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Indian Quant Funds Face Questions Over Models, Risks and Returns
Quant funds use computers, data and mathematical rules to choose stocks.
Traditional funds rely more on fund managers and research teams making judgments.
Quant funds may use factors such as momentum, value, quality, growth and low volatility.
Different funds combine these factors in different ways.
Some also let fund managers make human decisions.
Momentum is popular, but it can perform badly when market leadership changes.
The funds have produced very different results so far.
Their short history means there is limited evidence across complete market cycles.
Investors are advised to study each fund’s model instead of relying only on the word “quant.”
India’s quant-equity mutual fund category has 11 schemes managing about ₹11,700 crore, but only two have more than seven years of history.
These funds use mathematical models, data and predefined factors such as momentum, value, quality, growth and low volatility.
Strategies differ widely, with some relying mainly on models and others combining quantitative signals with fund-manager judgment.
Momentum is prominent across many schemes, while market-cap exposure and rebalancing frequencies vary significantly.
Performance has been uneven: Nippon India Quant averaged a 20% five-year rolling CAGR versus 17.5% for the Nifty 200 Total Return Index, while DSP Quant returned 12.5%.
- Who
- Indian asset management companies and investors in quant-based equity mutual funds.
- What
- Quant-based equity mutual funds are being assessed for their investment models, risks and performance.
- Where
- India’s mutual fund market.
- When
- The analysis was published on September 19, 2026; the performance comparisons cover stated one-, three- and five-year periods and the last seven-year period.
- Why
- The category has limited history, uneven returns and major differences in factor selection, portfolio risk and use of human judgment.
Case for Quant Investing
Reasons for Caution
Rules versus human bias
Case for Quant Investing
Predefined, backtested rules and limited human intervention may reduce behavioural biases and make the investment process more systematic.
Reasons for Caution
Models depend on selected factors and signals, which may stop working as market conditions change.
Diversification across factors
Case for Quant Investing
Combining factors such as value, quality, momentum and low volatility may reduce dependence on one source of returns and create more resilient portfolios.
Reasons for Caution
Multi-factor strategies do not eliminate factor risk; momentum can crash, value can remain weak, and other factors can lag in particular market environments.
Evidence of performance
Case for Quant Investing
Nippon India Quant outperformed the Nifty 200 Total Return Index in the cited five-year rolling-return comparison, and some newer funds performed relatively well over selected periods.
Reasons for Caution
Returns have been uneven, only two funds have more than seven years of history, and DSP Quant lagged the index in the cited comparison.
Key facts
- Schemes
- 11 quant-based equity mutual fund schemes
- Assets managed
- About ₹11,700 crore
- Long track records
- Only two schemes have more than seven years of history
- Common factors
- Momentum, value, quality, growth and low volatility
- Best stated long-term comparison
- Nippon India Quant averaged a 20% five-year rolling CAGR versus 17.5% for the Nifty 200 Total Return Index
- Contrasting performance
- DSP Quant recorded a 12.5% CAGR in the cited five-year rolling-return analysis
- Rebalancing
- Axis, DSP, Motilal Oswal and SBI Quant rebalance monthly; Aditya Birla and Nippon India Quant rebalance quarterly
Sources
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