Factor investing is now quite popular in India with around 120 mutual fund smart-beta schemes (another name for factor funds) managing approximately ₹49,000 crore in assets as of June 2025. While the majority, nearly 106 schemes, focus on a single factor, a growing set of funds are adopting a multi-factor approach, constructing portfolios based on two or more factors.
Recent additions to this space include Bandhan Multi-Factor Fund and Sundaram Multi-Factor Fund, which join the existing Axis Multi-Factor Passive Fund of Fund.
Single-factor investing
Factor investing blends elements of both active and passive strategies, attempting to outperform market capitalisation-based indices by tilting portfolios towards certain stock characteristics. They passively track indices that are filtered using quantitative metrics, from broader benchmarks like the Nifty, Sensex and mid-cap and small-cap indices. For example, the Nifty 100 Low Volatility 30 index monitors the performance of the 30 least volatile stocks from the Nifty 100 universe over the previous year, using standard deviation as the selection metric.
Indian mutual funds have factor-based schemes around key investment factors such as quality, value, alpha, momentum, low volatility, and equal weight strategies.
Momentum-based funds capitalises on the tendency of well-performing stocks to continue their outperformance in the short term. These stocks are selected based on momentum scores calculated from six-month and twelve-month price returns, adjusted for daily price volatility. This factor tends to excel during trending markets and bull runs but struggles during market reversals and high volatility periods.
The quality factor identifies companies based on their return on equity, debt-to-equity ratios, and earnings growth consistency. This approach performs during economic uncertainty and market downturns when investors prioritise stability and predictability. However, quality strategies may underperform during speculative bull markets. .
Low volatility strategies target stocks with lower price fluctuations relative to the broader market, typically outperforming during bear markets and volatile periods while lagging during strong bull markets.
The value factor filters for stocks trading below their intrinsic worth based on various valuation metrics, working best during market recoveries but experiencing underperformance during bull markets.
Alpha strategies capture stocks that have outperformed markets and again perform well in trending bull markets.
Limitations of single factor investing
However, single-factor strategies carry risks. The most significant drawback is factor cyclicality, each factor experiences extended periods of underperformance. For example, value investing lagged from 2017 to 2021 before seeing a revival in 2022. Momentum surged in 2021, only to lose steam in the following year. Alpha was out of favour in 2022, but outperformed in 2024. These cycles test investor discipline. They also lead to behavioural pitfalls, such as exiting a strategy just before its recovery. Moreover, single factor approaches also overweight specific characteristics, potentially leading to sector or style biases that increase portfolio volatility.
Advantages of multi-factor investing
Multi-factor investing addresses these limitations by combining multiple factors within a single portfolio, creating a more diversified investment strategy. This approach leverages the low correlation between different factors to provide diversification benefits. Currently, mutual fund companies offer 11-odd two-factor strategies that typically combine Alpha-Low Volatility or Momentum-Quality factors. Among the multi-factor funds employing more than two factors, the two recently launched Bandhan and Sundaram funds are actively managed and utilise quantitative models to juggle multiple factors, while the existing Axis Multi Factor Passive FoF allocates equally across four factors by investing in either in-house factor funds or those from other fund houses.
However, multi-factor investing is not without flaws. It involves complex factor combinations, and investment decisions rely heavily on back-tested models that may not hold up in future. Additionally, these funds are newly launched and lack historical performance data, making it challenging to evaluate their consistency across different market cycles. Investors may benefit from waiting to observe how these funds perform across various market conditions before making investment decisions.
Published on August 2, 2025