| Year |
2024 |
| Volume/Issue/Review Month |
Volume 1 | Special Issue | October |
| Title |
Performance of AI Powered Mutual Fund: A case study of Tata QUANT Fund |
| Authors |
Munmun Mohanty, Pragyan Paramita Sarangi , Rajaram Rout, Nirmal Kumar Routra |
| Broad area |
Performance of AI Powered Mutual Fund: A case study of Tata QUANT Fund |
| Abstract |
As quant trading continues to reshape India’s mutual funds landscape, it’s crucial for
investors and fund managers to adapt to new paradigms and stay informed about industry trends.
This study is undertaken as a systematic investigation into the performance of the first AI-powered
mutual fund in India, Tata QUANT fund. Moreover, this study offers a critical analysis of the
theoretical foundation for AI-driven portfolio management, incorporating ideas from the literature
on behavioural economics and finance. This research provides important insights into the constraints
and usefulness of AI-driven funds in a developing economy environment by addressing concerns
about the marginal predictive capability of AI approaches and their ability to achieve optimal
trade-offs amidst transaction costs. Though there have been many funds based on quantitative
algorithms, Tata QUANT is the only fund that is on AI and it has a performance history of only three
years. It is seen from the analysis that though the quant funds have been performing quite well, the
Tata Quant has not been able to beat the market yet. The fund has high volatility with poor risk
adjusted return. But as the legal and regulatory landscape is opening up to the AI, it is expected
that even this fund will perform in the long run. To conclude, quant funds definitely have a great
future when technology as well as Indian capital markets develop and mature. |
| File |
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| Referenceses |
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