The Audit
We evaluated every NSE-listed stock against a quality framework covering profitability, balance sheet strength, cash generation, valuation discipline, and governance — fifteen criteria in total. At each fiscal year-end from FY2013 through FY2025, we scored every stock and then measured how those quality tiers actually performed over the following twelve months, expressed as alpha relative to the Nifty 500 index. The result spans four distinct market cycles.
What Alpha vs the Index Shows
The most instructive lens is not raw return — it is alpha, the return earned above or below the Nifty 500 for the same period. Alpha isolates stock selection from market tailwinds. A stock returning 30% in a year when the Nifty 500 returned 36% has negative alpha, regardless of how good the absolute number sounds.
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Average Alpha vs Nifty 500 by Quality Tier — FY2013 to FY2025
Higher-quality (≥80% of criteria passing) vs lower-quality (<60% passing). Alpha = stock 1-yr return minus Nifty 500 return over the same period. FY periods end March 31.
INSIGHT In 9 of 13 years, lower-quality stocks delivered higher alpha than higher-quality ones. The exceptions cluster around two periods: the post-COVID recovery (FY2020–FY2021) and the early bull market of FY2013. Outside these windows, quality screening added no alpha — and often subtracted it.
Both quality tiers, on average, deliver positive alpha against the Nifty 500 — because our universe is broader than the index, and mid and small-cap stocks structurally outperform large-cap indices in bull markets. The question is which quality tier earns more of that alpha. The answer, for most years, is the lower quality one.
The Alpha Gap: When Quality Wins and When It Loses
Stripping back to the difference in alpha between quality tiers makes the pattern concrete. In most years, the gap runs in one direction. But it reverses sharply in two specific market environments.
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Alpha Gap: Higher-Quality Minus Lower-Quality (by year)
Positive bars: high-quality stocks generated more alpha than low-quality ones. Negative bars: low-quality outperformed.
INSIGHT Quality delivered its biggest alpha advantage in FY2020 (+17.6pp gap) and FY2021 (+23.8pp gap) — the post-COVID dislocation and its immediate aftermath. These are the years where owning quality businesses provided a meaningful edge. They are also years most investors associate with everything going up.
The Cycles
The thirteen-year period spans four distinct environments. Each tells a different part of the quality story.
The early bull (FY2013–FY2017). Nifty 500 compounded at approximately 16% annually. In this environment, quality screening offered mild alpha advantages in some years (FY2013, FY2016) but underperformed in others. Lower-quality stocks — many of them high-growth companies in cyclicals and capital goods — ran harder than quality-screen favourites. The margin was not decisive in either direction.
The stress years (FY2018–FY2019). This two-year window — encompassing the NBFC crisis, IL&FS collapse, and finally the COVID crash — was the ultimate test for quality investing. Standard theory says quality protects in downturns. The data says otherwise. In FY2019 alone, when the Nifty 500 fell 30%, high-quality stocks underperformed the index by 17 percentage points. Lower-quality stocks underperformed by only 11 points. Quality crashed harder. The reason: quality companies are larger, more liquid, and held by institutional investors who sell first in a panic. Illiquid smaller companies with weaker fundamentals simply could not be sold at scale.
WARNING “In the 2020 crash, 64% of high-quality stocks lost more than half their value. Quality did not protect capital. It was the most efficiently destroyed.”
The post-COVID recovery (FY2020–FY2021). This is where quality genuinely delivered. Scoring in March 2020 — at the COVID market bottom — and measuring returns to March 2021, high-quality stocks generated +60% alpha above the Nifty 500. Lower-quality stocks generated +43%. The gap of 17 percentage points is the largest quality advantage in the dataset. FY2021 extended the pattern: +43% alpha for high quality versus +19% for low quality. The recovery rewarded the businesses that could survive the dislocation and had balance sheets to grow into the recovery. For once, quality was a return predictor, not just a risk filter.
The recent cycle (FY2022–FY2025). The most recent three years have seen quality fail to deliver consistent alpha advantage. In FY2023 — a strong bull year with the Nifty 500 up 36% — lower-quality stocks generated +47% alpha versus +26% for high quality. This is the pattern that dominates most market environments in India: growth-phase companies, running high leverage and thin margins as they scale, get re-rated far more aggressively than the steady compounders that pass quality screens.
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Nifty 500 Annual Return vs Quality Alpha Gap — All Years
Each point is one fiscal year. X-axis = Nifty 500 return that year. Y-axis = alpha advantage of high quality over low quality. Points above zero = quality won; below = low quality won.
INSIGHT No clear linear relationship between market returns and the quality advantage — quality does not systematically win in bull markets or protect in bear markets. The post-COVID recovery cluster is the statistical outlier: the one regime where quality, valuations, and balance sheet strength all mattered simultaneously.
What Quality Does Predict: Recovery Leadership
The FY2020 and FY2021 data points are not noise. They reveal something structurally true about how quality behaves after a genuine market dislocation. When prices have been compressed indiscriminately — when panic selling does not distinguish between good businesses and bad ones — the businesses with strong fundamentals recover faster and further. The market re-discovers their value.
This is different from quality being a return predictor in normal markets. In normal markets, the re-rating of quality is already complete; the premium is already in the price. Only when that premium is temporarily destroyed — in a crash — does the subsequent recovery create alpha.
