ETF data in Excel is the workflow allocators reach for whenever they need to look at twenty-plus funds at the same time. Issuer web pages were built for a single product view. Excel was built for grids. The friction has never really been the spreadsheet itself, it has been getting current price, AUM, expense ratio, yield, and return data into the cells fast enough to actually compare funds while the market is moving. This guide shows how to pull live ETF data into Excel with MarketXLS, which fields actually move an allocation decision in late May 2026, and how to combine those fields into a 25-ETF screener that ranks every fund on a single composite Cost-Quality Score. A live-formula template and a static sample workbook with snapshot values as of May 29, 2026 are linked further down so you can open them side by side while you read.
ETF Data in Excel: The Fields That Matter (At a Glance)
Most ETF research compresses down to a small set of fields. The table below shows the columns the rest of this guide is built around, why each one matters, and the exact MarketXLS function that pulls it into Excel.
| Field | Why it matters | MarketXLS formula |
|---|---|---|
| Last price | Anchor for every position-sizing calculation | =QM_Last("SPY") |
| Net assets (AUM) | Liquidity proxy. Sub-billion AUM tends to widen spreads | =FundNetAssets("SPY") |
| Total assets | Larger reporting view of fund size | =FundTotalAssets("SPY") |
| Expense ratio | Long-term drag on returns | =FundExpenseRatio("SPY") |
| Dividend yield | Trailing 12-month income for the holdings | =DividendYield("SPY") |
| YTD price change | Year-to-date momentum check | =ChangePercentYTD("SPY") |
| YTD total return | YTD return including distributions | =StockReturnYTD("SPY") |
| 30-day volatility | Annualized realized volatility | =StockVolatilityThirtyDays("SPY") |
| 52-week high | Range upper bound | =FiftyTwoWeekHigh("SPY") |
| 52-week low | Range lower bound | =FiftyTwoWeekLow("SPY") |
| Average daily volume | Trading liquidity | =AverageDailyVolume("SPY") |
| Beta | Sensitivity vs broad market | =Beta("SPY") |
| Fund family | Issuer name | =FundFamily("SPY") |
| Inception date | Track record window | =FundInceptionDate("SPY") |
| Top holdings | Constituents for overlap checks | =FundHoldings("SPY") |
| Report period | Most recent reporting date | =FundReportPeriodEndDate("SPY") |
Every cell in the template version of the workbook is a live MarketXLS formula. The sample workbook is pre-filled with snapshot values from May 29, 2026 so the model is fully readable even without a MarketXLS session running.
Why Late May 2026 Is a Useful Moment for an ETF Rebuild
Late May is the boundary between the first-quarter earnings season, which finished a few weeks ago, and the summer trading window that historically runs thinner volume. Quarter-end rebalancing in June will move large amounts of money across factor and sector ETFs, and any allocation decision made in the next two weeks is effectively a decision about how to be positioned into that flow. That is a good reason to bring fresh ETF data into Excel right now and to do it on a single sheet so the columns can be sorted and filtered against each other.
The macro background is also doing some work. The energy sector is up roughly 23% year to date in the snapshot, technology is up roughly 32%, and broad bond exposure is roughly flat as long rates stay range-bound. Year-to-date dispersion of more than 30 percentage points across sectors is large enough that the choice between, say, an equal-weight broad index and a sector tilt actually matters this year. A screener that is one page wide makes that visible at a glance instead of requiring a deck of tabs.
The 25-ETF Universe in the Workbook
The dashboard is wired to 25 liquid, well-known ETFs that span the major asset class buckets. The mix is deliberately diversified, not curated for a single thesis.
| Bucket | Tickers |
|---|---|
| US broad equity | SPY, IVV, VOO, VTI, QQQ, DIA, IWM |
| US factor | VTV (value), VUG (growth), SCHD (dividend) |
| US sector SPDRs | XLE, XLK, XLF, XLV, XLY, XLI, XLU, XLP |
| International equity | VXUS, EFA, VWO |
| Fixed income | AGG, TLT, HYG |
| Commodity | GLD |
Column A on the Main Dashboard sheet is the ticker. Every other column in the template version is a live MarketXLS call. If you want a different universe, replace the tickers in column A and the rest of the row recalculates. The only sheet that needs a manual update when you change tickers is the Allocation Builder, because the model portfolios reference specific symbols.
