Sector Cycle Analyzer — India MF 20 Years

View: Same data — two lenses. Returns shows alpha vs Nifty, Rank shows where each sector finished each year.

Sector Performance vs Nifty 50 (annual returns)

Severely under (-20%+ vs Nifty) Under (-10 to -20%) Mild under (-2 to -10%) Roughly in-line Beat Nifty (+2 to +10%) Strong beat (+10 to +25%) Explosive (+25%+ vs Nifty)

Sector Rotation — Year-by-Year Rank (1 = top performer)

Top 10% — leader Top 25% Top 40% Mid pack Bottom 40% Bottom 25% Bottom 10% — laggard (often the contra buy)

Numbers show that year's rank among all sectors. Reading down a column shows that year's winners and losers; reading across a row shows how a sector cycled. Sectors that print mostly red rotate into green within 1-3 years historically — that's the contra setup.

Cycle Summary & Current Status

🎯 Auto-Selected Contra Picks

Sectors ranked by Contra Score (verdict + dry streak + drawdown + cumulative underperformance, with bonus for early 3M turning signals). For each, the 2 deepest-underperformer funds — the highest mean-reversion potential if the sector cycles back.

Reading the Score

75+ Multiple deep signals all aligned (rare, prime contra)

45 – 75 Strong contra setup, classic mean-reversion candidate

25 – 45 Cooling / mild dry — watchlist

< 25 Not shown — not contra-worthy

Max theoretical ~143 • Threshold to appear = 25

Saves the current top 5 sector picks at today's NAV with auto-generated thesis. Skips picks saved in last 25 days.

💎 Contra Pick Funds — All Equity (Diversified + Sector)

Funds that were top quartile in the past but have slipped to bottom quartile recently — classic mean-reversion candidates. Style temporarily out of favor, manager skill still intact.

Screening filters (all must pass): Regular plan, Growth option · Fund age ≥ 5 years · Currently lagging category/theme 3Y average · Was top quartile in at least 1 calendar year over last 5 years.
Score factors: drawdown depth, lag vs category, 3M turning, AMC quality, was-king count. Threshold = 25.

Saves the current top 5 fund picks at today's NAV. Skips picks saved in last 25 days.

🚪 Exit Watch — Sectors at Top of Cycle

Sectors that have already run — long winning streaks, deep cumulative outperformance, hot momentum. These are exit / book-profit candidates. Historical analogs of similar tops show what happened next (often: -10% to -25% interim drawdown before sideways).

💰 Sector Valuation Overlay — Cheap vs Expensive

Enter current P/E for each Nifty sector index and its 5-year historical average. The tool computes Z-score (how far current P/E is from history in standard deviations) and flags cheap (Z < -1) vs expensive (Z > +1) sectors. Combine with contra signals = high-conviction entry.

📊 About sector data sources in this tool:

PURE INDEX (e.g., Bank BeES) — sector ETF with ≥7 years of clean NAV history. Reflects the actual Nifty sector index. Best signal.
FUND PROXY (e.g., ICICI Prudential Technology Fund) — active sector fund used because index ETF data is unreliable. Some manager bias in returns but trends are directionally correct.

Why not direct NSE index data? Browser CORS restrictions block direct fetches from Yahoo Finance / NSE APIs. To use pure index data, you'd need either (a) a backend service that pre-fetches and writes JSON to disk, or (b) manual periodic copy-paste. This tool uses option (c) — fund-proxy with long clean history — which is the most reliable for a self-contained HTML file.

Where to fetch current P/E values:

NiftyIndices.com → click any sectoral index → P/E shown on landing page
Trendlyne → search "Nifty IT", "Nifty Bank" etc. for current + historical avg
Screener.in → sectoral aggregates

Update frequency: Monthly is sufficient. Sector P/E doesn't change much day-to-day.

How Z-score is computed: Z = (Current P/E − 5Y Avg P/E) ÷ 5Y StdDev. Approximation when only avg given (assumes 15% of avg as StdDev). Cheap zone: Z ≤ -1.0 (sector trading 1+ standard deviation below its 5Y average). Expensive zone: Z ≥ +1.0. Fair: -1 to +1. Combine Z < -1 with 🟢 STRONG ENTRY from Sector Contra = highest-conviction entry signal.

