🔄 Sector Rotation — Indian Market
Sector rotation tracker for the Indian market as of 16 October 2026: 28 NSE sector and thematic indices ranked by relative strength against the Nifty 500, with a Relative Rotation Graph, the rotation history since 2019, sector seasonality and a backtested momentum-rotation strategy. Media leads on relative strength (+8.3% over three months against the Nifty 500's -4.6%), while CPSE is the weakest at -8.3%. The tape reads as “Risk-off / defensive” — 9 of 28 sectors are above their 200-day average and cyclicals are running -3.0% against defensives over three months. In the Leading quadrant of the RRG right now: Pharma, Private Bank, Services, Capital Markets, Bank.
Data as of 16 Oct 2026
Updates ~11:15 & ~17:15 IST on trading days
28 sectors · history since 2019
Benchmark: Nifty 500
Where the market is right now
Risk-off / defensive
Few sectors hold their long-term uptrends and defensives are outperforming — capital is playing defence.
9/28 above 200-DMA
5/28 above 50-DMA
-3.0pp cyclicals vs defensives
Media
strongest sector (1M/3M/6M blend)
+8.3% over 3 months
CPSE
weakest sector
-8.3% over 3 months
6
sectors in the Leading quadrant
10 improving · 7 weakening
20 pp
best-to-worst spread this month
how much rotation is on offer
14.5%
rotation strategy CAGR since 2019
Nifty 500 11.8%
🎯 Relative Rotation Graph — sectors vs Nifty 500
Each dot is one sector; the tail behind it is the path it travelled over the last 10 weeks.
Right = outperforming the Nifty 500; up = that outperformance is still building.
Sectors normally circle clockwise — Improving → Leading → Weakening → Lagging. A short tail means a sector is going
nowhere relative to the market; a long one pointing at the top-right corner is the classic emerging-leadership signal.
Showing 16 core sectors by default, 28 in total. Every reading also appears in words in the
leaderboard table.
🟢 Leading 6
Outperforming and still gaining — the trend is intact.
- Pharma +5.1%
- Private Bank +1.7%
- Services new +1.5%
- Capital Markets +1.9%
- Bank -0.0%
- Healthcare new +0.9%
🔵 Improving 10
Still behind the market but turning up — where new leaders are born.
- Financial Services -1.1%
- PSU Bank +1.1%
- Metal new +2.1%
- Infrastructure -2.4%
- Energy new -3.3%
- Oil & Gas -2.0%
- PSE -2.4%
- FMCG new -3.9%
- Commodities -2.9%
- CPSE -3.7%
🟡 Weakening 7
Still ahead of the market but losing momentum — leadership fading.
- Media +12.9%
- IT +13.8%
- Digital +9.8%
- Defence new +3.1%
- Realty -5.5%
- Transport & Logistics +0.8%
- Consumer Durables -3.4%
🔴 Lagging 5
Underperforming with no momentum — the classic avoid zone.
- Chemicals new -1.7%
- Manufacturing new -0.2%
- Consumption -1.0%
- Auto new -0.3%
- Core Housing -4.8%
Values shown are each sector's return minus the Nifty 500 over three months.
“New” marks a sector that changed quadrant in the last five weeks — the moments worth looking at.
🧠 How to read this map
An RRG plots two things at once. The x-axis (RS-Ratio) asks “is this sector beating the Nifty 500?” — above 100 means its relative strength is running above its own six-month norm. The y-axis (RS-Momentum) asks “is that still improving?” Put together, they sort every sector into the phase of its own cycle rather than just ranking today's return.
The useful habit is to read the tail, not the dot. A sector sitting deep in Leading with a tail curling down and right is already handing back leadership; one still inside Lagging but travelling hard toward the top-right is where new leadership usually shows up first. Sectors that hover near the 100/100 crosshair with stubby tails are simply moving with the market and carry no rotation signal at all.
Because both axes are normalised against each sector's own history, the RRG says nothing about whether the market itself is going up. A sector can lead a falling market all the way down. Pair it with the market-phase read above and the 200-day trend column in the leaderboard before acting on it.
🏆 Sector strength leaderboard
| # | Sector | RS score | Day | 1M | 3M | 6M | 1Y | vs Nifty 500 (3M) | Trend | From 52w high | RRG quadrant |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Media Cyclical | 98 | +1.92% | +8.8% | +8.3% | +16.4% | +6.8% | +12.9% | Above 50 & 200 | -0.2% | Weakening |
| 2 | IT Defensive | 90 | +3.92% | +9.8% | +9.2% | +0.4% | -10.2% | +13.8% | Above 50 & 200 | -20.8% | Weakening |
| 3 | Digital Cyclical · since 2021 | 90 | +2.09% | +1.9% | +5.2% | +7.3% | -6.4% | +9.8% | Above 50 & 200 | -10.8% | Weakening |
| 4 | Defence Cyclical · since 2022 | 83 | +0.16% | +0.9% | -1.4% | +4.5% | +13.6% | +3.1% | Above 200 only | -8.5% | Weakening |
| 5 | Pharma Defensive | 81 | -0.14% | -1.4% | +0.5% | +14.6% | +16.6% | +5.1% | Above 200 only | -5.4% | Leading |
| 6 | Private Bank Financials | 79 | +0.08% | +1.5% | -2.8% | +2.3% | -1.5% | +1.7% | Above 50 & 200 | -6.9% | Leading |
| 7 | Services Defensive · since 2019 | 73 | +1.62% | +2.3% | -3.0% | -2.5% | -8.7% | +1.5% | Above 50 only | -11.8% | Leading |
| 8 | Capital Markets Financials · since 2023 | 70 | -1.07% | +0.4% | -2.6% | -0.9% | +12.6% | +1.9% | Above 200 only | -8.0% | Leading |
