Value vs Growth Dashboard Excel: May 2026 Factor Rotation Tracker

Value vs Growth Dashboard Excel - if you opened this page, you are probably trying to answer the same question every allocator has been wrestling with for the last eighteen months: is the value/growth pendulum about to swing, has it already started, or is the current setup just noise inside a larger growth-led regime? This guide ships a premium, dashboard-grade Excel workbook designed to answer that question on one screen, then walks through how each sheet is built, which MarketXLS formulas drive it, and how to read the spread.

This is not a generic "what is value vs growth" explainer. It is a working template, a methodology, and a checklist for the factor rotation conversation you are already having with your portfolio.

What the Dashboard Tells You at a Glance

The headline view sits inside the Dashboard sheet of the workbook. A row of KPI tiles across the top compresses thirty stocks worth of fundamentals into seven numbers, every one of which is a live MarketXLS formula reference in the template version of the file.

The story almost tells itself. Value carries every classic discount metric - P/E, Forward P/E, Price/Book, dividend yield - while growth carries every classic momentum metric - ROIC, revenue growth, operating margin. The trade is not about which side is "better." It is about whether the discount unwinds before the growth engine slows.

That is exactly what a dashboard is supposed to surface. You should not have to click through twelve tabs and run three pivot tables to see the regime. This workbook puts the regime question on the first sheet you open.

What's Inside the Template

The workbook ships with eleven sheets, designed to flow from "what's the regime" at the top to "how do I act on it" further in. Both the sample (static values, formula comments on every data cell) and the template (live MarketXLS formulas, zero hardcoded data) follow the same design.

1. Cover - branded title page with the 2026 edition tag, "data as of" stamp, and a table of contents. No data lives here, just presentation. This is the page you screenshot when you share the template with a client.
2. How To Use - a step-by-step tutorial covering every sheet, every input cell, and every MarketXLS function used in the workbook. Required reading on the first open.
3. Dashboard - KPI tile row, an embedded indexed-performance chart, a thirty-name screener with conditional formatting heatmaps on every metric column, and a valuation-comparison bar chart at the bottom. This sheet hides gridlines and has a print area set so a portfolio manager can hand a client the dashboard as a one-page handout.
4. Inputs - the only place the workbook needs your input. Yellow cells with bold borders for portfolio size, risk tier (Conservative / Base / Aggressive dropdown), rotation horizon, value tilt, growth tilt, position limits, stop-loss, take-profit, benchmark choice, and rebalance cadence. Five custom ticker rows let you bolt additional names onto the watchlist.
5. Scenario Analysis - a what-if matrix across five macro regimes (rate cut cycle, rate hike cycle, stagflation, soft landing, AI capex boom) with expected value return, expected growth return, the spread, the recommended tilt, and a 1-5 confidence score. Data bars and icon sets make the regime read instant.
6. Strategy - a long-value / long-growth allocation builder. Capital flows in from Inputs, gets split per the tilt, and the trade table shows entry triggers, exit triggers, profit targets, and stop-loss levels per leg.
7. Portfolio - the per-name allocation grid: every ticker, its side, sector, target weight, dollar allocation, and live share count via QM_Last. A pie chart shows basket capital allocation. Data bars highlight the largest positions.
8. Comparison - side-by-side metric averages with a winner column and a red-amber-green spread heatmap. Includes a column chart of every metric side by side.
9. Historical Performance - twelve months of indexed value vs growth performance with month-over-month deltas, a cumulative return summary, and an embedded line chart.
10. Methodology - the documentation page: basket construction, valuation multiples, profitability metrics, growth metrics, risk metrics, scenario tilt logic, limitations, and data refresh cadence.
11. Glossary & Disclaimer - definitions of every term used in the workbook plus the educational-only disclaimer.

Every sheet ends with a "MarketXLS Functions Used in This Sheet" block listing the exact formula references so a user can see which functions power which numbers. Every sheet has frozen panes, a tab color, and a footer line crediting MarketXLS.

The Factor Rotation Question in May 2026

Why build this dashboard now? Because the last cycle made value vs growth feel like a settled debate, and that is usually when it stops being one.

