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Value, Quality, Momentum Value + quality + momentum
We took it to KrestTested
A decade of Indian data · 2016 to 2026

Stack value, quality and momentum, and the blend is supposed to beat any one of them. It beat the market, then quietly trailed simpler screens.

Three of the most respected edges in investing, cheapness, profitability and momentum, averaged into a single ranking. In theory the mix should lift the return and smooth the ride. On a decade of Indian data it did beat the index, but it earned less than several plainer screens, carried a worse risk adjusted return than the index itself, and came apart the moment we concentrated it. A useful lesson in what happens when you average your convictions.

₹10 lakh in the three factor blend since 2016
Growth of the portfolio · vs Nifty 500
Top decileTop 30Nifty 500

One backtest is one story. We built 258 portfolios from the screen, one for every month you could have started, held one, three and five years, and asked the plain question: does stacking three proven edges really beat backing any one of them? Rank every company three ways, by earnings yield, by gross profitability and by twelve month momentum, add the ranks, and buy the best thirty. It made about 16.7% a year against the market's 13.9%, turning ten lakh into roughly forty nine lakh. A real edge, but a modest one, and modest is a surprise when you have just stacked three edges that are each supposed to work on their own.

Concentrating the blend broke it

Here is the finding that should give any factor investor pause. On almost every strategy we have tested, holding fewer, higher conviction names lifts the return. Do that here and it collapses. Push from the best thirty into the best ten and the return did not rise, it fell to about 11% a year, below a plain index fund, at a risk adjusted return barely above zero. The blend's very top picks, the names that scored well on all three factors at once, were its weakest. That is the opposite of how conviction is supposed to work.

Return by how tightly you held the top names
Full decade return a year · vs Nifty 500
Tighter usually means richer. Here the best ten earned least, and less than the index. The sign of an averaged signal.

A spotless ranking with a soft centre

The strange part is that the ordering itself was excellent. Sorted into ten buckets, the blend's rank correlation came to −0.89, the cleanest sort we have measured, and yet its risk adjusted return landed below the index's. A pristine sort and a soft payoff at the same time is the tell of an averaged signal. Adding three rankings sends every high conviction pick toward the middle: a stock that value loves but momentum hates cancels out to a mild score, so the blend keeps the inoffensive all rounders and quietly drops the extremes, which is exactly where the biggest returns tend to hide.

Return by the blended rank, best bucket to worst
Full decade return a year · vs Nifty 500
A near perfect staircase. The ranking works; it is the reward for topping it that is thin.

The compromise basket

Look at what the blend actually held and the picture resolves. These are competent all rounders, an auto parts maker, a gas utility, a construction firm, a mid tier software name, spread across materials, industrials and consumer stocks, and about two thirds micro cap. Not a mispriced bargain nor a runaway compounder among them, because a stock extreme enough to be either would have been penalised on one of the three factors and knocked out of the top. The blend, by design, owns the sensible middle.

The stocks it kept buying
Share of yearly rebuilds each name survived
Where the money sat · average sector weight
By company size, share of the basket
16.7%
a year for the top 30 · the index made 13.9%
0.47
risk adjusted return · below the index's own 0.51
11%
for the best 10 names · concentrating made it worse
The full teardown

In the deep dive we test whether the blend at least smoothed the ride it was built to smooth, what weather it needed, and how a strategy of three edges stacks up cut for cut against the index. Short version: it diversified away the very conviction it was supposed to concentrate.

Read the full teardown

Three good ideas, averaged into a muddle

None of this means value, quality or momentum is broken. Each, on its own, has earned its reputation, and the diversified version here still beat the market and was positive in every five year window. The lesson is narrower and more useful: averaging three rankings is not the same as combining three edges. A sum of ranks rewards the stock that is merely fine at everything over the one that is exceptional at something, and exceptional is what pays. Stacking factors can work, but the way you combine them matters more than how many you own, and adding a sum of ranks is the bluntest way to do it.

So we took it to Krest, and ran it through the whole test.

KREST TESTED · RUN ON REAL HISTORY ·
Method mark
Krest Tested
We ran the three factor blend through the whole test on a decade of Indian data, cut by cut. The rigour is ours; the verdict is yours.

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Test before you trust.

Every figure on this page came from a few clicks on Krest. See this exact analysis live and interactive, or point the same test at any strategy you have ever believed.

For education only. Not investment advice or a recommendation to buy, sell, or hold any security, strategy, or product. Past performance does not guarantee future results, and all investing carries risk, including the possible loss of capital. Make your own decisions, and consider consulting a SEBI registered investment adviser.

Best effort analysis. Prepared on a best effort basis from historical data and may contain errors, omissions, or assumptions. Shared for information and discussion only, and should be independently verified before you rely on it. Krest accepts no liability for any decision made or loss incurred based on it.

Figures reflect a three factor screen (equally ranked on earnings yield, gross profit to assets and twelve month momentum, filtered to positive EBIT and market cap above ₹1,000 cr), reconstructed yearly over the last ten years of Indian data (since June 2016), measured against the Nifty 500 total return index. Multi factor combination draws on the value, quality and momentum literature. Because this rests on about ten years of data, a longer run of history could change the conclusions.

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