| 9 | Bank Financials | 60 | +0.06% | -0.8% | -4.6% | -1.3% | -2.7% | -0.0% | Below both | -9.6% | Leading |
| 10 | Chemicals Commodity · since 2025 | 58 | -0.21% | -1.4% | -6.3% | +1.8% | -3.6% | -1.7% | Below both | -11.1% | Lagging |
| 11 | Healthcare Defensive · since 2020 | 57 | -0.26% | -3.6% | -3.7% | +8.2% | +6.3% | +0.9% | Above 200 only | -7.4% | Leading |
| 12 | Realty Cyclical | 53 | -0.33% | +0.4% | -10.1% | +5.0% | -11.5% | -5.5% | Above 200 only | -15.2% | Weakening |
| 13 | Financial Services Financials | 52 | +0.09% | +0.5% | -5.6% | -4.3% | -7.3% | -1.1% | Below both | -11.1% | Improving |
| 14 | Transport & Logistics Cyclical · since 2022 | 51 | +0.44% | -2.9% | -3.8% | +0.3% | -7.4% | +0.8% | Below both | -10.6% | Weakening |
| 15 | Manufacturing Cyclical · since 2021 | 43 | +0.35% | -2.8% | -4.7% | -2.6% | +0.6% | -0.2% | Below both | -8.9% | Lagging |
| 16 | PSU Bank Financials | 42 | +0.67% | -2.2% | -3.4% | -8.7% | +5.3% | +1.1% | Below both | -18.4% | Improving |
| 17 | Consumption Defensive | 41 | +0.45% | -2.7% | -5.6% | -3.1% | -11.4% | -1.0% | Below both | -12.5% | Lagging |
| 18 | Metal Commodity | 37 | +0.95% | -4.8% | -2.4% | -5.8% | +17.9% | +2.1% | Below both | -12.9% | Improving |
| 19 | Infrastructure Cyclical | 36 | +0.46% | -2.1% | -7.0% | -6.3% | -6.2% | -2.4% | Below both | -10.9% | Improving |
| 20 | Auto Cyclical | 36 | +0.75% | -4.2% | -4.9% | -2.5% | -4.7% | -0.3% | Below both | -13.7% | Lagging |
| 21 | Core Housing Cyclical · since 2023 | 33 | -0.13% | -1.5% | -9.4% | -3.4% | -11.6% | -4.8% | Below both | -12.2% | Lagging |
| 22 | Energy Commodity | 26 | -0.06% | -2.7% | -7.9% | -6.9% | +2.0% | -3.3% | Below both | -13.5% | Improving |
| 23 | Oil & Gas Commodity · since 2020 | 25 | -0.45% | -2.9% | -6.6% | -7.5% | -8.2% | -2.0% | Below both | -15.2% | Improving |
| 24 | PSE Cyclical | 23 | -0.11% | -2.6% | -7.0% | -12.7% | -6.9% | -2.4% | Below both | -14.7% | Improving |
| 25 | FMCG Defensive | 21 | -0.39% | -2.1% | -8.5% | -10.2% | -20.1% | -3.9% | Below both | -21.4% | Improving |
| 26 | Consumer Durables Cyclical · since 2020 | 17 | -0.61% | -4.6% | -8.0% | -4.7% | -6.5% | -3.4% | Below both | -11.5% | Weakening |
| 27 | Commodities Commodity | 17 | +0.33% | -3.6% | -7.5% | -9.8% | -1.2% | -2.9% | Below both | -13.9% | Improving |
| 28 | CPSE Cyclical · since 2019 | 7 | -0.39% | -4.0% | -8.3% | -17.6% | -7.7% | -3.7% | Below both | -20.1% | Improving |
| Nifty 500 benchmark | — | +0.40% | -1.2% | -4.6% | -2.6% | -5.5% | — | ||||
The RS score is the average percentile rank of each sector's 1-month, 3-month and 6-month return
relative to the Nifty 500 — 100 means it topped every window, 0 means it was last in all three.
Rank-based on purpose, so one violent month can't buy a sector the top spot. Click any sector for its full
valuation and history page.
🔬 Inside the sectors — how the individual stocks are positioned
| Sector | Stocks | Within 5% of 52w high | More than 30% below | Median gap to 52w high | Up today | Closest to their highs |
|---|---|---|---|---|---|---|
| Media | 8 | 2 (25%) | 1 (12%) | -11.0% | 6/8 | TIPSMUSIC, PVRINOX, SUNTV, DELTACORP, SUNSHINE |
| IT | 53 | 6 (11%) | 17 (32%) | -21.7% | 39/53 | CYIENT, ONEPOINT, COFORGE, TECHM, 63MOONS |
| Defence | 22 | 1 (5%) | 3 (14%) | -17.9% | 14/22 | HAL, UNIMECH, APOLLO, ROSSTECH, AXISCADES |
| Pharma | 54 | 4 (7%) | 4 (7%) | -15.2% | 27/54 | LAURUSLABS, SYMBIOTEC, GLAND, AUROPHARMA, DIVISLAB |
| Bank | 30 | 4 (13%) | 3 (10%) | -15.1% | 17/30 | KOTAKBANK, SOUTHBANK, KARURVYSYA, KTKBANK, ICICIBANK |
| Chemicals | 35 | 2 (6%) | 5 (14%) | -15.5% | 16/35 | CASTROLIND, ADVANCE, PAUSHAKLTD, JGCHEM, FCL |
| Healthcare | 19 | 2 (11%) | 3 (16%) | -19.7% | 11/19 | INDGN, MOMSBELIEF, MOLBIO, LALPATHLAB, GKSL |
| Financial Services | 82 | 5 (6%) | 20 (24%) | -19.3% | 27/82 | GCSL, MOTILALOFS, TFCILTD, PNBHOUSING, ANANDRATHI |
| Metal | 59 | 4 (7%) | 11 (19%) | -18.5% | 44/59 | SAMBHV, SHYAMMETL, GOODLUCK, RATNAVEER, PTCIL |
| Infrastructure | 81 | 6 (7%) | 20 (25%) | -20.4% | 45/81 | SHREEJISPG, NAZARA, SWASTIKAIN, TECHNOCRAF, SHADOWFAX |
| Auto | 52 | 4 (8%) | 11 (21%) | -19.2% | 35/52 | WHEELS, SSWL, KROSS, SHRIPISTON, SONACOMS |
| Energy | 19 | 0 (0%) | 7 (37%) | -24.0% | 10/19 | CMLL, CLEANMAX, NHPC, ADANIGREEN, JSWENERGY |
| Oil & Gas | 28 | 1 (4%) | 7 (25%) | -17.8% | 10/28 | STEAMHOUSE, GANDHAR, DEEPINDS, MANALIPETC, RAIN |
| FMCG | 39 | 2 (5%) | 13 (33%) | -23.7% | 16/39 | ABDL, CUPID, RADICO, DALMIASUG, VINCOFE |
| Consumer Durables | 35 | 7 (20%) | 6 (17%) | -10.8% | 25/35 | SHANTIGOLD, SKYGOLD, RAMBHAJO, SHRINGARMS, DEEPA |
A sector index can be dragged up by two heavyweights while most of its constituents go nowhere. This table is the
breadth check: when a leading sector also has most of its stocks near 52-week highs, the move has participation
behind it. Stocks are grouped by their NSE industry classification, not by official index membership
(NSE does not serve constituent lists to cloud IPs), and the pool is limited to the 750 most
actively traded names so the numbers describe investable companies rather than the micro-cap tail. Counts therefore
approximate each index rather than matching it.