Snapshot: 25 ETFs On One Page
The Main Dashboard sheet renders the whole universe in one table. Below is a compressed view of the late May 2026 snapshot. Static values shown for readability; the template file has live formulas in every numeric cell.
| Ticker | Asset Class | Price | Expense % | Yield % | YTD % | 1-Yr % | 30D Vol % |
|---|---|---|---|---|---|---|---|
| SPY | Equity | 756.48 | 0.095 | 1.03 | 10.73 | 28.35 | 14.7 |
| VOO | Equity | 695.49 | 0.030 | 1.08 | 10.69 | 28.38 | 14.7 |
| VTI | Equity | 372.54 | 0.030 | 1.06 | 10.77 | 28.52 | 15.0 |
| QQQ | Equity | 738.31 | 0.180 | 0.42 | 20.42 | 42.23 | 19.2 |
| DIA | Equity | 510.78 | 0.160 | 1.42 | 5.61 | 20.79 | 14.3 |
| IWM | Equity | 290.43 | 0.190 | 0.91 | 16.74 | 41.62 | 21.0 |
| VTV | Equity | 211.85 | 0.030 | 1.92 | 9.88 | 23.61 | 11.4 |
| VUG | Equity | 89.60 | 0.030 | 0.40 | 10.57 | 30.13 | 19.5 |
| SCHD | Equity | 32.50 | 0.060 | 3.29 | 17.20 | 24.19 | 9.9 |
| XLK | Sector | 191.02 | 0.080 | 0.48 | 32.38 | 65.45 | 25.0 |
| XLE | Sector | 56.29 | 0.080 | 2.50 | 23.31 | 38.08 | 24.9 |
| XLF | Sector | 51.58 | 0.080 | 1.52 | -6.10 | 1.22 | 14.1 |
| XLV | Sector | 149.47 | 0.080 | 1.72 | -3.88 | 12.69 | 15.2 |
| XLI | Sector | 173.13 | 0.080 | 1.17 | 9.59 | 21.22 | 20.5 |
| XLU | Sector | 44.42 | 0.080 | 2.54 | 2.87 | 8.45 | 16.7 |
| XLP | Sector | 82.91 | 0.080 | 2.58 | 6.72 | 0.10 | 14.3 |
| VXUS | International | 86.06 | 0.050 | 2.76 | 12.44 | 28.56 | 22.4 |
| EFA | International | 104.80 | 0.320 | 3.17 | 8.00 | 18.00 | 21.2 |
| VWO | International | 59.88 | 0.060 | 2.48 | 9.01 | 27.40 | 22.1 |
| AGG | Bond | 99.06 | 0.030 | 3.95 | -0.79 | 0.98 | 4.8 |
| TLT | Bond | 85.76 | 0.150 | 4.57 | -1.46 | -0.60 | 10.4 |
| HYG | Bond | 80.31 | 0.490 | 5.82 | -0.45 | 0.93 | 5.8 |
| GLD | Commodity | 417.12 | 0.400 | 0.00 | 4.73 | 37.39 | 26.8 |
A few patterns jump out once the dashboard is on one screen. Technology and energy are the two strongest one-year buckets, with year-to-date moves running well ahead of broad indices. Financials and healthcare are the two negative year-to-date sector readings, even though both still show small positive one-year totals. Bond ETFs are roughly flat on the year, with HYG yielding the most and TLT carrying the largest interest-rate sensitivity. Gold is up on a one-year basis but quieter year to date than equity sectors. These are the kinds of observations that take three clicks in Excel and twenty browser tabs anywhere else.
What Each Field Actually Tells You
Last price feels obvious until you try to size a position from a stale figure. =QM_Last("ticker") returns the most recent traded price the MarketXLS feed has on file, and it updates every time the workbook recalculates. The rest of the row anchors to that price column, so a refresh on a single cell flows through the position-sizing math on the Allocation Builder sheet.