Through 2023 and 2024 the Russell 1000 Growth crushed the Russell 1000 Value as a handful of AI-adjacent mega-caps drove most of the index return. By late 2025, breadth started widening, dividend payers started catching a bid, and the cumulative spread between value and growth indices reached generational extremes. As of the May 2026 snapshot in the workbook, the growth basket has compounded roughly 31% over twelve months while the value basket has compounded roughly 16%. That is still a 15-percentage-point spread in growth's favor over the last year, but the monthly slope has flattened.

The dashboard does not predict the turn. It surfaces the conditions under which the turn historically happens:

• Valuation spread at multi-decade highs - the trailing P/E gap between the two baskets is over 30 turns. The long-run average is roughly 10 turns.
• Quality of growth narrowing - revenue growth is still strong on the growth side, but the dispersion within the basket is widening. A few names carry most of the growth.
• Macro regime ambiguity - rate cut expectations have been pushed out, but the labor market is softening. That historically supports value relative to growth at the margin.

You are not buying a forecast when you use this template. You are buying a structured way to monitor the spread so you notice when it changes.

Why Build This as a Dashboard, Not a Screener

Most value vs growth comparisons end at "here is a list of cheap stocks and a list of expensive stocks." That misses the point of factor investing. The interesting object is the spread, not the level.

A dashboard-first design makes the spread the headline. The KPI tiles compare basket-level averages. The conditional formatting on the screener uses color scales tuned to the relative position of each name within its own basket. The historical performance sheet plots both indexed series so the cumulative gap is impossible to miss.

This is also the design pattern that makes the template usable by a wealth advisor who is not going to memorize a hundred MarketXLS formulas. The user changes one input cell - say, the risk tier dropdown moves from Base to Conservative - and the value tilt nudges up, the dollar allocation rebalances, and the strategy table reflects the new leg sizes. They do not need to know the formulas underneath. They need to read the dashboard.

The 30-Name Screener (and How to Read It)

The screener block in the Dashboard sheet contains fifteen value-leaning names followed by fifteen growth-leaning names. The split is deliberate: same number on each side keeps the basket-level averages comparable.

Value side (15 names): BRK.B, JPM, XOM, CVX, WMT, PFE, KO, PG, VZ, T, MO, BAC, WFC, C, MMM. Mega-caps across financials, energy, consumer staples, healthcare, telecom, and one industrial. Median trailing P/E around 13x, average dividend yield around 3.4%.

Growth side (15 names): AAPL, MSFT, NVDA, GOOGL, AMZN, META, TSLA, AVGO, CRM, ADBE, NFLX, ORCL, AMD, NOW, UBER. Concentrated in technology and communication services, with a handful of consumer discretionary and industrials. Median trailing P/E around 38x, average revenue growth around 18%.

Each row shows price, trailing P/E, forward P/E, price-to-book, dividend yield, ROIC, operating margin, revenue growth, beta, and sector. Conditional formatting paints each numeric column with a three-color scale tuned to that metric's interpretation (lower P/E is green, higher dividend yield is green, higher ROIC is green, and so on). Beta and revenue growth get data bars so magnitude is obvious at a glance.

The point of these tickers is not "buy these." The point is they are well-known representative names that anchor each factor. Replace them with your own portfolio in the custom watchlist inputs and the dashboard updates instantly.

MarketXLS Formulas Powering the Workbook

Every metric in the dashboard maps to a MarketXLS function. Here is the working list, all verified against the function catalog before being used in the build:

=QM_Last("AAPL")                            Current pending last price
=PERatio("AAPL")                            Trailing P/E ratio
=ForwardPE("AAPL")                          Forward P/E (consensus NTM)
=PriceToBook("AAPL")                        Price-to-book ratio
=PriceToSales("AAPL")                       Price-to-sales ratio
=PEGRatio("AAPL")                           PEG ratio TTM
=EnterpriseValueToEBITDA("AAPL")            EV / EBITDA multiple
=DividendYield("AAPL")                      Trailing dividend yield
=ReturnOnEquity("AAPL")                     ROE last 12 months
=ReturnOnInvestedCapitalOneYear("AAPL")     ROIC last 12 months
=OperatingMargin("AAPL")                    Operating margin
=RevenueGrowth("AAPL")                      Annual revenue growth
=QuarterlyRevenueGrowthYOY("AAPL")          Revenue growth YoY
=QuarterlyEarningsGrowthYOY("AAPL")         EPS growth YoY
=Beta("AAPL")                               Beta vs S&P 500
=Sector("AAPL")                             Sector classification
=MarketCapitalization("AAPL")               Market cap
=QM_GetHistory("AAPL")                      Historical price series