🔁 Month-by-month rotation — the last 13 months
| Sector | Oct 25 | Nov 25 | Dec 25 | Jan 26 | Feb 26 | Mar 26 | Apr 26 | May 26 | Jun 26 | Jul 26 | Aug 26 | Sep 26 | Oct 26 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Media | -0.3 | -4.6 | -1.6 | -4.1 | +2.2 | -10.9 | +15.4 | -3.3 | +5.0 | +9.5 | -3.8 | +1.7 | +4.1 |
| IT | +6.1 | +4.7 | +1.3 | +0.4 | -19.5 | -5.0 | +1.0 | -0.9 | -9.6 | +16.8 | +1.6 | -11.2 | +15.2 |
| Digital | +6.2 | +1.9 | +0.0 | -4.3 | -12.9 | -7.5 | +6.8 | +1.4 | -2.7 | +11.2 | +4.1 | -9.4 | +8.0 |
| Defence | +3.6 | -1.5 | -3.3 | +5.6 | -0.7 | -11.2 | +24.4 | +1.5 | +4.5 | -2.0 | +4.2 | -4.5 | -0.7 |
| Pharma | +3.4 | +3.7 | -1.2 | -4.4 | +5.7 | -3.1 | +4.7 | +4.6 | +4.0 | +4.8 | +2.5 | -2.8 | -2.5 |
| Private Bank | +6.0 | +2.6 | -0.2 | -0.6 | +0.2 | -15.6 | +8.9 | +0.2 | +6.1 | -1.5 | +1.8 | -4.7 | +3.8 |
| Services | +4.3 | +2.4 | -1.0 | -1.6 | -2.4 | -12.3 | +6.6 | -1.9 | +2.8 | +2.5 | -1.4 | -5.9 | +5.1 |
| Capital Markets | +9.3 | +5.6 | -2.6 | -0.2 | -1.0 | -7.6 | +23.2 | +4.5 | -0.5 | -2.6 | +3.4 | -7.2 | +3.0 |
| Bank | +5.7 | +3.4 | -0.3 | +0.0 | +1.5 | -16.9 | +9.1 | -1.1 | +6.1 | -0.5 | +1.3 | -5.8 | +2.2 |
| Chemicals | +2.0 | -1.3 | +0.9 | -4.2 | -0.2 | -10.2 | +14.2 | +2.7 | +1.3 | +1.6 | -0.2 | -5.5 | +0.0 |
| Healthcare | +3.9 | +2.3 | -2.6 | -5.1 | +7.0 | -4.5 | +5.1 | +3.2 | +4.9 | +3.8 | +1.1 | -4.7 | -2.8 |
| Realty | +9.2 | -4.7 | -2.8 | -10.8 | -0.3 | -16.6 | +21.9 | -1.4 | +6.0 | +8.7 | +0.3 | -6.3 | -2.5 |
| Financial Services | +4.3 | +2.8 | -1.0 | -1.0 | +2.0 | -15.6 | +9.1 | -1.2 | +4.7 | +0.1 | -1.1 | -6.3 | +3.0 |
| Transport & Logistics | +0.8 | +2.1 | -1.1 | -5.2 | +3.0 | -14.6 | +9.6 | +1.2 | +2.8 | +6.6 | +0.8 | -6.6 | -1.9 |
| Manufacturing | +3.3 | +0.3 | +0.7 | -2.3 | +4.8 | -11.0 | +10.8 | +2.2 | -0.1 | +2.9 | +1.6 | -6.8 | -1.8 |
| PSU Bank | +8.7 | +4.0 | +0.2 | +5.7 | +8.9 | -19.8 | +7.7 | -3.8 | +4.1 | -1.5 | +2.9 | -6.9 | +1.0 |
| Consumption | +2.9 | +0.5 | -1.5 | -6.7 | +0.6 | -10.4 | +10.5 | -1.4 | +2.3 | +4.9 | -2.3 | -6.2 | -0.2 |
| Metal | +5.7 | -3.0 | +8.5 | +5.9 | +3.5 | -9.0 | +15.2 | +4.7 | -6.9 | +1.6 | +3.7 | -3.3 | -4.9 |
| Infrastructure | +6.2 | +0.9 | -0.4 | -4.8 | +4.1 | -10.2 | +10.0 | -0.7 | +0.4 | +0.2 | -2.4 | -4.9 | -0.1 |
| Auto | +1.0 | +3.6 | +1.5 | -5.1 | +5.3 | -15.6 | +9.0 | +1.6 | +0.5 | +8.6 | +0.3 | -8.8 | -2.0 |
| Core Housing | +2.9 | -2.1 | -1.7 | -5.4 | +2.9 | -13.9 | +13.6 | +2.0 | +1.5 | +3.9 | -0.2 | -8.2 | -1.3 |
| Energy | +3.6 | -2.0 | -0.6 | -0.5 | +5.4 | -5.9 | +17.0 | +0.3 | -2.8 | -2.5 | -2.0 | -3.5 | -1.2 |
| Oil & Gas | +6.3 | +0.4 | +1.6 | -3.6 | +4.0 | -12.0 | +8.4 | -4.2 | -1.5 | +2.0 | -1.3 | -4.4 | -0.5 |
| PSE | +2.7 | -3.2 | +1.1 | +3.2 | +2.8 | -8.6 | +11.2 | -3.8 | -2.4 | -0.4 | -2.4 | -3.5 | -1.2 |
| FMCG | +2.7 | -1.1 | -0.2 | -7.7 | -0.1 | -11.0 | +12.2 | -3.3 | -1.2 | +0.7 | -6.3 | -3.3 | +0.2 |
| Consumer Durables | +4.0 | -1.9 | -3.0 | -6.4 | +9.3 | -12.1 | +12.9 | -6.2 | +4.3 | +10.0 | +0.9 | -9.4 | -1.0 |
| Commodities | +4.7 | -2.1 | +3.3 | +1.4 | +3.2 | -8.3 | +12.2 | +0.6 | -4.9 | +0.7 | -1.7 | -3.9 | -2.3 |
| CPSE | +2.4 | -3.8 | +0.1 | +7.0 | +4.0 | -2.6 | +8.0 | -6.0 | -4.4 | -2.5 | -2.4 | -2.3 | -2.6 |
| Nifty 500 | +4.3 | +0.9 | -0.3 | -3.3 | +0.4 | -11.4 | +10.5 | -0.1 | +1.5 | +2.0 | -0.0 | -5.9 | +0.9 |
| Best − worst spread | 10pp | 10pp | 12pp | 18pp | 29pp | 17pp | 23pp | 11pp | 16pp | 19pp | 10pp | 13pp | 20pp |
Every cell prints its own number, so the tint is a reading aid rather than the data. The last row is the
dispersion — the gap between the best and worst sector that month. Wide months are when sector
selection pays; narrow months are when it barely matters what you owned.