Net assets are a liquidity proxy. =FundNetAssets("ticker") returns the dollar value of fund assets at the most recent reporting date. As a rough rule of thumb, broad index ETFs with more than ten billion dollars in assets tend to have tight spreads and deep order books. Sub-billion ETFs may be perfectly investable but warrant a check of the bid-ask spread before placing a large order. =FundTotalAssets("ticker") reports the broader assets figure where the issuer publishes both numbers.
Expense ratio is the single most reliable predictor of long-term net return inside the same asset class. =FundExpenseRatio("ticker") returns the annual ratio. In the snapshot above, the three broad US equity funds (VOO, VTI, IVV) all run at three basis points, while older funds in the same exposure (SPY at 9.45 basis points) carry slightly higher fees. Active mandates and niche international exposures can run an order of magnitude higher.
Dividend yield is the trailing twelve-month income generated by the fund's holdings. =DividendYield("ticker") returns the value as a percentage. Yield matters more for some buckets than others. For broad index funds it functions as a cash-flow floor; for dividend-tilt funds like SCHD it is the entire thesis; for high-yield bond funds like HYG it is the headline number that justifies the fund's existence. Yield comparisons across asset classes are not apples-to-apples, which is why the screener keeps yield in its own column rather than rolling it into a composite return number.
Returns come in two flavors. =ChangePercentYTD("ticker") returns the year-to-date price change, while =StockReturnYTD("ticker") returns the year-to-date total return including dividends. Both default to a percentage. The Main Dashboard uses both. For high-yield assets like HYG or TLT, the gap between price change and total return is meaningful. For low-yield growth funds like QQQ or VUG, the two columns sit on top of each other.
Volatility is the risk gauge. =StockVolatilityThirtyDays("ticker") returns annualized realized volatility computed from the last thirty trading days. The number is useful as a comparison across funds, not as a forecast. In the snapshot above, broad market and defensive sectors cluster between 10% and 16%, growth and small-cap funds run between 18% and 22%, and concentrated commodity or sector ETFs can hit 25% or higher.
The 52-week range and average daily volume columns complement the others. =FiftyTwoWeekHigh("ticker") and =FiftyTwoWeekLow("ticker") give you the range a fund has traded in over the past year, which is useful for thinking about position-sizing and where to set a mental stop. =AverageDailyVolume("ticker") returns the daily share count, which tells you how large an order you can place before pushing the price around.
Beta and fund family are the qualitative columns. =Beta("ticker") returns the sensitivity of the ETF to the broad market. For a broad index like SPY the value is around 1.00 by definition. For QQQ or XLK the value runs above 1.10 because the underlying is more growth-heavy. For utilities or staples it sits below 0.80. =FundFamily("ticker") tells you who runs the fund, which matters when you are checking issuer concentration in your portfolio.
The Cost-Quality Score (One Number, Four Inputs)
The dashboard's right-most column is a composite called the Cost-Quality Score. It is a single number between 0 and 100 that blends four inputs:
- Expense ratio: 25 points. Zero percent expense earns 25, anything above 0.50% earns zero. Linear in between.
- One-year return: 25 points. A 20% return earns 25, anything below -10% earns zero. Linear in between.
- Net assets: 25 points. Fifty billion dollars in assets earns 25, sub-billion earns zero. Linear in between.
- 30-day volatility: 25 points. Ten percent realized volatility earns 25, anything above 40% earns zero. Linear in between.
In the May 29 snapshot, the broad equity index funds (VOO, VTI, IVV) and the dividend-tilt SCHD score in the strong band. The sector funds split. XLK and XLE earn their cost score (eight basis points is cheap) but get penalized on volatility. QQQ scores well on return but pays a fee premium versus VOO. Defensive funds like XLU and XLP earn the volatility points but lag on one-year return. The scoring formula is editable on the Main Dashboard sheet. Change the breakpoints if you want a different sensitivity, and the verdict column ("Strong", "Solid", "Watch", "Weak") updates automatically.
The point of the score is not to rank funds the way a fund rating service does. It is to give you a single column you can sort by, so a 25-row table compresses into "look at the green band first." Used that way, the score is a screening aid that lets the rest of the analysis happen on a smaller, more relevant set of funds.
