A capital markets stocks screener in Excel ranks investment banks, brokers, exchanges, and asset managers on valuation (P/E, price-to-book), profitability (ROE, operating margin), and momentum (52-week range, trend), then combines them into a composite score. The free template in this post scores twenty names across six sub-segments with MarketXLS formulas such as =PriceToBook("MS") and =ReturnOnEquity("GS"), and adds an EPS scenario grid, a single-stock entry checklist, and a sleeve allocator. It was written as Q2 2026 bank earnings pointed to a rebound in trading and investment-banking revenue.
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The point is not to tell you what to buy. The point is to give you a repeatable, transparent scoring system so you can see how twenty of the most-watched capital-markets names stack up against each other on the metrics that actually move these stocks, and refresh the whole thing with a single recalculation.
Capital Markets Stocks at a Glance: The Q2 2026 Setup
Capital markets is the corner of the financial sector that lives and dies on activity: trading volumes, deal flow, assets under management, and fee generation. Unlike a plain-vanilla commercial bank that earns most of its money from net interest margin on loans, capital-markets firms are levered to markets themselves. When volatility rises, exchanges print volume. When confidence returns, M&A pipelines convert and boutique advisers collect fees. When markets rally, asset managers see AUM-based fees climb. That is why this group tends to be higher beta than the money-center banks, and why the Q2 2026 earnings season matters so much for it.
Here is the snapshot the screener organizes for you, grouped by sub-segment:
| Sub-Segment | Example Names | Primary Revenue Driver | Cyclicality | Q2 2026 Tailwind |
|---|---|---|---|---|
| Bulge-Bracket IB | GS, MS | Trading + advisory fees | High | Trading rebound + IB backlog |
| Broker / Wealth | SCHW, IBKR, LPLA, RJF | Net interest + activity fees | Medium | Client cash + higher activity |
| Exchanges | CME, ICE, NDAQ, CBOE | Volume-based fees | Low | Elevated volatility lifts volume |
| Asset Managers | BLK, TROW, BEN | AUM-based fees | Medium | Market gains lift AUM |
| Alt Asset Managers | KKR, APO, BX, ARES | Management + performance fees | High | Fundraising and realizations |
| Boutique Advisory | EVR, HLI | Pure advisory fees | High | M&A cycle turning up |
The table above summarizes the group: six distinct engines, each with a different sensitivity to the same macro backdrop. The screener turns that qualitative map into a ranked, scored list you can sort.
Why a Screener, and Why in Excel
You could track these names in a dozen browser tabs. The trouble is that capital-markets stocks are not comparable on a single number. A P/E ratio that looks cheap on a bulge-bracket bank can look expensive on an exchange with structurally higher margins and lower cyclicality. Return on equity means one thing for an asset-light advisory boutique and another for a balance-sheet-heavy investment bank. To compare them fairly you need several metrics side by side, normalized into one composite view.
That is exactly what a spreadsheet is good at. And with the MarketXLS add-in, the spreadsheet is not static: every price, ratio, and metric is a formula that refreshes on recalculation (stock quotes are 15-minute delayed on the Standard plan and real-time on Advanced and Business). You are not copying numbers off a website. You type a ticker once and the workbook pulls the current price, P/E, price-to-book, ROE, dividend yield, operating margin, beta, and the 52-week range, then computes a score.
The Composite Score: How the Screener Ranks
The Main Dashboard sheet assigns each name a 0-to-100 composite score built from three pillars that matter for this group:
- Quality (50% weight): Return on equity (30%) plus operating margin (20%). Capital-markets firms with durable, high returns on equity have historically compounded book value faster, and book value growth is the engine of long-run returns in financials.
- Value (35% weight): A penalty for expensive trailing P/E (20%) and expensive price-to-book (15%). Price-to-book is the classic valuation anchor for financials because so much of the balance sheet is marked to market.
- Momentum (15% weight): Proximity to the 52-week high. Financials trend, and staying near the highs during an up-cycle has historically carried information.
The exact scoring formula that sits behind every row looks like this:
=IFERROR(ROUND(
0.30*MIN(100, ROE*2.5) +
0.20*MIN(100, OpMargin*1.5) +
0.20*MAX(0, 100 - PE*2.2) +
0.15*MAX(0, 100 - PB*9) +
0.15*MAX(0, 100 - PctOffHigh*2.5), 0), "")
You can see and edit this in the workbook. Do not treat the score as a buy signal. It is a transparent, adjustable ranking so you can quickly see which names screen strongly on your chosen blend of quality, value, and momentum, and then do your own homework.
The weights are deliberately exposed as editable cells because different investors care about different things. A value-oriented investor might dial the two valuation components up and the momentum component down to zero, effectively turning the screen into a cheap-and-profitable filter. A trend follower might do the opposite, leaning on proximity to the 52-week high while still keeping a quality floor so the screen never surfaces a low-ROE name at any price. There is no single correct blend. The value of writing the formula out in the open is that you can reason about why a name ranks where it does, rather than trusting a black box you cannot inspect. That transparency is the whole philosophy behind building a screener in Excel instead of renting one.