🧩 The rotation quilt — sectors ranked every calendar year
The classic “periodic table” view. Read it across a row and the point makes itself: leadership almost never repeats
two years running, and the sector at the bottom of one column is regularly at the top of the next. That instability is
the entire argument for rotating — and the entire risk of chasing last year's winner. The dashed row is the
Nifty 500 for reference.
🔗 Do these sectors actually diversify each other?
| Sector | MEDIA | IT | PHRM | PVTB | BANK | RLTY | FIN | PSUB | CONS | MTL | INFRA | AUTO | ENRG | PSE | FMCG | COMM |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Media | 1.00 | 0.25 | 0.54 | 0.42 | 0.44 | 0.54 | 0.43 | 0.53 | 0.55 | 0.57 | 0.57 | 0.52 | 0.56 | 0.59 | 0.32 | 0.62 |
| IT | 0.25 | 1.00 | 0.29 | 0.29 | 0.26 | 0.29 | 0.27 | 0.18 | 0.36 | 0.28 | 0.32 | 0.39 | 0.22 | 0.22 | 0.22 | 0.30 |
| Pharma | 0.54 | 0.29 | 1.00 | 0.34 | 0.35 | 0.50 | 0.38 | 0.39 | 0.60 | 0.47 | 0.57 | 0.57 | 0.52 | 0.55 | 0.41 | 0.55 |
| Private Bank | 0.42 | 0.29 | 0.34 | 1.00 | 0.97 | 0.61 | 0.95 | 0.60 | 0.64 | 0.53 | 0.69 | 0.60 | 0.54 | 0.52 | 0.38 | 0.61 |
| Bank | 0.44 | 0.26 | 0.35 | 0.97 | 1.00 | 0.65 | 0.96 | 0.72 | 0.67 | 0.57 | 0.73 | 0.62 | 0.60 | 0.58 | 0.40 | 0.66 |
| Realty | 0.54 | 0.29 | 0.50 | 0.61 | 0.65 | 1.00 | 0.66 | 0.56 | 0.69 | 0.56 | 0.72 | 0.62 | 0.64 | 0.63 | 0.40 | 0.64 |
| Financial Services | 0.43 | 0.27 | 0.38 | 0.95 | 0.96 | 0.66 | 1.00 | 0.62 | 0.71 | 0.55 | 0.74 | 0.64 | 0.58 | 0.57 | 0.43 | 0.65 |
| PSU Bank | 0.53 | 0.18 | 0.39 | 0.60 | 0.72 | 0.56 | 0.62 | 1.00 | 0.50 | 0.67 | 0.71 | 0.55 | 0.71 | 0.75 | 0.28 | 0.75 |
| Consumption | 0.55 | 0.36 | 0.60 | 0.64 | 0.67 | 0.69 | 0.71 | 0.50 | 1.00 | 0.57 | 0.81 | 0.87 | 0.63 | 0.61 | 0.73 | 0.70 |
| Metal | 0.57 | 0.28 | 0.47 | 0.53 | 0.57 | 0.56 | 0.55 | 0.67 | 0.57 | 1.00 | 0.73 | 0.64 | 0.74 | 0.77 | 0.29 | 0.90 |
| Infrastructure | 0.57 | 0.32 | 0.57 | 0.69 | 0.73 | 0.72 | 0.74 | 0.71 | 0.81 | 0.73 | 1.00 | 0.75 | 0.88 | 0.85 | 0.51 | 0.90 |
| Auto | 0.52 | 0.39 | 0.57 | 0.60 | 0.62 | 0.62 | 0.64 | 0.55 | 0.87 | 0.64 | 0.75 | 1.00 | 0.59 | 0.59 | 0.50 | 0.70 |
| Energy | 0.56 | 0.22 | 0.52 | 0.54 | 0.60 | 0.64 | 0.58 | 0.71 | 0.63 | 0.74 | 0.88 | 0.59 | 1.00 | 0.91 | 0.39 | 0.91 |
| PSE | 0.59 | 0.22 | 0.55 | 0.52 | 0.58 | 0.63 | 0.57 | 0.75 | 0.61 | 0.77 | 0.85 | 0.59 | 0.91 | 1.00 | 0.39 | 0.91 |
| FMCG | 0.32 | 0.22 | 0.41 | 0.38 | 0.40 | 0.40 | 0.43 | 0.28 | 0.73 | 0.29 | 0.51 | 0.50 | 0.39 | 0.39 | 1.00 | 0.43 |
| Commodities | 0.62 | 0.30 | 0.55 | 0.61 | 0.66 | 0.64 | 0.65 | 0.75 | 0.70 | 0.90 | 0.90 | 0.70 | 0.91 | 0.91 | 0.43 | 1.00 |
Violet = move together, amber = move apart, pale = unrelated.