The Allocation Builder: Three Model Portfolios From One Input Cell
The Allocation Builder sheet turns the dashboard into something you can actually size. The yellow cell at the top of the Main Dashboard holds your portfolio size in dollars. The Allocation Builder reads that value with ='Main Dashboard'!B5, then sizes three model portfolios from it.
The Conservative model leans 45% into bonds and gold, holds about 30% in defensive equity (SCHD, VTV, XLP, XLU), and parks the remaining 25% in a mix of broad market and international exposure. The Balanced model splits roughly 60/30/10 across equity, bonds, and alternatives, with the equity side diversified across factors and regions. The Aggressive model goes about 95% into equity with a growth and small-cap tilt and emerging-markets exposure.
For each ticker in each model, the sheet projects an annual income figure using the live dividend yield column from the dashboard and a weighted fee figure using the live expense ratio column. The totals row at the end of each model gives you a blended yield, a blended expense ratio, and total annual income for the assumed portfolio size. None of those numbers are hard-coded. Change the input cell from 250,000 to a different number and every row in every model recomputes.
The Holdings Drilldown: One Cell, One Spilled Table
ETF overlap is the silent killer of diversification. If you hold SPY and QQQ and VOO, you are likely concentrated in the same dozen mega-cap stocks across three tickers, even though the three funds look distinct on a category column. The Holdings Drilldown sheet handles this with a single formula: =FundHoldings(B4) spills the complete top-holdings table for whichever ticker sits in cell B4.
Replace SPY with QQQ in B4 and the table refills with the Nasdaq-100 constituents. Replace it with XLK and you get the technology sector SPDR positions. In each case, the metadata cells above (fund family, inception date, net assets, expense ratio) update through their own formulas: =FundFamily(B4), =FundInceptionDate(B4), =FundNetAssets(B4), =FundExpenseRatio(B4). That is the test of a useful ETF workbook: change one cell and every dependent cell respects it.
The Asset Class Rollup: Top-Down View Without Rebuilding
The Asset Class Rollup sheet uses native Excel AVERAGEIFS against the dashboard. Each row averages expense, yield, YTD return, one-year return, 30-day volatility, beta, and Cost-Quality Score across all funds in a bucket. Equity, Sector, International, Bond, and Commodity each get a row.
The point of this sheet is to make a portfolio-level conversation faster. If a client asks "what is the average expense ratio of the international funds we own?" you point to a cell that reads the live values straight from the Main Dashboard. If you want to ask "what is the average one-year return of the bond bucket?" you look at the same row. No copy-paste, no rebuilding the rollup whenever a ticker changes.
Download the Templates
Download the templates:
- - Pre-filled with snapshot data from May 29, 2026 plus a reference column showing the MarketXLS formula that produced each value.
- - Live-updating formulas in every numeric cell. Requires an active MarketXLS session.
Both files contain six sheets: How To Use, Main Dashboard, Cost vs Performance, Allocation Builder, Holdings Drilldown, and Asset Class Rollup. Each sheet has a "MarketXLS Functions Used" box at the bottom listing every formula that powers the rows above.
Building the Same Workbook From Scratch
If you want to assemble the workbook yourself rather than open the linked file, the steps are short.
Start with a single sheet. Put tickers in column A starting at row 13. In row 12 put the column headers from the table at the top of this article. In columns D through N use the MarketXLS formulas: =QM_Last(A13), =FundNetAssets(A13), =FundExpenseRatio(A13), =DividendYield(A13), =ChangePercentYTD(A13), =StockReturnYTD(A13), =StockVolatilityThirtyDays(A13), =FiftyTwoWeekHigh(A13), =FiftyTwoWeekLow(A13), =AverageDailyVolume(A13), =Beta(A13).
Add an input block at the top: portfolio size in B5, target yield in B6, max expense ratio in B7, minimum AUM in B8, max volatility in B9. Color those cells yellow with bold borders so future-you remembers they are inputs.
Add the Cost-Quality Score column. The formula given earlier blends four caps in 25-point increments. Wrap it in ROUND(...,0) so the result reads as an integer. Add a verdict column that returns "Strong", "Solid", "Watch", or "Weak" based on the score band you prefer.