Building It With Real MarketXLS Formulas
Every data cell in the template version is a verified MarketXLS function. Here is how the core screener row is constructed for Goldman Sachs (ticker GS), and the same pattern repeats down all twenty rows:
Company name =Name("GS")
Latest price =QM_Last("GS")
P/E ratio =PERatio("GS")
Price-to-book =PriceToBook("GS")
Return on equity =ReturnOnEquity("GS")
Dividend yield =DividendYield("GS")
Market cap ($B) =MarketCapitalization("GS")/1000000000
Beta =Beta("GS")
Operating margin =OperatingMargin("GS")
52-week high =FiftyTwoWeekHigh("GS")
52-week low =FiftyTwoWeekLow("GS")
Formula documentation: Name, QM_Last, PERatio, PriceToBook, ReturnOnEquity, DividendYield, MarketCapitalization, Beta, OperatingMargin, FiftyTwoWeekHigh, FiftyTwoWeekLow
Because these are live functions, you are never more than a recalculation away from current data. Swap GS for MS, SCHW, CME, BLK, KKR, or any other ticker and the entire row updates. That is the difference between a screenshot and a screener.
A few notes on why these specific metrics were chosen for capital-markets names:
- Price-to-book is more meaningful than P/E for balance-sheet-heavy investment banks, where earnings can be lumpy but book value is a cleaner anchor. The
=PriceToBook("MS")output tells you what the market is paying for each dollar of Morgan Stanley's equity. - Return on equity is a key quality gate. A firm consistently earning a high ROE is compounding shareholder capital, and
=ReturnOnEquity("BX")lets you compare an alternative asset manager against a traditional one. - Beta flags cyclicality.
=Beta("KKR")typically reads well above 1.0, which is the numeric way of saying alternatives have more torque to the cycle than, say, an exchange. - Operating margin separates the structurally efficient (exchanges like CME often post very high operating margins via
=OperatingMargin("CME")) from the more capital-intensive banks.
The Scenario Analysis Sheet: Operating Leverage in Action
Capital-markets earnings are famous for operating leverage. When trading and investment-banking revenue swings, the change drops disproportionately to the bottom line because a large share of the cost base is relatively fixed. The Scenario Analysis sheet models exactly this.
You enter three inputs in the yellow cells: a base blended EPS for the segment, a fair P/E multiple, and the current segment price. The sheet then runs six revenue scenarios, from a deep freeze where investment banking stalls to a full boom driven by an M&A wave and rate cuts, and shows the implied EPS, a fair value, and the upside or downside versus the current price.
| Scenario | Trading/IB Rev Growth | EPS Impact | Read |
|---|---|---|---|
| Deep freeze | -20% | -28% | Screens rich |
| Soft | -8% | -11% | Below plan |
| Base | 0% | 0% | Fairly valued |
| Rebound | +12% | +17% | Screens attractive |
| Strong upcycle | +25% | +35% | Screens attractive |
| Boom | +40% | +55% | Screens attractive |
The key insight the grid makes visual: a 12% revenue rebound can translate into a roughly 17% EPS swing because of that operating leverage. This is the mathematical reason capital-markets stocks tend to move hard around earnings inflections, and it is why the Q2 2026 rebound narrative has the group in focus. You can seed the base EPS with a live figure using =EarningsPerShare("GS") and cross-check your fair multiple against =ForwardPE("GS").
The Valuation & Entry Framework Sheet
Screening surfaces candidates; a framework keeps you disciplined about them. The Valuation & Entry sheet takes a single watch ticker you type into a yellow input cell and reads eight live metrics against value, quality, and momentum bands:
- P/E against cheap, fair, and rich bands
- Price-to-book against your own target entry level
- ROE against weak, solid, and elite thresholds
- Operating margin for efficiency
- Dividend yield for the income cushion
- Distance from the 52-week high for momentum
- Beta for cyclicality
Type MS into the input cell and the sheet re-reads Morgan Stanley live via =QM_Last(B5), =PriceToBook(B5), =ReturnOnEquity(B5), and the rest. It is a structured way to ask, for any one name, "is this cheap, is it high quality, and is it trending," without eyeballing a chart. Again, this is an educational checklist, not a recommendation.
The Portfolio Allocation Sheet
The Portfolio Allocation sheet turns the analysis into position sizing. Enter your portfolio size, the percentage you want to allocate to a capital-markets sleeve, and a risk-tolerance setting from 1 to 3. The sheet spreads that sleeve across the six sub-segments and computes a dollar allocation and an estimated share count for a sample ticker in each bucket using =QM_Last(E10) and similar live prices.
The logic embedded in the design is straightforward and honest about trade-offs:
- Lower risk tolerance argues for a heavier tilt toward exchanges and asset managers, which earn steadier volume-based and AUM-based fees.