The tightest pair is
Bank & Private Bank at 0.97 —
holding both is close to holding one position twice.
The loosest is IT & PSU Bank
at 0.18, the pair that genuinely spreads risk.
This is why the strategy section ranks a deduplicated sector list: Bank, Private Bank and Financial Services are three
views of the same book, and a naive “top 3” would happily buy all three.
📅 Which sectors tend to do well in Oct?
Small sample warning: our index history starts in 2019, so each monthly average rests on
at most 7–8 observations. That is enough to notice a
tendency and nowhere near enough to trade on one by itself. The n in each cell is the number of years behind
it; anything with fewer than 3 years is left blank rather than dressed up as a pattern.
| Sector | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Media | -4.243% up · n7 | -4.025% up · n8 | -5.038% up · n8 | +2.875% up · n8 | +1.750% up · n8 | +1.862% up · n8 | +3.750% up · n8 | +1.725% up · n8 | +2.938% up · n8 | -1.125% up · n8 | +1.057% up · n7 | -0.343% up · n7 |
| IT | +0.171% up · n7 | -4.725% up · n8 | -2.525% up · n8 | -0.838% up · n8 | +0.338% up · n8 | +1.662% up · n8 | +6.475% up · n8 | +2.862% up · n8 | -1.438% up · n8 | +2.962% up · n8 | +3.786% up · n7 | +4.486% up · n7 |
| Digital | -3.520% up · n5 | -5.540% up · n5 | -0.840% up · n5 | +0.880% up · n5 | +0.760% up · n5 | +2.260% up · n5 | +4.480% up · n5 | +3.280% up · n5 | -2.520% up · n5 | +1.860% up · n5 | +5.0100% up · n4 | +0.775% up · n4 |
| Defence | +1.550% up · n4 | -5.320% up · n5 | +5.780% up · n5 | +13.9100% up · n5 | +10.180% up · n5 | +5.080% up · n5 | +2.460% up · n5 | +3.060% up · n5 | +0.860% up · n5 | +0.640% up · n5 | +5.875% up · n4 | +1.025% up · n4 |
| Pharma | -2.929% up · n7 | -1.438% up · n8 | +1.762% up · n8 | +6.575% up · n8 | -0.650% up · n8 | +2.075% up · n8 | +5.588% up · n8 | +0.650% up · n8 | +0.162% up · n8 | -1.138% up · n8 | +2.857% up · n7 | +2.157% up · n7 |
| Private Bank | -2.114% up · n7 | -0.325% up · n8 | -4.362% up · n8 | +4.662% up · n8 | +0.262% up · n8 | +2.262% up · n8 | +0.138% up · n8 | +1.750% up · n8 | -0.162% up · n8 | +3.275% up · n8 | +4.686% up · n7 | +1.343% up · n7 |
| Services | -1.90% up · n7 | -1.525% up · n8 | -2.575% up · n8 | +3.075% up · n8 | +0.050% up · n8 | +2.675% up · n8 | +2.175% up · n8 | +1.450% up · n8 | -0.562% up · n8 | +2.275% up · n8 | +4.286% up · n7 | +2.057% up · n7 |
| Capital Markets | — | — | — | — | — | — | — | — | — | +7.0100% up · n3 | — | — |
| Bank | -1.729% up · n7 | +0.038% up · n8 | -4.062% up · n8 | +4.462% up · n8 | +0.450% up · n8 | +2.462% up · n8 | +0.438% up · n8 | +1.150% up · n8 | -0.362% up · n8 | +3.475% up · n8 | +4.986% up · n7 | +1.643% up · n7 |
| Healthcare | -3.517% up · n6 | -0.533% up · n6 | +2.283% up · n6 | +3.667% up · n6 | +0.050% up · n6 | +4.283% up · n6 | +5.2100% up · n6 | +0.850% up · n6 | -0.350% up · n6 | -1.333% up · n6 | +2.660% up · n5 | +1.967% up · n6 |
| Realty | -1.629% up · n7 | -2.638% up · n8 | -3.938% up · n8 | +5.062% up · n8 | +3.262% up · n8 | +4.588% up · n8 | +4.450% up · n8 | +0.138% up · n8 | +2.138% up · n8 | +1.862% up · n8 | +5.171% up · n7 | +4.557% up · n7 |
| Financial Services | -2.014% up · n7 | -0.225% up · n8 | -3.062% up · n8 | +4.175% up · n8 | +0.650% up · n8 | +2.875% up · n8 | +1.062% up · n8 | +1.350% up · n8 | -0.662% up · n8 | +3.075% up · n8 | +4.886% up · n7 | +1.443% up · n7 |
| Transport & Logistics | -0.550% up · n4 | -1.050% up · n4 | -1.940% up · n5 | +6.3100% up · n5 | +4.0100% up · n5 | +3.680% up · n5 | +5.3100% up · n5 | +1.980% up · n5 | +0.260% up · n5 | -2.140% up · n5 | +2.875% up · n4 | -0.125% up · n4 |
| Manufacturing | -0.740% up · n5 | -1.340% up · n5 | +1.080% up · n5 | +5.2100% up · n5 | +2.380% up · n5 | +2.160% up · n5 | +3.980% up · n5 | +1.380% up · n5 | +0.167% up · n6 | -1.350% up · n6 | +1.260% up · n5 | +1.360% up · n5 |
| PSU Bank | +2.857% up · n7 | -0.638% up · n8 | -3.162% up · n8 | +2.675% up · n8 | -0.138% up · n8 | +4.162% up · n8 | +0.338% up · n8 | -0.838% up · n8 | +0.238% up · n8 | +5.062% up · n8 | +6.386% up · n7 | +3.357% up · n7 |
| Consumption | -1.729% up · n7 | -2.025% up · n8 | -1.375% up · n8 | +4.475% up · n8 | +1.562% up · n8 | +2.375% up · n8 | +2.775% up · n8 | +2.775% up · n8 | +1.362% up · n8 | -0.750% up · n8 | +1.643% up · n7 | +1.343% up · n7 |
| Metal | -2.214% up · n7 | +0.038% up · n8 | -0.075% up · n8 | +8.275% up · n8 | +0.675% up · n8 | +0.075% up · n8 | +3.662% up · n8 | +0.938% up · n8 | +1.550% up · n8 | -0.650% up · n8 | +5.357% up · n7 | +6.386% up · n7 |
