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

Eeshaan Dutta, Sarthak Diwan, Siddhartha P. Chakrabarty
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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.
ESG 驱动的可持续交易对算法:印度市场分析
本文提出了一种将环境、社会和治理(ESG)评级与配对交易策略相结合的算法交易框架。它通过开发一种独特的算法,将 ESG 数据与识别共同整合股票的方法相结合,满足了对社会责任投资解决方案的需求。这样就可以选择符合 ESG 原则的盈利股票对。此外,它还将技术指标纳入了这一可持续发展框架,以优化交易执行。广泛的回溯测试证明了该模型的有效性,在坚持 ESG 原则的前提下,该模型持续产生超越传统配对交易策略的正收益。这为算法交易的变革铺平了道路,为投资者、政策制定者和学术界提供了真知灼见。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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