The reason this matters: every cell in the live template version uses these formulas rather than hardcoded values. When you open the workbook tomorrow, the prices and the spreads have updated. When the next earnings season prints, the forward P/Es shift. The dashboard you saved last quarter is still the dashboard you opened today, but with fresh data.

The sample workbook ships with the values pre-filled (so it works without the MarketXLS add-in installed), but every data cell has a comment showing the underlying formula. Hover over any number to see exactly what would produce it.

The Inputs Sheet: One Place to Change Everything

A dashboard is only as useful as the inputs that feed it. The Inputs sheet centralizes every assumption so the rest of the workbook stays in sync:

• Portfolio Size - dollar amount to allocate. Drives every dollar figure downstream.
• Risk Tier - Conservative / Base / Aggressive dropdown. In Conservative mode the value tilt nudges up by ten percentage points; in Aggressive mode it nudges down by ten.
• Rotation Horizon - how many months you expect the factor regime to persist. Drives the rebalance cadence default.
• Value Tilt % - target allocation to the value basket.
• Growth Tilt % - target allocation to the growth basket.
• Max Single-Name Weight % - position cap. The Portfolio sheet enforces this on each ticker.
• Stop-Loss % - drawdown trigger for full rebalance.
• Take-Profit % - return trigger for partial gain-locking.
• Benchmark - S&P 500 by default; other choices include Russell 1000 Value, Russell 1000 Growth, MSCI World, and Equal Weight S&P.
• Rebalance Frequency - Monthly, Quarterly, Semi-Annual, or Annual dropdown.

Every other sheet references these cells. Change the portfolio size from $250,000 to $1,000,000 and the per-name dollar allocations on the Portfolio sheet update automatically. Change the value tilt from 60% to 40% and the strategy legs flip weight without you touching any other cell. That is the entire point of an inputs sheet, and the workbook treats it that way.

Scenario Analysis: The Five Regimes That Matter

The Scenario Analysis sheet is where the workbook earns its keep for an advisor. It is one thing to read the current dashboard; it is another to think structurally about how value and growth behave across regimes.

The five scenarios baked into the sheet:

Rate Cut Cycle. Historically supports growth modestly (lower discount rates raise long-duration equity valuations) but value has caught up late in cycles when the cut path turns out shallower than expected. The dashboard's base assumption: growth +14.8%, value +8.5% over twelve forward months.

Rate Hike Cycle. Reverses the discount-rate effect. Growth multiples compress; value's lower duration and higher current cash flows look relatively more attractive. Base assumption: value +4.2%, growth -2.3%.

Stagflation. The hardest regime for both factors. Value tends to lose less because pricing power and dividend income offer some protection; growth loses more because earnings revisions turn negative on top of multiple compression. Base assumption: value +6.8%, growth -5.4%. Confidence on this regime is the highest of the five (5/5) because the historical pattern has been very consistent.

Soft Landing. The Goldilocks scenario. Inflation cools without breaking growth. Both factors do well, with a slight edge to value off the depressed starting valuation. Base assumption: value +11.2%, growth +16.4%.

AI Capex Boom. The continuation of the last eighteen months: hyperscaler spending, semiconductor demand, software platform monetization. Growth crushes value. Base assumption: value +3.4%, growth +22.7%. The dashboard's risk warning here: the basket-level multiple in growth is already pricing significant continuation, so the asymmetry favors disappointment.

The sheet uses red-amber-green color scaling on the spread row so the regime tilt is immediate. Icon sets on the confidence column let the user see at a glance which of the five regime calls is highest-conviction.

A reminder repeated everywhere in the workbook: these are educational ranges, not forecasts. The point of the scenario matrix is to force the user to ask "which of these five am I implicitly betting on" before changing the value tilt.