| Infrastructure | +0.143% up · n7 | -0.638% up · n8 | -0.462% up · n8 | +4.675% up · n8 | +2.175% up · n8 | +2.388% up · n8 | +1.375% up · n8 | +0.138% up · n8 | +1.462% up · n8 | +0.962% up · n8 | +2.871% up · n7 | +1.229% up · n7 |
| Auto | +2.271% up · n7 | -2.550% up · n8 | -6.025% up · n8 | +6.888% up · n8 | +4.388% up · n8 | +3.088% up · n8 | +1.762% up · n8 | +2.462% up · n8 | +1.775% up · n8 | +0.950% up · n8 | +2.343% up · n7 | +1.371% up · n7 |
| Core Housing | -4.10% up · n3 | -1.967% up · n3 | -1.933% up · n3 | +7.5100% up · n3 | +2.475% up · n4 | +5.2100% up · n4 | +2.175% up · n4 | -0.325% up · n4 | -1.150% up · n4 | -2.225% up · n4 | +1.833% up · n3 | +2.767% up · n3 |
| Energy | -0.529% up · n7 | -0.450% up · n8 | +1.062% up · n8 | +6.888% up · n8 | +0.662% up · n8 | +1.450% up · n8 | +0.550% up · n8 | +0.638% up · n8 | +1.962% up · n8 | +0.250% up · n8 | +1.543% up · n7 | +0.529% up · n7 |
| Oil & Gas | +0.133% up · n6 | -1.043% up · n7 | -1.543% up · n7 | +7.3100% up · n7 | -0.129% up · n7 | +1.957% up · n7 | +2.871% up · n7 | +1.157% up · n7 | -0.643% up · n7 | -1.229% up · n7 | +3.467% up · n6 | +2.350% up · n6 |
| PSE | +1.557% up · n7 | -0.250% up · n8 | +0.250% up · n8 | +5.488% up · n8 | +1.862% up · n8 | +1.175% up · n8 | +0.738% up · n8 | -0.738% up · n8 | +1.650% up · n8 | +0.350% up · n8 | +2.843% up · n7 | +2.357% up · n7 |
| FMCG | -2.129% up · n7 | -2.812% up · n8 | +0.462% up · n8 | +3.688% up · n8 | +1.050% up · n8 | +0.850% up · n8 | +3.375% up · n8 | +0.762% up · n8 | +0.862% up · n8 | -1.338% up · n8 | +0.643% up · n7 | +1.143% up · n7 |
| Consumer Durables | -4.133% up · n6 | +0.957% up · n7 | -4.757% up · n7 | +4.686% up · n7 | -1.257% up · n7 | +3.486% up · n7 | +5.186% up · n7 | +3.8100% up · n7 | +1.157% up · n7 | -0.943% up · n7 | +2.867% up · n6 | +2.967% up · n6 |
| Commodities | -0.443% up · n7 | +0.150% up · n8 | +0.575% up · n8 | +6.2100% up · n8 | +0.375% up · n8 | +0.362% up · n8 | +2.475% up · n8 | -0.138% up · n8 | +1.762% up · n8 | +0.262% up · n8 | +2.057% up · n7 | +2.571% up · n7 |
| CPSE | +1.971% up · n7 | +1.362% up · n8 | +1.050% up · n8 | +5.0100% up · n8 | +1.562% up · n8 | +1.275% up · n8 | -0.338% up · n8 | -0.425% up · n8 | +2.150% up · n8 | +0.038% up · n8 | +2.143% up · n7 | +2.057% up · n7 |
The outlined column is the current month. Each cell shows the average return, the share of years that month was
positive, and how many years are behind it. For a much deeper, walk-forward-tested treatment of seasonality at the
stock level, see Stock Seasonality.
🌤️ Best Oct record
- PSU Bank — average +5.0%, up in 62% of 8 years
- Bank — average +3.4%, up in 75% of 8 years
- Private Bank — average +3.2%, up in 75% of 8 years
- Financial Services — average +3.0%, up in 75% of 8 years
- IT — average +2.9%, up in 62% of 8 years
🌧️ Weakest Oct record
- Transport & Logistics — average -2.1%, up in 40% of 5 years
- FMCG — average -1.3%, up in 38% of 8 years
- Manufacturing — average -1.3%, up in 50% of 6 years
- Healthcare — average -1.3%, up in 33% of 6 years
- Oil & Gas — average -1.2%, up in 29% of 7 years
🧪 Does rotating actually beat just holding the index?
The rule tested is deliberately dull: every month end, rank the 11 deduplicated NSE sector indices by their trailing 3-month return, hold the top 4 equally weighted, and repeat. The headline version also refuses to hold any sector trading below its own 200-day average, parking that share in cash instead. Nothing is optimised per sector, and the full lookback × count grid is published below so you can see the result is a plateau rather than one lucky cell.
| Approach | CAGR | Total return | Worst drawdown | Volatility | Months beating the index |
|---|---|---|---|---|---|
| Balanced rotation headline Top 4 sectors by 3-month return, but only while each one is above its own 200-day average — anything failing that test sits in cash. | +14.5% | +176% | -22.4% | 16.8% | 51/90 (57%) |
| Pure momentum Top 4 sectors by 3-month return, always fully invested — no trend filter, so it rides every drawdown the market has. | +18.8% | +261% | -37.3% | 19.5% | 55/90 (61%) |
| Single hottest sector Everything in the one strongest sector each month. Included to show what concentration actually costs. | +13.4% | +155% | -51.1% | 26.1% | 44/90 (49%) |
| Nifty 500 buy & hold The thing any of this has to beat. | +11.8% | +130% | -38.3% | 17.2% | — |
Index levels are price indices, so every number here — the strategy and the benchmark alike — excludes dividends
(roughly 1.2% a year for the broad market). Taxes, slippage and the impact of trading whole sector baskets are not
modelled.
