ESG driven pairs algorithm for sustainable trading: Analysis from the Indian market
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917575896596480 |
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| author | Dutta, Eeshaan Diwan, Sarthak Chakrabarty, Siddhartha P. |
| author_facet | Dutta, Eeshaan Diwan, Sarthak Chakrabarty, Siddhartha P. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_14761 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | ESG driven pairs algorithm for sustainable trading: Analysis from the Indian market Dutta, Eeshaan Diwan, Sarthak Chakrabarty, Siddhartha P. Trading and Market Microstructure 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. |
| title | ESG driven pairs algorithm for sustainable trading: Analysis from the Indian market |
| topic | Trading and Market Microstructure |
| url | https://arxiv.org/abs/2401.14761 |