Where quality generates alpha: post-dislocation recovery environments, when institutional flows return to large-cap quality, periods of macro uncertainty (selective re-rating), when credit conditions tighten (balance sheet premium).
Where low quality generates alpha: normal bull markets driven by growth expectations, mid/small-cap re-rating cycles, high-growth sectors expanding into new markets, post-consolidation sectors where capex pays off.
The One Genuine Edge: Blowup Avoidance in Calm Markets
In non-crash market environments — years when the Nifty 500 moved within normal bounds — high-quality stocks did avoid the most catastrophic individual losses more reliably than low-quality ones. In years without a systemic event, roughly 6–8% of low-quality stocks suffered a loss exceeding fifty percent in twelve months, versus 0–2% of high-quality stocks.
This matters at the portfolio level. A single fifty-percent drawdown in a position takes several years of compounding to recover from. Eliminating the stocks most likely to blow up — even if it costs some return — is valuable risk management.
The caveat is critical: this protection disappears entirely in systemic crashes. When markets fall 25-30%+, quality stocks are not spared. Their liquidity becomes a liability. In the 2020 crash specifically, the quality bucket saw catastrophic losses at rates comparable to or worse than the low-quality bucket.
Implications for Investors
The evidence points to a specific and limited role for quality analysis, rather than the universal screening function it is often presented as.
Quality criteria, applied rigidly as a return-ranking tool, would have underperformed a simple broad-market index in most years of this study. An investor who bought only stocks passing all quality checks would have largely owned large, mature businesses whose upside was capped by their own predictability.
But an investor who uses quality as a floor — removing the stocks most likely to suffer permanent capital loss in normal market conditions — while positioning into higher-return opportunities within the surviving universe would have accessed a better risk-adjusted outcome than either pure quality or pure speculation.
The data also suggests a specific entry thesis: after genuine market dislocations, when quality premiums have been temporarily destroyed, rotating into high-quality businesses has historically generated alpha. The FY2020 data point — scoring at the COVID bottom, capturing the recovery — is the clearest example in this dataset.
INSIGHT “Quality investing works once a decade, right after the crash you weren’t prepared for. The rest of the time, it just makes you feel safe.”
A Note on FY2026
This analysis covers FY2013 through FY2025 — thirteen complete measurement periods. FY2026 is excluded not because the data is absent, but because the methodology requires a full twelve months of forward returns. Quality is assessed at each fiscal year-end (March 31), and performance is then measured from that same date to March 31 of the following year.
For FY2026, the scoring was completed in March 2026 — but the forward return window closes in March 2027, which has not yet occurred. Including a partial return (covering only the April–August 2026 window) would distort the alpha calculation and make FY2026 incomparable to every other year in the dataset. The current market environment — a soft bear, with the broader index down modestly since March 2026 — will form the FY2026 data point once the measurement window closes next year.
How This Research Was Done
Each stock in our NSE-listed universe was assessed annually at fiscal year-end against a set of criteria across five dimensions: profitability, financial resilience, growth trajectory, capital efficiency, and governance. Each criterion is assessed objectively against a defined threshold and scored as passing or failing.
Stocks are placed into tiers based on the share of criteria they pass. Only stocks with enough data to assess the majority of criteria are included; those without sufficient history are excluded from that year’s cohort. Banks and insurers are assessed against a modified subset of criteria, since standard measures of debt and working capital do not apply to financial intermediaries.
Forward returns are the one-year price performance of each stock beginning from the scoring date. These are compared against the Nifty 500 index return over the identical period. The difference — alpha — is the unit of comparison across quality tiers and across years. The analysis covers thirteen fiscal years from FY2013 to FY2025 with over 3,800 stock-year observations in total.
| DIMENSION | WHAT IT MEASURES |
|---|---|
| Profitability | Whether the business earns a meaningful return on the capital it employs, and whether those earnings are large enough to matter — assessed on trailing and normalised bases. |
| Financial resilience | Whether the business generates enough operating cash flow to cover its interest obligations, and whether debt is at a level that does not create existential risk in a downturn. |
| Growth trajectory | Whether revenues have grown at a meaningful rate over the prior five years — a signal that the business is not in structural decline. |
| Capital efficiency | Whether cash generated from operations has been positive over most recent years, whether working capital is managed tightly, and whether capital expenditure is broadly funded from internal cash rather than external borrowing. |
| Valuation | Whether the stock’s current earnings and book multiples are below their own historical median — a relative, not absolute, assessment. |
| Governance | Whether key insiders hold a meaningful ownership stake, and whether any of that stake has been pledged as loan collateral — a leading indicator of financial stress at the promoter level. |
METHODOLOGY Source: NSE regulatory filings and exchange price data, FY2013–FY2025. Quality scores computed at each fiscal year-end; forward returns measured to the same date twelve months later. Alpha defined as individual stock return minus Nifty 500 return over the identical period. Banks and insurance companies assessed against a modified criteria set. Returns are price-only; dividends excluded. This analysis is for informational and research purposes only and does not constitute investment advice. Past performance is not indicative of future results.
Data: AMFI public disclosures. Analysis: Punji Research. Not investment advice.