Add a second sheet for cost versus performance. Reference the Main Dashboard columns directly: ='Main Dashboard'!F13 for the expense ratio, ='Main Dashboard'!I13 for the one-year return. Compute a cost score and a return score, sum them into a composite, and add a verdict column.
Add an allocation sheet. Pull the portfolio size with ='Main Dashboard'!B5. For each row in each model, multiply the input by the weight to get a dollar allocation, multiply the allocation by the yield from the dashboard to get projected income, multiply by the expense ratio to get the weighted fee.
Add a holdings sheet. Put a ticker in a yellow input cell and use =FundHoldings(B4) to spill the top-holdings table. Add the metadata cells around it.
Add an asset class rollup sheet. Use AVERAGEIFS against the asset class column on the Main Dashboard. Round the result to two decimal places.
That is the whole workbook. Six sheets, one input cell as the source of truth, every numeric value driven by a MarketXLS formula. If you change a ticker in column A on the Main Dashboard, every dependent sheet updates because every dependent sheet reads from row references on the dashboard.
FAQ
How do I get live ETF data into Excel?
You need a data feed that exposes Excel functions. MarketXLS does this through an add-in that registers functions like =QM_Last("SPY") and =FundExpenseRatio("SPY") directly into Excel's formula bar. Once the add-in is installed and you are signed in, the formulas recalculate when the workbook opens and on demand. Manual copy-paste from issuer pages works for a single snapshot but goes stale within hours and breaks the moment you want to update.
Which MarketXLS function returns the ETF expense ratio?
=FundExpenseRatio("ticker") returns the annual expense ratio for an ETF or mutual fund. The value is a percentage. Pair it with =FundNetAssets("ticker") for the dollar value of the fund and =FundTotalAssets("ticker") for the broader assets figure. Issuer reporting standards differ slightly across families, but the function returns a normalized value drawn from the underlying data feed.
How do I pull top holdings of an ETF into Excel?
=FundHoldings("ticker") spills a table of the fund's top holdings into adjacent cells. Make sure there is enough empty space below and to the right of the formula cell, or the formula will report a spill error. The function is the cleanest way to check overlap between funds you already own and a fund you are considering, because the holdings come in as native Excel rows you can VLOOKUP or filter against.
What ETF fields should I include in a screener?
At a minimum: ticker, asset class, last price, AUM, expense ratio, dividend yield, year-to-date return, one-year return, 30-day volatility, 52-week high, 52-week low, average daily volume, and beta. Above that, the value of additional fields depends on the screen. For an income screen, add =DividendPerShare("ticker") and a payout frequency column. For a sector tilt screen, add =Sector("ticker") and an industry breakdown. For a factor screen, add a value or quality metric column built from the underlying holdings.
Is there a free version of this template?
Both files linked above are free to download. Opening the static sample file does not require a MarketXLS session because every cell is a value, not a formula. Opening the formula version and seeing live updates does require an active MarketXLS session, since the formulas pull from the licensed data feed. See MarketXLS pricing for details on the plans that include ETF functions.
How often does the data refresh?
=QM_Last("ticker") updates as often as the workbook recalculates. By default that happens when the file opens, when you press F9, and when MarketXLS triggers an automatic refresh on the schedule set in the add-in. Most allocator workbooks run a refresh once per minute during market hours, which keeps the screener current without overwhelming the data feed.
The Bottom Line
ETF data in Excel is a workflow question more than a data question. The data is available, the formulas exist, and the workbook scaffold takes an afternoon to build. The harder question is whether you keep the workbook on one sheet wide enough to compare twenty funds at once, or whether you spread the same data across twenty browser tabs and lose the ability to sort. The 25-ETF screener attached to this post is one answer to that question. Pulling live numbers with MarketXLS formulas, scoring funds against a composite Cost-Quality measure, and sizing three model portfolios from a single yellow input cell is enough structure to actually run an allocation review without leaving Excel.
This template and analysis are educational, not investment advice. The fund inclusions are illustrative, not endorsements. Past performance does not guarantee future results. Set your own constraints, change the breakpoints in the score, and replace the ticker list with the funds you actually care about.
Ready to bring live ETF data into your spreadsheet? Start at marketxls.com or book a demo to see the formulas in a working session.
