presents dense stochastic calculus and derivations of closed-form optimal trading strategies under non-linear impact, yet validates these theoretical formulas using proprietary trading data and explicit sensitivity analysis.

Research Flowchart

  flowchart TD
  A["Research Goal: Quantify cost of misspecified price impact models"] --> B["Methodology: Derive analytic formulas for misspecification cost"]
  B --> C["Inputs: Proprietary trading data, alpha signals, order sizes"]
  C --> D{"Computational Process: Simulate optimal trade schedules under varying impact assumptions"}
  D --> E["Compare outcomes: Over/under-estimation of impact concavity & decay"]
  E --> F["Key Finding: Misspecification is asymmetric"]
  F --> G["Overestimation can turn profits into losses<br>Underestimation reduces profits"]