One grid, same basis, every bank. Log each result as it drops; valuation columns and charts update automatically. Click a company for its detail page with quarterly trends. Entries save in this browser.
Scorecard
Standalone figures unless noted. The columns follow the ROA Pyramid: NIM, cost-to-income and credit cost drive ROA; ROA × leverage = ROE. The strip under each reported bank is its automatic diagnosis — flags encoding the buy-side heuristics (provision-flattered PAT, write-backs, the 1% ROA / 15% ROE / 70% PCR bars, outlier growth, capital-raise risk) plus your notes; ▾ collapses it. Flags are prompts for the concall, not verdicts. Click a column header to sort. Hover a row, then Edit to update after a bank reports.
Company
Status
PAT ₹cr
PAT YoY
PPOP YoY
NII YoY
NIM
C/I
ROA
ROE
Adv YoY
Dep YoY
GNPA
NNPA
PCR
Credit cost
CET1
P/B
P/E
Valuation vs quality
The anchor question for financials: what return on book are you buying, and at what multiple of book? Up-and-left is expensive for what it earns; down-and-right is cheap for what it earns.
P/B vs ROE
Reported banks · dotted lines mark the group medians
Return on assets
Annualised, Q1FY27 · the cleanest profitability measure for a bank
Segment lens
Where each lender's growth actually comes from — segment YoY growth normalised into common buckets (definitions differ by bank; hover a cell for the share of book and caveats). The first column is the company's total book growth, the reference point. An amber ring marks a segment growing 15+ points faster than the company's own book — the framework's outlier tell, i.e. the FY28 lag-test list. Segments are extracted from filings and update when new results are processed, not via the form.
Capital markets & wealth
Fee businesses riding the same market cycle as the lenders above, but with a different chassis — no NIM, no credit cost; the questions are AUM vs net flows (how much growth is client money vs MTM), revenue yield and its durability, upfront vs trail accounting, and regulatory exposure. P/E on trailing reported PAT.
Company
Model
Period
Revenue ₹cr
Rev YoY
PAT ₹cr
PAT YoY
Key metric
Mkt cap ₹cr
P/E (TTM)
Log a result
Pick a company (or add a new one), enter the numbers from its press release, and save. Percentages are entered as plain numbers — 4.53 means 4.53%.
How to read a bank quarter
The framework, upgraded with the methodology from the First Principles Investing posts (Rahul Rao). Rank on quality first, price second.
The ROA Pyramid — the chassis for every lender
Walk the P&L top-down: NII → NIM ("the gross margin for banks") → minus opex → PPOP (cost-to-income = opex ÷ operating income) → minus provisions (credit cost) → PAT → ROA = PAT ÷ total assets. Then ROE = ROA × leverage.
Bars: ROA ≥ 1% and ROE ≥ 15% minimum for "doing pretty good"; anything under 1% ROA has the potential of being bad to ugly. PCR ~70% is the comfort bar. C/I judged vs best peers (~45–50%).
A business is a movie reel, not a photograph: what matters is which pyramid line moves next quarter, not the level today. The 5%→15% ROE journey creates the biggest stock-price delta — and the P/B re-rating starts before the fundamentals finish printing.
NIM forensics: there's no standard formula — check the denominator (total assets vs interest-earning assets only). For rate-cycle comparisons prefer the interest spread (loan yields − cost of funds); NIM embeds leverage and ALM mismatch. With ~83% of private-bank floating loans repo-linked, rate cuts hit spreads for a few quarters (assets reprice faster than fixed deposits), then wash out.
Quality of earnings — where did the growth actually come from?
PAT YoY vs PPOP YoY is the first check (the tracker computes it). PAT +28% on PPOP +9% means the growth is provision write-backs — the PNB Housing "mirage": NII +9%, fee income padded by a new one-off line, and negative credit cost doing the rest. Ask on the concall: how much recovery pool is left?
Strip one-offs before believing any growth number: treasury/forex income, divestment gains, security-receipt recoveries, new fee lines. Rebuild PAT without them — South Indian Bank's "+197% PAT" was a ~32% decline ex-treasury.