📈 Growth of ₹1 — Balanced rotation vs Nifty 500
Both lines start at 1.00 on 30 Apr 2019 — the first month end with enough history for the
3-month ranking, so neither side gets a free head start. The year-by-year table below is the same
data without the smoothing that a long equity curve inevitably applies to a bad year.
📆 Year by year
| Year | Balanced rotation | Nifty 500 | Difference |
|---|---|---|---|
| 2019 | -1.4% | +2.2% | -3.6pp |
| 2020 | +11.3% | +16.7% | -5.4pp |
| 2021 | +42.0% | +30.2% | +11.8pp |
| 2022 | +12.2% | +3.0% | +9.2pp |
| 2023 | +32.1% | +25.8% | +6.3pp |
| 2024 | +32.0% | +15.2% | +16.9pp |
| 2025 | +1.3% | +6.7% | -5.4pp |
| 2026 YTD | -10.8% | -6.7% | -4.1pp |
💸 What costs do to it
| Cost per unit traded | Strategy CAGR | vs benchmark |
|---|---|---|
| 0.00% | +16.2% | +4.3pp |
| 0.20% (used above) | +14.5% | +2.7pp |
| 0.50% | +12.2% | +0.3pp |
| 1.00% | +8.3% | -3.5pp |
Monthly rebalancing turns the portfolio over often. This column is the difference between a strategy and a
spreadsheet — at a full 1% per unit traded most of the advantage is gone.
🔬 Robustness grid — CAGR (and worst drawdown) for every setting
Pure relative momentum
| Ranking lookback | Top 1 | Top 2 | Top 3 | Top 4 | Top 5 |
|---|---|---|---|---|---|
| 1-month return | -0.1%DD -66% | 1.5%DD -54% | 7.0%DD -49% | 10.2%DD -44% | 10.0%DD -43% |
| 2-month return | -0.6%DD -43% | 11.9%DD -40% | 10.1%DD -39% | 11.4%DD -39% | 11.0%DD -43% |
| 3-month return | 13.4%DD -51% | 15.2%DD -46% | 18.2%DD -43% | 18.8%DD -37% | 15.1%DD -40% |
| 6-month return | 17.6%DD -48% | 9.7%DD -50% | 14.0%DD -43% | 12.9%DD -41% | 12.7%DD -40% |
| 12-month return | 11.5%DD -49% | 10.1%DD -46% | 8.7%DD -43% | 14.6%DD -39% | 17.1%DD -38% |
With the 200-DMA filter
| Ranking lookback | Top 1 | Top 2 | Top 3 | Top 4 | Top 5 |
|---|---|---|---|---|---|
| 1-month return | -1.0%DD -55% | 6.2%DD -34% | 8.8%DD -29% | 10.1%DD -27% | 8.9%DD -24% |
| 2-month return | -2.8%DD -59% | 6.1%DD -40% | 6.3%DD -39% | 6.9%DD -30% | 8.5%DD -23% |
| 3-month return | 9.0%DD -55% | 12.4%DD -33% | 14.4%DD -26% | 14.5%DD -22% | 11.9%DD -24% |
| 6-month return | 10.8%DD -49% | 7.9%DD -34% | 10.1%DD -29% | 8.6%DD -23% | 10.1%DD -22% |
| 12-month return | 13.1%DD -49% | 10.9%DD -30% | 8.5%DD -33% | 12.1%DD -23% | 12.6%DD -24% |
This is the honesty check. A real effect shows up as a region of the grid that works, not a single cell:
the 3-month lookback beats the index at almost every portfolio size, while the 1-month version gets whipsawed and the
12-month version reacts too late. Any strategy whose edge lives in exactly one cell has been fitted to the past.
Notice too what the 200-DMA filter does — it gives up some return and takes a large bite out of the drawdown.
📌 What the rule says today
All 4 slots are filled. Sectors are shown in ranking order; the ones below the cut are included so you can
see what is next in line.
🧾 The last 12 rebalances, exactly as the rule called them
| Rebalanced | Held | Strategy | Nifty 500 | Difference |
|---|---|---|---|---|
| 30 Sep 2026 | Pharma, Media, Metal, Realty | -1.5% | +0.9% | -2.4pp |
| 31 Aug 2026 | Realty, Pharma, Auto, Media | -4.1% | -5.9% | +1.8pp |
| 31 Jul 2026 | Pharma, Realty, Media, Auto | -0.1% | -0.0% | -0.1pp |
| 30 Jun 2026 | Media, Pharma, Energy, Metal | +3.3% | +2.0% | +1.3pp |
| 29 May 2026 | Metal, Energy, Pharma, Infrastructure | -1.3% | +1.5% | -2.8pp |
| 30 Apr 2026 | Energy, Metal, Pharma, Infrastructure | +2.2% | -0.1% | +2.4pp |
| 30 Mar 2026 | Metal | +3.6% | +10.5% | -6.9pp |
| 27 Feb 2026 | Metal, PSU Bank, Energy, Auto | -12.7% | -11.4% | -1.3pp |
| 30 Jan 2026 | PSU Bank, Metal, IT, Bank | -1.9% | +0.4% | -2.3pp |
| 31 Dec 2025 | PSU Bank, Metal, IT, Bank | +3.1% | -3.3% | +6.4pp |
| 28 Nov 2025 | PSU Bank, Metal, Bank, Auto | +2.5% | -0.3% | +2.7pp |
| 31 Oct 2025 | PSU Bank, Auto, Metal, Infrastructure | +1.4% | +0.9% | +0.4pp |
Universe: Auto, Bank, FMCG, IT, Media, Metal, Pharma, PSU Bank, Realty, Energy, Infrastructure.
Deliberately deduplicated — the correlation matrix under rotation history shows why Bank, Private Bank and Financial
Services cannot all count as separate bets.