👥 Client Portfolio Advisor — Personalized Per-Client Recommendations

Paste a client's mutual fund holdings → tool computes allocation, flags data observations from our research backtest, and generates a client-ready WhatsApp message framed as factual data (MFD-compliant), not as buy/sell advice.

⚠ MFD Compliance Note: As an AMFI-registered MFD (ARN-90735), this tool produces factual data observations from sector backtest research, NOT personalised investment advice (which requires SEBI-RIA registration). The on-screen "Data Observations" and the generated WhatsApp message are framed accordingly. Always review before sending; remove anything that crosses into advice. When in doubt, consult your compliance professional.

Paste format: One fund per line. Each line: Fund Name | Current Value separated by pipe OR tab OR multiple spaces. Example:

ICICI Prudential Technology Fund | 250000
HDFC Mid Cap Opportunities | 180000
Nippon India Pharma Fund | 120000

Client Name (optional):

📣 Monthly WhatsApp Broadcast — Auto-Generated Market Commentary

One-click generation of a SEBI-compliant market data update based on current Sector Cycle research. Framed as factual data observations (allowed for MFDs), NOT as buy/sell recommendations (which require an RIA license). Send to all clients on the 1st of every month.

⚠ MFD Compliance Note: As an AMFI-registered Mutual Fund Distributor (ARN), you cannot give personalised buy/sell recommendations — that requires SEBI-RIA registration. This composer is designed to share factual market data and educational observations only. Review the generated text and remove anything that sounds like a directive before sending. When in doubt, consult your compliance professional.

Commentary structure: Greeting → Market overview (Nifty + sector leadership) → 2-3 Contra opportunities (sectors only, no scheme names) → 1-2 Exit watch sectors → Educational close + SEBI disclaimer. Total ~180-220 words. You can edit before sending.

📰 Monthly Newsletter — World News + Market Data

Compose a SEBI-safe monthly news digest — Indian + Global headlines, market data, and economic indicators. No sector recommendations, no scheme names, no advisory content. Pure news + general market data, formatted for email or WhatsApp.

⚠ MFD Framing: Newsletter content stays in information / education / news commentary territory which is permitted for MFDs. Avoid adding "you should buy X" or "we recommend Y" language. Just curate facts; let the data speak.

Newsletter Month:

Newsletter Title:

📊 Market Recap (auto-filled — editable)

🇮🇳 Indian Headlines (paste 3-5 major stories)

Sources: Economic Times, Moneycontrol, Business Standard, Mint. Format: one headline per line, brief context after dash.

🌍 World Headlines (paste 3-5 stories)

Sources: Reuters, BBC, Bloomberg, FT. Cover US Fed, geopolitics, oil, commodities, big tech.

📉 Economic Data (rates, inflation, currency, commodities)

Optional but adds depth. Format: Indicator — Current — Change.

📝 Closing Note (optional personal touch)

Workflow: 1) Fill Month + Title. 2) Click Auto-Fill for market data. 3) Spend 10 min pasting key headlines from your news sources. 4) Click Preview to review. 5) Download as HTML for email OR Copy as Text for WhatsApp. Newsletter auto-saves as you type.

🏆 Best in Class — Category-by-Category Fund Selector

For each MF category, ranks every fund in our universe by a composite backtest score: persistence (past top-quartile years), current valuation (top vs bottom quartile now), AUM sweet spot, low TER, and historical down-capture. The top 3-5 per category are your data-driven shortlists.

⚠ MFD Compliance Note: Output here is factual data ranking from our research backtest. As an MFD (ARN-90735) you can share these as "data observations" but cannot present as buy recommendations. The list is a SHORTLIST aid — for client-specific recommendations, refer them to a SEBI-registered Investment Advisor.

