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ESG-Constrained Pairs Trading in Indian Equities

Article arXiv papers · Author: Eeshaan Dutta et al.
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Summary

The document describes a pairs trading framework that incorporates environmental, social, and governance ratings when choosing stocks. It combines ESG-based pair selection with cointegration analysis to identify candidate relationships, then uses technical indicators to guide trade execution.

The paper reports that back-tests produced positive returns and outperformed conventional pairs trading while retaining ESG criteria. The supplied description gives no performance figures, test design, benchmark details, or information about transaction costs and robustness. Its claims should therefore be read as a summary of reported results rather than evidence that the approach will generalize to live Indian markets.

Key ideas

  • ESG ratings are used alongside cointegration analysis to select equity pairs.
  • The framework applies pairs trading within an Indian market setting.
  • Technical indicators are included to guide trade execution.
  • The document reports favorable back-test comparisons but provides no methodological or performance details.

Tags

EquitiesPairs tradingTechnical indicatorsBacktesting
Full text
# ESG driven pairs algorithm for sustainable trading: Analysis from the Indian market


# ESG driven pairs algorithm for sustainable trading: Analysis from the Indian market









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.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.