🧭 The business-cycle map
🌱 Early cycle
Recovery begins, rates still low, credit reopens.
Rate-sensitives and consumer discretionary tend to move first, because cheap money and pent-up demand hit them before earnings recover.
☀️ Mid cycle
Growth broadens, capex and credit demand pick up.
The longest phase. Leadership is widest here, which is exactly when momentum-based rotation works best.
🍂 Late cycle
Capacity tightens, inflation and rates rise.
Pricing power moves to whoever owns the scarce input, so commodity and energy sectors take over just as the broad market gets choppy.
❄️ Contraction
Demand slows, earnings estimates get cut.
Defensives lose the least. They rarely top the leaderboard outright — they get there by everything else falling faster.
This is the textbook map, and it is worth knowing precisely so you notice when the market ignores it — which it
frequently does. Indian cycles are also driven by things the US-derived textbook version never modelled: monsoons,
government capex, PSU policy and global commodity prices. Use the live RRG and leaderboard for what
is happening; use this map for why it might be.
🪜 How to actually use this page
- Start with the market phase, not the sectors. If most sectors are below their 200-day averages, the best-ranked sector is often just the one falling slowest. Rotation is a way to choose what to own, never a reason to be fully invested.
- Read the RRG for direction. Sectors moving toward the top-right are gaining leadership; ones curling down out of Leading are giving it back. Direction of travel beats current position.
- Confirm with the leaderboard. A sector worth acting on usually clears three tests at once: a high RS score, a price above both its 50- and 200-day averages, and a small gap to its 52-week high.
- Check the breadth. The “inside the sectors” table shows whether the index move has its stocks behind it or is two heavyweights dragging an otherwise flat sector along.
- Respect the correlations. Three financial indices are one bet in three costumes. Spread across the genuinely uncorrelated pairs shown under rotation history.
- Size for the drawdown, not the CAGR. Even the filtered strategy on this page sat through a 22% decline. Any rotation approach will spend long stretches behind a simple index fund — the year-by-year table shows exactly which ones.
📐 Method & data
Data. Daily closing levels for 28 NSE sector and thematic indices plus the Nifty 500, from NSE's official published index data — a live snapshot twice each trading day (~11:15 and ~17:15 IST) and NSE's end-of-day archives, stored daily since 2019. These are price indices: dividends are excluded from every series, benchmark included.
Returns and trend. Window returns are close-to-close over calendar spans (1M ≈ 30 days, 3M ≈ 91 and so on), matched to the nearest earlier session and left blank when the nearest session is too far off to be honest about. Moving averages are simple averages of the last 50 and 200 sessions.
RS score. For each of the 1-, 3- and 6-month windows we subtract the Nifty 500's return, rank every sector on the result, and average the three percentile ranks. Ranks rather than raw numbers, so a single outlier month cannot buy the top spot.
RRG. On weekly bars, relative strength is sector ÷ benchmark × 100. RS-Ratio is that series expressed as a z-score against its own trailing 26 weeks, smoothed over 4 weeks, and recentred on 100. RS-Momentum applies the identical treatment to the 4-week change in RS-Ratio. This follows the published construction of the JdK indicators — the original coefficients are proprietary, so read these as a consistent internal scale rather than numbers comparable with a vendor terminal.
Backtest. Monthly rebalancing at the last session of each month, equal weights, costs of 0.20% charged on the portion of the portfolio actually traded. The strategy and the benchmark both start at the first month end with enough history for the ranking window. There is no per-sector tuning and no look-ahead: every ranking uses only data available at that month end.
What is not modelled. Dividends, taxes, bid-ask spreads, the tracking error of whatever instrument you would actually use to buy a sector, and the fact that several of these indices have no liquid ETF at all. Treat the backtest as evidence that a tendency exists, not as an achievable return.
❓ Sector rotation — FAQ
What is sector rotation?
Sector rotation is the tendency for money to move between industry groups as the economy and market cycle turn — rate-sensitives and consumer discretionary early in a recovery, capital goods and IT through the middle, commodities and energy late, defensives such as FMCG and pharma when growth slows. Rotation strategies try to hold whichever sectors are currently attracting that money instead of owning the whole market equally.
How do I read the Relative Rotation Graph (RRG)?
The horizontal axis is relative strength versus the Nifty 500 and the vertical axis is the momentum of that relative strength; both are centred on 100. Sectors travel clockwise: Improving (bottom-left, turning up) → Leading (top-right, outperforming with momentum) → Weakening (bottom-right, still ahead but fading) → Lagging (bottom-left). The tail shows the last 10 weeks, so direction matters as much as position — a sector heading toward the top-right is more interesting than one already deep inside Leading and turning.
Which sector is performing best right now?
Over the last three months Media is the strongest NSE sector at +8.3% versus -4.6% for the Nifty 500, and it ranks first on our blended 1M/3M/6M relative-strength score. The full leaderboard above updates after every price refresh.
Does sector-rotation momentum actually work in India?
On our data it does, modestly and unevenly. Holding the top 4 of 11 NSE sector indices by three-month return, rebalanced monthly and only while each is above its 200-day average, compounded at 14.5% a year since 2019 against 11.8% for the Nifty 500, with a worst drawdown of 22% versus 38%. It beat the index in only 51 of 90 months — the edge comes from a handful of strong trending years, not from steady monthly wins, and it lagged badly in 2020's V-shaped reversal. Costs matter: at 1% per rebalance the edge largely disappears.
How often does this page update?
Twice on every trading day, after the ~11:15 and ~17:15 IST index data refreshes. Index levels come from NSE's official published index data, archived daily since 2019.
Is this investment advice?
No. This is auto-generated market research built from public NSE index data. Sector momentum reverses without warning, backtests ignore slippage and taxes, and past rotation patterns do not predict future ones. Consult a SEBI-registered adviser before investing.
Disclaimer: this page is auto-generated market research built from public NSE index data, not investment advice or a recommendation to buy or sell anything. Sector leadership reverses without warning, and every backtest here is a historical simulation that ignores slippage, taxes and the practical difficulty of buying a sector. Do your own research and consult a SEBI-registered adviser before investing.