Only booked provisions are provisions. "Imputed" buffers, expected recoveries from written-off pools, and litigation outcomes are hopes, not coverage. Internal-consistency test: GNPA − provisions should ≈ NNPA; if the three don't reconcile, something is being framed.
Redo the math in investor presentations — claims like "97% of new book is A+ rated" often apply to a sub-segment, not the book. Companies choose their most flattering basis (YoY vs QoQ, average vs period-end); this grid exists to neutralise that.
Red flags — the forensic checklist
Growth far above peers is a risk tell, not a virtue. IIFL's gold book grew 7–13% QoQ while peers did 0–6% — that outlier growth is what drew the RBI ban. "Fastest-growing lender" is a confession, not a boast. For fast growers, current GNPA is meaningless — look at lagged 1-yr/2-yr NPAs and 30+/90+ dpd early-mortality on recent vintages.
The dilution-price test: a capital raise priced near or below ~1× book is a desperation signal (IDFC First at 1.2×, South Indian Bank at 0.8×). You can predict raises before they're announced: capital ÷ (RWA grown at guided pace) → if forward CET1 sinks below peers, the raise is arithmetically inevitable.
Trust-factor aggregation: tally incidents across the whole group and all regulators over the trailing year, not just the listed entity. Small amounts of shady behaviour are fully diagnostic. Watch smart-money exits and their timing vs bad news (Fairfax sold IIFL the day after the AIF story).
Disclosure behaviour is data: no long-term history tables, missing segment-wise NPAs on a big slice of the book, or management steering attention to its cleanest sub-book — "when you don't have much to brag, you probably don't."
Lending DNA rarely changes: few lenders blow up in one cycle and post top-quartile NPAs the next. A promoter exit with the old operating management still in place is not a transformation.
Slippages lead, NPAs lag: delinquency buckets lead NPAs by 2–3 quarters; GNPA can "improve" through write-offs while the book deteriorates.
Valuation — P/B vs ROE, and the screen
P/B must be explained by asset quality, profitability and growth — a discount is only an opportunity once you know which of the three causes it. P/B < 1 for a lender means the market doubts the book value or expects no growth.
The turnaround screen (shaded zone on the chart): P/B ~1 + ROE 12–15% trending up + improving GNPA + improving disbursements. The ROE delta, not its level, is the alpha predictor.
Beware "cheapest in the sector" at a cycle peak — DHFL was "clearly the cheapest" HFC at 1.8× book in 2017. Blockbuster lending-sector IPOs tend to mark a near-term segment top.
Rough fair value: P/B ≈ (ROE − g) ÷ (cost of equity − g). Cross-check with a reverse-DCF: what growth does the current price imply, and is the market too bullish or too bearish? Recompute P/B for pending dilution (rights issues, ESOPs) before trusting the optical multiple.
Classify every bull argument as Signal / Trend / Fact / Estimate — distrust Signals, and check whether a smart-money signal is currently reversing.
Sector-specific metrics — NBFC, HFC, MFI
NBFC / gold: yield to AUM, credit cost to AUM, AUM growth vs peers, RoAA/RoAE quarterly. Gold lending is the highest-ROA lending segment (~4.5%); diversification away from the core ("de-worsification") into MFI/vehicle/housing is what has historically broken asset quality and the multiple.
Housing finance: GNPA quality tiers — A-players kept GNPA < 1.2% in every one of the last 10 years, B-players never above 2.4%. Average ticket size is the glass ceiling: growing ATS walks an HFC into bank competition. Watch disbursement growth, BT-out, and DSA-sourced books.
Microfinance / SFB:X-bucket collection efficiency > 99% is healthy — it's the earliest warning metric (current dues from non-overdue borrowers). Credit cost as % of AUM is the swing line (~3% normal, 10%+ crisis). Net government-guarantee claims (CGFMU) against NNPA. State concentration is the tail risk.
Credit rating reports are underused: the rating itself is the least important part — mine Key Strengths / Key Weaknesses for entry barriers, funding costs, counterparty payment cycles, and explanations of anomalies you've spotted. Discount their growth forecasts.