- Higher risk tolerance can justify leaning into bulge-bracket investment banks and alternative asset managers, which carry more operating leverage and more upside to a genuine deal-making and trading up-cycle.
You control every weight in a yellow input column, and a TOTAL row checks that your sub-segment weights sum to 100% within the sleeve. Layer in =DividendYield("BLK") or =Beta("KKR") if you want to weight explicitly by income or by risk.
The Sub-Segment Comparison Sheet
The final sheet is a color-coded map of how the six sub-segments differ on revenue driver, rate sensitivity, cyclicality, typical price-to-book, the specific Q2 2026 tailwind, and the key thing to watch. Red flags high sensitivity or cyclicality, amber is medium, green is low. It is the one-screen answer to "how are these businesses actually different," and it pairs naturally with the numeric screener on the Main Dashboard. Compare structural profitability directly with =OperatingMargin("CME") for an exchange versus =OperatingMargin("EVR") for an advisory boutique.
Download the Templates
Download the templates:
- - Pre-filled with an illustrative snapshot so you can explore the layout immediately, with the MarketXLS formula names shown alongside every value.
- - Live-updating formulas that refresh with the MarketXLS add-in installed.
Both files contain the same six sheets: How To Use, Main Dashboard, Scenario Analysis, Valuation & Entry, Portfolio Allocation, and Sub-Segment Comparison. Every sheet lists the exact MarketXLS functions it uses so you can rebuild or extend it yourself.
How to Use the Screener Responsibly
A screener is a starting point for research, not a conclusion. A few guardrails:
- Compare within sub-segments first. An exchange and a boutique adviser are different businesses; the composite score is most useful when you rank like against like.
- Sanity-check the score against the raw metrics. If a name scores well only because of momentum, know that before you act.
- Remember the cycle. Capital-markets earnings are cyclical by nature. A strong Q2 does not guarantee a strong Q3, and operating leverage cuts both ways.
- Do your own diligence. Read the filings, understand the revenue mix, and form your own view. Nothing in this workbook is investment advice.
Frequently Asked Questions
What is a capital markets stocks screener in Excel?
A capital markets stocks screener in Excel is a spreadsheet that pulls live financial metrics for investment banks, brokers, exchanges, and asset managers, then ranks or filters them on valuation, profitability, and momentum. With MarketXLS, each metric is a live formula such as =PERatio("GS") or =ReturnOnEquity("MS"), so the whole screen refreshes on recalculation instead of being copied by hand.
Which stocks count as capital markets stocks?
Capital markets stocks are financial firms whose revenue comes from market activity rather than traditional lending. That includes bulge-bracket investment banks (GS, MS), brokers and wealth platforms (SCHW, IBKR, LPLA, RJF), exchanges (CME, ICE, NDAQ, CBOE), traditional asset managers (BLK, TROW, BEN), alternative asset managers (KKR, APO, BX, ARES), and boutique advisory firms (EVR, HLI). The screener groups all six sub-segments so you can compare them.
Why are capital markets stocks in focus for Q2 2026?
Q2 2026 earnings season kicked off with the large financial institutions, and the early theme is a rebound in trading and investment-banking revenue after several soft quarters. Because these firms have high operating leverage, even a modest revenue recovery can produce an outsized earnings swing, which is why the group draws so much attention around earnings inflections.
What metrics matter most for capital markets stocks?
Price-to-book and return on equity tend to matter most, because financials are balance-sheet businesses where book value is the cleanest anchor and ROE measures how efficiently that capital compounds. Operating margin, beta, dividend yield, and distance from the 52-week high round out the picture. The screener combines all of these into a single composite score you can adjust.
Do I need the MarketXLS add-in to use the template?
The static sample file opens in any copy of Excel and shows an illustrative snapshot plus the formula names. The live template requires the MarketXLS add-in so functions like =QM_Last("GS") and =PriceToBook("MS") can pull current data. You can see how the add-in works and what data it covers on the MarketXLS site.
Is this screener investment advice?
No. The workbook is an educational tool. Tickers appear only to demonstrate how the formulas and scoring work, and the composite score is a transparent ranking, not a buy or sell signal. Always do your own research and consider consulting a licensed professional.
The Bottom Line
Capital markets stocks are one of the most cyclical, operating-leveraged corners of the market, and Q2 2026 has put them squarely in the spotlight as trading and investment-banking revenue rebounds. A good screener does not predict the cycle; it organizes it, so you can compare investment banks, brokers, exchanges, and asset managers on the same transparent footing and refresh the whole view in seconds. This Excel template does exactly that, with live MarketXLS formulas behind every number and a clear, adjustable composite score on top.
Download both versions above, plug in your own tickers and weights, and make the framework yours. To see how the live formulas pull data across more than a thousand functions, explore MarketXLS, or book a demo to see the screener build out in real time.
