Paper: arXiv 2412.12458

Abstract

We conduct a preliminary analysis of a pairs trading strategy using the Ornstein-Uhlenbeck (OU) process to model stock price spreads. We compare this approach to a naive pairs trading strategy that uses a rolling window to calculate mean and standard deviation parameters. Our findings suggest that the OU model captures signals and trends effectively but underperforms the naive model on a risk-return basis, likely due to non-stationary pairs and parameter tuning limitations.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 4.0/10
  • Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: The paper employs advanced stochastic calculus and econometric testing (cointegration, OU process SDEs), but the empirical validation is preliminary, using a limited dataset without robust out-of-sample testing or risk management refinements.

Research Flowchart

  flowchart TD
  A["Research Goal: Compare OU Process Model vs. Naive Rolling Window<br/>for Pairs Trading Signals"] --> B
  subgraph B ["Methodology & Inputs"]
      direction LR
      B1["Pair Selection<br/>Stock Price Data"] --> B2["Spread Calculation<br/>Price Ratio or Log Spread"]
  end
  B --> C{"Computational Modeling"}
  C --> D["Naive Strategy<br/>Rolling Mean & STD"]
  C --> E["OU Process Strategy<br/>MLE Parameter Estimation"]
  D --> F
  E --> F["Strategy Evaluation<br/>Risk-Return Metrics"]
  F --> G["Findings & Outcomes"]
  subgraph G []
      direction TB
      G1["OU Model captures<br/>signals & trends effectively"]
      G2["Naive Model performs better<br/>on risk-return basis"]
      G3["Limitations: Non-stationary pairs,<br/>parameter tuning challenges"]
  end