Workflow — during the season
Never research only one stock in a sector — minimum the top 3. Sector census first: same metrics for every listed player, then hunt anomalies in both directions. That's what this grid is.
Calendar: board-meeting dates on nseindia.com corporate announcements; Screener.in and Trendlyne run free earnings calendars. Most financials report mid-July to early August.
Source: press release first (10 minutes), investor presentation for segment detail, concall transcript for guidance — management tone on margins and asset quality moves stocks more than the reported quarter. Track guidance vs delivery quarter by quarter.
Behavioural hygiene: if a price move triggers your interest, sleep on it before acting; separate the thesis (is the lender good?) from the expression (shares, rights entitlements, position size). Position size is conviction.
Real Estate · Base quarter: Q4FY26 (ended 31 March 2026)
Real Estate Tracker
Developers are pre-sales machines: bookings and collections lead, P&L revenue lags recognition by years. This grid is seeded from Q4FY26 (Q1FY27 operating updates fold in as developers report). Click a company for trends and analysis.
Scorecard
All figures consolidated, latest reported quarter (Q4FY26 unless noted). Pre-sales = booking value, the lead indicator; reported P/E is on FY26 PAT and MISLEADS for developers (revenue recognises 3-4 years after sale). Econ P/E = market cap ÷ economic PAT, where economic PAT = FY26 annual pre-sales × estimated embedded net margin (+ rental profit where material) — the Nine One Capital substitution. Margin estimates: luxury 25-40%, premium ~16-20%, mid 10-13%, haircut for conservatism; flagged per company. ND/E negative = net cash.
Company
Model
Pre-sales ₹cr
Pre-sales YoY
Collections
Revenue
EBITDA %
PAT ₹cr
Net debt ₹cr
ND/E
Mkt cap ₹cr
P/E (FY26)
Econ P/E est
Pre-sales ranking
Latest-quarter booking value across the sector — size and momentum at a glance.
How to read a developer
Framework adapted from Nine One Capital's "Why Real Estate Stocks Are Hard to Analyse but Worth the Effort" (Jul 2026): six parameters plus one, and a refusal to use reported revenue, PAT or P/E for anything.
Why every screen gets this sector backwards
A developer sells a flat 3-4 years before delivery; under Ind AS 115 most (~15 of 20 listed) recognise revenue only at handover. Sales and cash happen today; revenue and profit report 3-4 years later. Prestige sold ₹30,024 cr in FY26 but reported PAT of ₹1,312 cr — ~₹66,000 cr of sold value hasn't touched the revenue line.
The balance sheet misleads too: "inventory" is largely sold-but-unrecognised future revenue, and the biggest "liability" — customer advances — is interest-free project funding (Godrej carries >₹36,000 cr of it against ₹5,131 cr reported revenue).
Interest capitalisation is the single biggest margin lever: two identical developers can report EBITDA margins 10 points apart purely on this choice. Quick check: interest PAID (cash-flow statement) vs finance cost (P&L) — the gap sits in inventory and returns as future cost.
Result: revenue growth, EBITDA margin, PAT, ROE, ROCE, D/E and P/E all inherit these distortions. That is why the mispricing exists — and persists.
The six parameters, plus one
1. Pre-sales and collections, not revenue — the two honest numbers; no accounting policy manufactures a booking or a bank credit. Track the GDV pipeline too (shelf stock of future pre-sales): a ₹4,000 cr/yr seller with ₹60,000 cr of pipeline is a different business from one with ₹8,000 cr.
2. Economic PAT = current pre-sales × embedded net margin (from concalls, not the P&L: luxury 25-40%, premium 16-20%, mid 10-13%) + rental profit. Companies at 60-80× reported earnings turn out to be at 8-15× economic earnings — the Econ P/E column above.
3. Value the rental book separately, at NOI × multiple like a REIT — accounts carry it at cost (Oberoi: ₹4,433 cr carried vs ₹16,182 cr own-disclosed fair value). The annuity book is the sector's downturn insurance.
4. Compute the debt yourself: add JV debt (equity-accounted ventures hide borrowings), add quasi-debt (deferred land payments, JDA obligations, payable-when-able NCDs), and run the interest test (interest paid vs expensed).
