At the start of the year, timelines fill with screenshots of gleaming charts—“This fund did 45% last year.” Within hours, investors are trawling “Top performers of 2024” and those familiar “Best Mutual Funds” lists, turning yesterday’s winners into today’s buy list.

We’ve all been there—the pull of yesterday’s winners is strong. The distinction, though, is crucial: naïve performance-chasing is impulse; momentum is a discipline. It treats recent returns as information about how news diffuses and positioning adjusts, then applies rules around entry, exit, and risk. Our question was whether Indian funds are, intentionally or not, tilting toward that momentum factor—and if any generate alpha beyond it.

Understanding Momentum: A Proven Investment Strategy

Before we dive into our findings, let’s clarify something important: momentum investing isn’t some newfangled trend—it’s one of the most researched and academically validated investment strategies in quantitative finance.

Think of it simply: momentum investing means buying stocks that have been performing well recently, based on the principle that outperformance tends to persist in the short to medium term. This effect was first rigorously documented by Jegadeesh and Titman (1993), who showed that stocks with high returns over the past 3-12 months continue to outperform over the subsequent months.

But why does momentum work? The academic consensus points to behavioral biases. Investors tend to under-react to positive news—they wait for confirmation before buying, creating a gradual price adjustment. Conversely, they over-react to negative news, selling quickly on bad information. This asymmetric response creates momentum patterns that skilled investors can exploit.

The NIFTY500 Momentum 50 index, which we used as our benchmark, systematically captures this effect by selecting the top 50 stocks from the NIFTY 500 universe based on momentum scores. From 2005-2025, this approach delivered a 21.59% CAGR versus the NIFTY 50’s 13.92% return.

So the question we wanted to explore wasn’t whether momentum works—we know it does. The question was: Is the alpha generated by Indian mutual funds purely down to momentum exposure, or is there genuine value creation beyond that momentum bet?

Our Research Approach

We decided to investigate whether Indian mutual funds show measurable momentum exposure, and if so, whether they’re generating alpha beyond that momentum exposure.

Using data from 425 Indian mutual funds (filtered from an initial universe of 526 funds to include only those with at least 756 trading days of data), we ran regression analysis using 3-year rolling windows. Think of it as asking each fund, repeatedly over time: “How closely do your returns move with momentum stocks?”

The analysis produces two key metrics:

• Beta: How much the fund moves with momentum (0.8 means it captures 80% of momentum moves)
• Alpha: The excess returns the fund generates beyond what momentum exposure explains

The Striking Discovery

The results were remarkable: 91% of Indian mutual funds showed consistently significant momentum exposure.

This level of convergence suggests that momentum has become a dominant factor in how Indian funds are managed, whether consciously or unconsciously. Only 9% of funds operated with strategies that were statistically independent of momentum patterns.

But here’s where the story gets more interesting. We discovered a strong relationship between momentum exposure and alpha generation.

The Alpha-Momentum Trade-off

When we analyzed the regression results across all funds, a clear pattern emerged: after controlling for momentum exposure, most funds fail to generate statistically significant alpha

The relationship between momentum exposure and alpha generation also revealed an interesting trade-off: a negative correlation of -0.533 between beta and alpha, indicating that funds with higher momentum exposure tended to generate lower excess returns beyond that momentum exposure.

Academic Context: The Persistence Problem

This aligns with broader academic research. Mark Carhart’s seminal 1997 study “On Persistence in Mutual Fund Performance” found that mutual fund performance persistence largely disappears when you account for momentum factors. More recently, Choi and Zhao (2020) demonstrated that alpha persistence has become even more elusive in modern markets.

Our findings support this academic consensus: sustainable alpha generation appears to be the exception rather than the rule.

The Performance Reality Check

This led us to an obvious question: If funds are already exhibiting momentum characteristics, could we deliver better returns by systematically chasing funds with high past year performance—a strategy millions of investors follow—rather than simply investing in a momentum index directly?

We tested this by implementing a systematic fund selection strategy that mimics how investors typically chase performance.

Here’s how we structured the backtest:

Fund Selection Strategy:

• Annual Review: Every year-end, rank all funds by their 12-month momentum (trailing returns)
• Portfolio Construction: Select the top decile (top 10%) and create an equal-weighted portfolio
• Rebalancing: At each year-end review, funds that remain in the top decile continue with their existing weights; new entrants receive equal weights.

We compared this momentum-based fund selection against direct investment in the NIFTY500 Momentum 50 index from 2016 to 2025:

Performance Results (2016-2025):

• NIFTY500 Momentum 50: 18.56% CAGR, 0.65 Sharpe Ratio
• Top Fund Selection (Gross): 15.67% CAGR, 0.64 Sharpe Ratio

The momentum index delivered superior returns with comparable risk metrics and significantly lower costs. Even before considering taxes, the systematic fund selection strategy underperformed the direct momentum index by 288 basis points annually. This raises questions about the value proposition of paying active management fees for what appears to be factor exposure.

The Exceptional Few

Of course, there are exceptions. We identified 3 funds that achieved both high momentum exposure (beta >0.8) and sustained alpha generation (>5% annually): These represent less than 1% of our sample. The rarity suggests that combining momentum exposure with alpha generation is exceptionally challenging.

What This Means for Investors

The prevalence of momentum exposure across Indian funds reveals something important about the current state of active management. When 91% of funds show significant momentum characteristics, it suggests that momentum has become a dominant factor in Indian fund management. 
The relationship between momentum exposure and alpha generation suggests that investors might be paying active management fees for factor exposure that could be obtained more cost-effectively through direct index investing.

Active management can deliver value, but our data shows it’s exceptionally rare and difficult to access consistently. This suggests a clear framework: most investors should embrace simple, low-cost factor investing for their core portfolio, while aggressive investors seeking alpha should focus exclusively on the select few managers who demonstrably generate persistent alpha beyond systematic factor exposure.

The Bottom Line

Our analysis reveals that the performance-chasing behavior we see in individual investors might have parallels in professional fund management. The systematic momentum exposure across Indian funds, combined with the challenges of persistent alpha generation, creates interesting questions about the evolving role of active management.

These findings don’t provide definitive investment advice, but they do highlight important considerations about fee transparency, strategy understanding, and the evolving landscape of factor-based investing.

The next time you see a “top performing funds” list, you might want to ask: Is this fund genuinely creating alpha beyond systematic factor exposure, or could I access similar returns more cost-effectively? The answer might reshape how you think about active management in an increasingly factor-aware world.

Methodology Note

This analysis examined 425 Indian mutual funds using 3-year rolling regression windows against the NIFTY500 Momentum 50 index from 2013-2025. Data sourced from ACE MF Research Database.