Investigating Risk Factors for Enhanced Portfolio Performance: An AI Approach for Indian Midcap Market Analysis
- Title
- Investigating Risk Factors for Enhanced Portfolio Performance: An AI Approach for Indian Midcap Market Analysis
- Creator
- Rai, Shashank Kumar; Awasthi, Yashmita; Singh, Shanu; Ahuja, Shivam
- Description
- This research investigates the potential of machine learning (ML) for constructing portfolios that outperform human-based management, specifically focusing on the Indian midcap market. The study compares AI-based portfolio compositions, optimised using various risk measures, to the holdings of top midcap mutual funds. In this research, the top five midcap mutual funds sectoral distributions, portfolio compositions, and AI-generated portfolios are examined. According to the research, there is significant performance potential in the AI-generated portfolio, particularly when taking shorter investment horizons into account. Portfolios that maximise the Sharpe ratio produced the best returns throughout the course of the test period for four out of the six sectors, according to the research statistics. Additionally, in order to shed light on the effectiveness and possible advantages of our strategy, our study compares the suggested technique to existing investing strategies that concentrate on particular corporations as well as well-established market benchmarks. The research shows that, particularly when taking shorter investment horizons into account, the AI-generated portfolio has great performance potential. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
- Source
- Lecture Notes in Networks and Systems;Volume;1294 LNNS;pp.173-195
- Date
- 01-01-2025
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Machine learning; Nifty midcap mutual funds; Nifty midcap100; Portfolio optimisation; Risk-return dynamics; Sharpe ratio
- Coverage
- Rai S.K., Christ University, Bengaluru, India; Awasthi Y., Christ University, Bengaluru, India; Singh S., Christ University, Bengaluru, India; Ahuja S., Christ University, Bengaluru, India
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISSN: 23673370; ISBN: 978-981963252-7;
- Format
- online
- Language
- English
- Type
- Conference paper
Collection
Citation
Rai, Shashank Kumar; Awasthi, Yashmita; Singh, Shanu; Ahuja, Shivam, “Investigating Risk Factors for Enhanced Portfolio Performance: An AI Approach for Indian Midcap Market Analysis,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/25507.