Momentum investing in India: an honest backtest

By Thuztra Research · 12 June 2026 · 7 min read · every number below is real engine output (methodology)

In 1993, Narasimhan Jegadeesh and Sheridan Titman published a study that embarrassed the efficient-market orthodoxy: stocks that had outperformed over the previous 3–12 months kept outperforming over the next 3–12 months. Not occasionally — systematically, across decades of data. The anomaly has since been documented in US equities, European markets, commodities, currencies — and yes, Indian equities, where NSE maintains an official factor index for it (the Nifty200 Momentum 30).

That's the promise. Most articles about momentum investing in India stop there, add a stock photo of a rocket, and link a course. We run a backtest engine, so instead we did the thing nobody selling you momentum does: we ran it, honestly, and published everything it confessed.

What momentum actually is (and isn't)

Systematic momentum is cross-sectional: rank a universe of liquid stocks by trailing return over a lookback window (academics use 3–12 months, often skipping the most recent month to dodge short-term mean reversion), hold the top slice, and re-rank on a fixed calendar. No tips, no charts, no judgement calls. That last part matters — buying a stock because it already ran 40% and a WhatsApp group is excited is not momentum investing. It's the same risk with the math removed.

What our engine shows: implementation is the strategy

We ran two common retail implementations for the ten years ending June 2026 — ₹1,00,000 starting capital, 5 bps transaction costs per rebalance leg, real NSE daily data, NIFTY 50 as benchmark:

Same factor, wildly different outcomes. The popular reel format — hold the single strongest stock from a tiny shortlist — compounded at 7.6% over a decade in which the index did roughly 11%. Negative alpha, a 46% drawdown, and after estimated capital-gains tax its ₹2.07L final equity shrinks to ₹1.62L — less than the ₹1.95L a plain 7% fixed deposit would have produced. The bank beat the strategy.

Broaden the universe to eight large-caps, hold the top three by 6-month return, rebalance monthly — and the picture changes: 15.7% CAGR and about +5.5 points of annualized alpha, at the price of a 39% drawdown you must actually sit through. Diversification across the ranked slice isn't a refinement of momentum; it is where the factor's edge lives. Concentrated "top pick" momentum is mostly noise.

The luck test most backtests never face

A good-looking equity curve can be luck wearing a costume. So our engine re-runs every strategy on hundreds of shuffled versions of the same market — same stocks, same return distribution, time order destroyed. If shuffled markets "work" as often as the real one, the strategy has no edge; it has a story.

Three more confessions

Tax is owed even when you lose to the bank. The top-1 variant churned enough to generate an estimated ₹44,895 in capital-gains tax (STCG 20%, LTCG 12.5% above ₹1.25L/FY) across the decade — payable regardless of the fact that the FD won.

Survivorship bias flatters every run. Both variants pick from stocks that are large-caps today. The companies that fell out of the index along the way — the ones a real investor in 2016 might have ranked — aren't in the test. Our engine flags this (survivorship: high) on every such run rather than pretending otherwise.

The window is a choice. The same top-1 strategy that gained 107% over ten years lost 21% over the five years ending June 2026. Anyone selling you a backtest chose its start date. Honest backtesting means showing you both.

If you still want momentum — the rules that survive

The literature and our runs agree on the discipline: a liquid universe of 50–100 names, a 6–12 month lookback, a top slice of 15–25 stocks (not one), equal weights, a fixed monthly or quarterly rebalance calendar, and absolutely no discretionary overrides — the factor's alpha historically concentrates in a few months a year, and the investor who "pauses" the system after a bad quarter usually misses them. Costs and tax scale with churn, so rebalancing more often than monthly mostly enriches your broker and the government.

All figures are backtested results from Thuztra's engine on historical NSE daily data — see the methodology. Backtests are educational research, not investment advice; past performance does not predict future results. Investments in securities are subject to market risk.