5. Operating cash flow is the reference point — nearly policy-proof. Cross-check OCF vs PAT over years: DLF converts ~1.4× PAT to OCF, Brigade ~1.5×; FY26's loudest warnings were Godrej (OCF −₹2,003 cr vs PAT +₹1,841 cr) and Mahindra Lifespace. Four consecutive years of negative OCF behind a growth story = pass, regardless of multiple.
6. NAV as cross-check, with a catalyst test — a cheap NAV without a catalyst stays cheap (Sunteck's decade-long discount). No mechanical event forcing the gap shut (completions converging, rental stabilisation, legacy roll-off) → no position.
+1 (most important): management track record and accounting choices. Read accounting policy as a character statement — a promoter who expenses interest when he could capitalise (Oberoi) is voluntarily reporting lower profits. Check reputation with societies, lenders and customers through 2009 and 2020. "We would rather own a conservative bookkeeper at 12× economic earnings than an aggressive one at 6×."
Screens and cycle notes
The post's five filters: pre-sales compounding 25%+ with 8-10 years of GDV shelf stock; conservative accounting; true net debt ~zero; promoter with a decades-long delivery record; a rental book scaling toward meaningful size. Very few names pass all five.
Geography preference: MMR first (redevelopment flywheel — ~₹100 cr equity per ₹1,000 cr GDV, >40% IRR on deployed capital when it works), then Ahmedabad, then NCR; deliberately light on Bengaluru (AI-disruption risk to the end-user base).
Cycle honesty: housing volumes cooled across top cities even as value hit records — this cycle is maturing, not beginning. The re-rating mechanism is completion-driven convergence of reported PAT toward economic PAT.
Sector-vs-ancillary gap: wires/cables/pipes/tiles trade at 30-80× clean earnings while developers, measured economically, sit at 6-15× growing pre-sales 25%+ — among the widest sector-vs-ancillary valuation gaps visible today.
Pharmaceuticals · Base quarter: Q4FY26 (ended 31 March 2026)
Pharma Tracker
Eight large-caps across the models — US generics, India branded, specialty, CDMO. The quality-of-earnings traps here are exclusivity windfalls (one-drug quarters), milestone income, and remediation costs; the mix (US vs India vs specialty) matters more than the headline. Q1FY27 results fold in as they report.
Scorecard
Consolidated, latest reported quarter (Q4FY26 unless noted). US share = US revenue as % of total where disclosed; R&D % of sales; P/E on FY26 PAT. Click a company for its trends, one-offs and analysis.
Company
Model
Revenue ₹cr
Rev YoY
EBITDA %
PAT ₹cr
PAT YoY
US share
R&D %
Net debt ₹cr
Mkt cap ₹cr
P/E (FY26)
Margin ranking
Latest-quarter EBITDA margin — the cleanest cross-model quality read (specialty and India-branded structurally out-earn commodity generics). Note Lupin's is exclusivity-inflated and Dr. Reddy's is cliff-depressed — see their pages.
Jewellery · Q1FY27 season (quarter ended 30 June 2026)
Jewellery Tracker
Retailers and one B2B manufacturer, in a quarter defined by gold: prices up ~60-70% YoY, the customs duty hiked 6%→15% mid-quarter (13-May), and the rupee weak. The sector's QoE trap this season — price-led revenue growth and inventory gains dressed as operating performance. Grammage and buyer counts are the honest volume numbers; most companies don't lead with them.
Scorecard
Latest reported period per company — Q1FY27 where results are out, Q4FY26 where only the March-quarter transcript/deck exists (marked). SSSG = same-store sales growth (price-inflated this season — read with the volume notes). P/E on FY26 PAT. Gold-volume and inventory-gain caveats live on each company page.
Company
Model
Period
Revenue ₹cr
Rev YoY
SSSG
Gross %
EBITDA %
PAT ₹cr
PAT YoY
Stores
Mkt cap ₹cr
P/E (FY26)
Growth vs volume
Revenue growth ranked — with the gold-price asterisk: hover-free honesty is in each company's notes (e.g. Thangamayil: +71% revenue on +9% gold volume and flat buyer counts).
