Ethical Tenets of Stock Price Prediction Using Machine Learning Techniques: A Sustainable Approach

Title

Ethical Tenets of Stock Price Prediction Using Machine Learning Techniques: A Sustainable Approach

Creator

Vellaiparambill A.; Natchimuthu N.

Description

The visible decline of ethics primarily gets reflected in financial markets, as it portrays human actions and sentiments in numerical terms than any sector. Accuracy in Stock market prediction remains inefficient due to many known and unknown variables. Academia and industry recently relied on ML at large to track the market and monetise the movements. The norms of fairness, accuracy, dependability, transparency in financing are left unattended in ML prediction models with assumptions far from reality. This study focuses on the ethical dimension of Machine Learning models and generates a sustainable framework for investors. Specifically, the Sustainable Development goals (SDG) can enhance the prediction models in ML with improved efficiency. Along with SDG, this research broadens the variables' horizon of prediction in ML of computer science domain with concepts of Socially responsible Investing (SRI), Environmental Social and Corporate Governance (ESG), and Carbon footprints. With One hundred fifteen articles reviewed, the proposed framework ensures sustainability in investments at the grassroots level. The Electrochemical Society

Source

ECS Transactions, Vol-107, No. 1, pp. 137-149.

Date

2022-01-01

Publisher

Institute of Physics

Coverage

Vellaiparambill A., Department of Commerce, Christ Deemed to be University, Bangalore, India; Natchimuthu N., Department of Commerce, Christ Deemed to be University, Bangalore, India

Rights

Restricted Access

Relation

ISSN: 19386737; ISBN: 978-160768539-5

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1149/10701.0137ecst

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