Paper: arXiv 2401.14761

Abstract

This paper proposes an algorithmic trading framework integrating Environmental, Social, and Governance (ESG) ratings with a pairs trading strategy. It addresses the demand for socially responsible investment solutions by developing a unique algorithm blending ESG data with methods for identifying co-integrated stocks. This allows selecting profitable pairs adhering to ESG principles. Further, it incorporates technical indicators for optimal trade execution within this sustainability framework. Extensive back-testing provides evidence of the model’s effectiveness, consistently generating positive returns exceeding conventional pairs trading strategies, while upholding ESG principles. This paves the way for a transformative approach to algorithmic trading, offering insights for investors, policymakers, and academics.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 6.0/10 (capped from 7.5: transaction costs only partially modelled; see penalty flags)
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper uses advanced statistical tests like Engle-Granger cointegration and ADF unit root tests (high math) while providing detailed backtesting results on real Indian market data with specific performance metrics (high rigor).

Research Flowchart

  flowchart TD
  A["Research Goal: Develop ESG-integrated<br>pairs trading algorithm for Indian equities"] --> B["Data Input: Indian Stock Data<br>+ ESG Ratings"]
  B --> C["Core Methodology: Identify<br>Cointegrated Stock Pairs"]
  C --> D["Algorithm Filter: Select Pairs<br>with High ESG Scores"]
  D --> E["Execution: Apply Technical Indicators<br>for Optimal Trade Timing"]
  E --> F["Back-testing & Analysis"]
  F --> G{"Key Findings & Outcomes"}
  G --> H["Outperforms Conventional<br>Pairs Trading Strategies"]
  G --> I["Generates Consistent<br>Positive Returns"]
  G --> J["Validates Sustainable<br>Investment Framework"]

Cited References (14)

  1. R eporting M atters 2020 (2020)
  2. S tate of C limate A ction 2022 (2022)
  3. Climate change and the just transition: A guide for investor action (2018)
  4. EU E missions T rading S ystem ( EU ETS )
  5. Handbook of S ustainable F inance (2022)
  6. Carbon Finance: A Risk Management View (2021)
  7. Role of derivatives in carbon markets
  8. A Machine Learning based Pairs Trading Investment Strategy (2021)
and 6 more
  1. Algorithmic trading: winning strategies and their rationale (2013)
  2. Learn Algorithmic Trading: Build and deploy algorithmic trading systems and strategies using Python and advanced data analysis (2019)
  3. Co-integration and error correction: representation, estimation, and testing (1987)
  4. OPTICS : Ordering points to identify the clustering structure (1999)
  5. CSRH ub - Corporate Social Responsibility and Sustainability Ratings (2023)
  6. NSE - National Stock Exchange of India Ltd. (2023)

0 of 14 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.