QSR & Dining · Q1FY27 season (quarter ended 30 June 2026)
QSR & Dining Tracker
The listed quick-service franchisees plus the casual-dining operators. This sector's QoE trap is structural: Ind-AS 116 capitalises rent, so 13-20% "EBITDA margins" collapse to 0-5% net margins once lease depreciation and interest return below the line — PAT and cash are the honest numbers, and "borrowings" are mostly lease liabilities. The June 2026 quarter looks like a demand inflection after two weak years: all three full reporters so far (Westlife, Devyani, Sapphire) printed profits with positive headline SSSG — Jubilant's full P&L lands ~13-Aug (its update showed +14.1% revenue but LFL of just 2.5%), RBA's on 3-Aug. At ~₹62,000 cr of combined market cap on ~₹230 cr of combined trailing PAT, the recovery is substantially pre-paid. A consolidation wave is running underneath: Sapphire is merging into Devyani (one Yum! vehicle, 3,000+ stores) and Burger King India has new promoters arriving with ₹1,500 cr.
Scorecard
Latest reported quarter per company (Q1FY27 where out). EBITDA % is the reported post-Ind-AS-116 figure — comparable across rows but flattered ~5-6 points versus pre-lease economics (Westlife's own framework: ~13% reported ≈ ~7.5% pre-Ind-AS). P/E on TTM PAT; "loss" where trailing PAT is negative.
Company
Brands
Period
Revenue ₹cr
Rev YoY
SSSG
EBITDA %
PAT ₹cr
Stores
Mkt cap ₹cr
P/E (TTM)
SSSG — the inflection watch
Same-store sales growth, latest reported quarter. This is the sector's lead indicator (the equivalent of pre-sales for developers): store rollouts only create value if the boxes already open are growing. FY26 was a negative-SSSG year for most of these names — the June quarter is the first broad positive print.
Chemicals · Q1FY27 season (quarter ended 30 June 2026)
Chemicals Tracker
Specialty chemicals and pigments. The sector's QoE questions this season: how much of the margin print is realization (war-driven raw-material pass-through, doubled ocean freight, Chinese price hikes of 30-40% on VAT-rebate cuts) versus volume — and whether cheap pre-war inventory is quietly funding reported spreads. Companies added as their filings arrive.
Scorecard
Latest reported quarter, consolidated. EBITDA computed on the company's own definition (incl. other income) where not disclosed directly. P/E on trailing-twelve-month PAT.
Healthcare Services · Q4FY26 base (Q1FY27 prints from August)
Healthcare Services Tracker
Single-specialty healthcare operators. The sector's recurring QoE questions: government-scheme receivables (payor concentration, aged AR, ECL provisions), step-wise reimbursement pricing that arrives in decade-sized jumps and then plateaus, and adjusted-EBITDA definitions that drift wider post-listing. Companies added as their filings arrive.
Scorecard
Latest reported quarter, consolidated, reported (not company-adjusted) basis. P/E on trailing reported PAT — adjusted-basis multiples live on each company page.
Technology · Q1FY27 season (quarter ended 30 June 2026)
Technology Tracker
Cloud, AI infrastructure, platforms and hardware distribution. The sector's QoE questions: capex-led "growth" whose returns depend on GPU useful-life assumptions (depreciation policy is the whole P&L), utilization vs contracted order book, customer/brand and supplier concentration, working-capital-funded distribution growth that never becomes cash, and the gap between EBITDA optics and cash-on-cash returns of rapidly-obsoleting hardware.
Scorecard
Latest reported quarter, consolidated. P/E on trailing-twelve-month PAT.
Manufacturers and EPC-linked businesses. Recurring QoE questions: government-customer receivables and their aging, order-book quality versus execution, working-capital cycles funding "growth", and special situations (mergers, group restructurings) where the swap math matters more than the P&L.
Scorecard
Latest reported period, consolidated where available. P/E on trailing-twelve-month PAT.
Consumer businesses and export processors. Recurring QoE questions: forex and tariff exposure on export books, commodity-input pass-through, other income versus operating profit, and diversification moves that change the business's identity.