Scoring methodology (max 100):

Persistence (0-30): Top quartile years in last 5 calendar years × 6
AUM Sweet Spot (0-15): Small Cap <15K Cr, Mid <30K Cr, Large/Flexi <50K Cr — full points; double = penalised
TER Penalty (0-15): Lower TER than category median = full points
Down-Capture (0-15): How well it held up in worst calendar year — lower loss than category = better
Style Purity (0-10): Matches mandate (no drift)
Current Quartile (0-10): Bonus if currently bottom quartile (mean-reversion entry) AND top historically (fallen star)
Fund Age & Track (0-5): 5+ years of history
Recent Penalty (0 to -15): Bottom 20% of category in last year → -15. Catches funds like Quant during SEBI investigation period
Manual Watchout (-30): You flag funds with known issues (SEBI/manager/compliance) — click "⚠ Add watchout" on any row. Flagged funds drop to bottom with 🚫 badge

Category: Top picks:

⏱ SIP Tenure Optimizer — Backtest-Driven SIP Plans

For each current contra pick, this gives a specific SIP tenure recommendation based on historical analog data. Unlike "SIP forever," each plan has a defined endpoint, expected outcome range, and exit signal. This is your 10x differentiator — no other distributor gives clients this level of specificity.

⚠ MFD Compliance Note: Output here uses backtest data observations, framed as factual research output, not personal recommendations. As an MFD (ARN-90735) you can share these as data-driven SIP scenarios. For client-specific recommendations, refer them to a SEBI-registered Investment Advisor.

📋 DR Brokers Track Record — Every Pick We've Saved

Every Contra Pick saved is logged here with date, NAV at save, contra score, and live forward performance. Auto-save runs on the 1st open of every month (top 3 sectors + top 3 funds). You can also manually click "🤖 Auto-Save Top 5" on the Sector Contra or Contra Funds tabs. This is your firm's accountability page — clients can see real calls and real outcomes.

📸 Monthly Research Archive — DR Brokers Conviction Log

Auto-saved snapshot of the full Sector Cycle analysis on the last day of every month. Each entry locks in what your firm thought at that point in time — Contra picks, Heat Map verdict, drawdowns. Look back 6/12 months later to see what played out. This is proof your firm's calls weren't hindsight.

How it works: When you open this page on the LAST DAY of any calendar month and no snapshot for that month exists yet, the tool automatically captures a snapshot — Sector Contra ranking, Contra Funds top 15, current heat map verdicts. The snapshot is stored in browser AND a JSON file downloaded to your computer (for backup / sharing).

📈 Backtest Proof — Every Historical Dry Streak & What Happened Next

Every dry streak detected in the past, along with the actual 1Y / 2Y / 3Y forward returns when the streak ended. Hit = sector beat Nifty 50 in the year after. The aggregate hit rate is the proof: "after a dry streak, sectors historically bounced X% of the time."

📖 Entry/Exit Playbook — Backtest-Derived Rules

Every closed dry streak bucketed by length \u00d7 drawdown depth. Shows which setups actually mean-reverted in the past — these are the rules we should hunt for in current sectors.

🏆 Per-Sector Win/Loss Track Record

Which sectors reliably bounce back after dry streaks vs which just stay weak. Tells you which sectors deserve contra bets and which ones are traps.

📋 All Historical Dry Streaks (raw data)

Methodology: A dry streak = 2+ consecutive years a sector lagged Nifty 50 by >2%. At the year the streak ends, we record the sector's actual return for the next 1, 2, and 3 calendar years. "Hit" = forward 1Y exceeded Nifty 50's 1Y by >2% (beat the benchmark, not just positive return). For sectors with index-ETF rep (INDEX badge in heat map), this measures pure sector cycle. For sectors using active fund proxy, fund alpha is in the noise.

🤖 Automated Contra Portfolio — Auto-Built From Live Data

Two ready model portfolios (₹2L & ₹5L monthly SIP) assembled automatically from the current sector-cycle verdicts and the fallen-star contra-fund screen. Diversified sleeves are filled with funds that were top-quartile and are temporarily lagging; sector sleeves use the coldest "Due/Dry" sectors (hot sectors are excluded). It rebuilds every time the data refreshes — pull is daily.

As of: — • Auto-rebuilds daily on first open after the NAV cache refreshes. • Regular Growth plans.

Client asked "why this sector?" — explain any sector's full dry history

⚠ MFD note: Auto-generated factual model allocations from backtest research — not personalised buy/sell advice (that needs SEBI-RIA). Review before sharing. Contra picks can stay cold 1–3 years; size for a 5–7yr horizon. ₹2L book = moderate tilt, ₹5L book = aggressive (heavier small-cap + 2 sector satellites).