Scorecard
Latest reported period. P/E on trailing-twelve-month PAT.
Contract development and manufacturing — the sector where the generics scorecard misleads. What matters instead: the CDMO segment's share and growth (not group revenue), the pipeline's stage-mix (Phase I economics differ from commercial by an order of magnitude), disclosed order book or committed revenue, capacity utilization against the capex cycle, and customer concentration. The recurring QoE trap: project-based revenue arrives in slugs, so single quarters swing violently — the annual line is the honest unit, and a blowout quarter measured against a trough quarter tells you almost nothing. The structural tailwind everyone is chasing: peptide/GLP-1 capacity and the China+1 shift in innovator sourcing.
Scorecard
Latest reported quarter, consolidated. "CDMO segment" = the contract-manufacturing/services line, with its share of total revenue — the number that should drive the multiple. P/E on trailing-twelve-month PAT.
Company
Model
Period
Revenue ₹cr
Rev YoY
EBITDA %
PAT ₹cr
CDMO ₹cr
CDMO % of rev
Key metric
Mkt cap ₹cr
P/E (TTM)
How to read a CDMO quarter
The framework adaptations this sector needs.
Five questions that decide the multiple
Is the CDMO line growing, or is the group? Group revenue blends legacy generics/API businesses with contract manufacturing. Only the CDMO segment earns a CDMO multiple — track its share of revenue quarter by quarter.
Where is the pipeline in its stages? A hundred Phase-I projects are worth less than three commercial supply agreements. Stage-mix disclosure (Phase I/II/III/commercial counts) separates real visibility from funnel theatre.
Is there an order book — and will they quantify it? Most Indian CDMOs won't. When a company discloses committed revenue, that disclosure is itself a quality signal; when a partner underwrites dedicated capacity (Neuland/Gland), that is demand validation by proxy.
Utilization against the capex cycle. CDMO growth is capex-led: revenue lags spending by 4-8 quarters, so depreciation arrives before the sales do (E2E's GPU problem in pharma form). High utilization forcing expansion is bullish; capex without utilization disclosure is not.
Lumpiness discipline. Project revenue arrives in slugs; a +100% quarter off a trough and a -20% quarter off a peak can describe the same business. Compare years, and treat any single quarter annualised as a hypothesis, not a run-rate.
A decision log, not a portfolio tracker. The point is to write down why you acted and what would prove you wrong — before the outcome is known — so that later you can tell skill from luck. Every entry is checked against the process rules below, and any company already on this tracker brings its own quality-of-earnings flags with it. Data lives in this browser only; export regularly.
Process check
These test your journalling discipline — not whether the trades are good. A decision can be well-made and still lose money; the log is how you tell the difference later.
Log a decision
Write the thesis and the falsifier before you act, in your own words. If you cannot state what would make you wrong, that is itself the finding.
Decision log
Newest first. Click a row to expand the full thesis, the falsifier and — where the name is tracked here — what this site's own notes flag about it.
Date
Company
Action
Price ₹
Size
Conv.
Falsifier
Review
How to use this well
The habits that make a journal worth keeping.
Six rules, and why each one earns its place
Write it before you act, not after. A thesis written post-trade is a rationalisation. The whole value of the log is that it captures what you actually believed at the moment of decision, including the parts you'd later prefer to forget.
Always state the falsifier. "I'd be wrong if X" is the single highest-value line in any entry. Without it there's no exit discipline and no way to grade the decision later — you'll simply reinterpret the thesis to fit whatever happened.
Grade decisions, not outcomes. A good process can lose money and a bad one can make it. At review, ask "given what I knew then, was this reasonable?" before asking "did it work?" Only the first question makes you better.
Record the state of mind. Patterns show up over a year that you cannot see in a single trade — buying after a run, averaging down to feel right, selling to relieve discomfort. The mood field is where that evidence accumulates.
Review on schedule, not on price moves. Set the review date when you enter. Revisiting because the price moved is how you end up reacting to noise; revisiting on a date is how you check a thesis.
Note when you do nothing. "Watch" entries — names you considered and passed on — are as instructive as trades, and they're the only record of the mistakes you avoided.