The Strategy Sheet: From Dashboard to Portfolio

The Strategy sheet translates the regime read into a pair-trade-style allocation. Two long legs (long value, long growth) sized per the input tilts, plus an optional hedge leg using a growth ETF on the short side for users who want a more market-neutral construction.

Each leg has entry trigger, exit trigger, profit target, and stop-loss columns. The entry trigger for both long legs in the default configuration is "P/E spread > 12x" - meaning the trade is most attractive when the gap between basket-level multiples blows out. The exit trigger is "spread < 6x" - signaling mean reversion has played out enough to lock gains and reassess.

The capital calculations at the top of the sheet are straightforward arithmetic against the Inputs sheet:

Capital to Value Basket  = Portfolio Size * Value Tilt %
Capital to Growth Basket = Portfolio Size * Growth Tilt %
Net Long Exposure        = Capital to Value Basket + Capital to Growth Basket

Change the input and every downstream number flexes. The strategy table is meant to be a teaching tool for thinking about pair construction, not a recommendation. The disclaimer block at the bottom of the sheet is explicit on that point.

Portfolio and Allocation Mechanics

The Portfolio sheet is where the dashboard becomes operational. It shows the basket-level capital block at the top (value basket capital, growth basket capital, cash reserve), a pie chart of that allocation, and a per-name table that takes each ticker, applies an equal weight within its basket, and produces a dollar allocation and a share count.

In the template version, the share count cell is =E[row]/QM_Last("[ticker]"). As the live price moves, the share count updates. That is how a dashboard-grade template differs from a static spreadsheet: it teaches the user how to think about dynamic position sizing without making them rebuild the math.

Data bars on the weight and dollar columns make the size distribution obvious. A user scanning the page sees instantly whether any one name is approaching the max-single-name cap.

Comparison: The Spread Story in One Page

The Comparison sheet is the simplest sheet in the workbook and one of the most useful. Eight metric rows. Value basket average. Growth basket average. Spread. Winner. Magnitude.

The winner column uses a small IF formula that flips the comparison logic by metric: for P/E, P/B, and beta, lower is "better" (the value side wins); for ROIC, operating margin, revenue growth, and dividend yield, higher is "better." So a single glance tells you which side wins on each metric and by how much.

The magnitude column expresses the spread as a percentage of the value-side average. That normalization matters because a 5-turn spread on a P/E of 12 is materially different from a 5-turn spread on a P/E of 40. A column chart embedded next to the table renders the side-by-side bars so the dispersion is visual.

This is also the sheet that scales well into a client conversation. If a client asks "why are you tilting toward value right now," you point at the Comparison sheet, walk down the metrics, and let the heatmap do the talking.

Historical Performance: Twelve Months of Context

The Historical Performance sheet is the temporal counterweight to the snapshot-focused Dashboard. Twelve months of indexed value vs growth performance, normalized to 100 at the start of the window, with month-over-month returns and the spread between them per period.

A line chart sits next to the table so the cumulative gap is immediately visible. The bottom of the sheet adds three summary rows: value's total return over the window, growth's total return, and the spread.

In the live template version, the data feed for this sheet uses QM_GetHistory against two index proxies (IVE for value, IVW for growth). The user can swap those tickers for any other pair (small-cap value vs small-cap growth, sector-specific factor ETFs, custom-built baskets) and the chart regenerates.

Methodology: How the Sausage Is Made

Premium templates earn their premium status partly through transparency. The Methodology sheet is the documentation page. It walks through:

• How the baskets are constructed - fifteen value-leaning names selected for below-median multiples, fifteen growth-leaning names selected for above-median revenue growth.
• Which MarketXLS functions drive each metric - mapped one-to-one.
• The assumptions behind the scenario tilts - acknowledged as ranges, not point forecasts.
• The limitations - static basket membership, equal weighting within each basket, no transaction costs modeled.
• Data refresh cadence - on-open and on-demand for the template; static for the sample with formula comments showing what the live version would produce.

For an advisor who has to defend a template to a client or a compliance reviewer, the Methodology page is the part that does the heavy lifting.

How to Use This Template With Your Own Portfolio

The default thirty tickers in the screener cover roughly $25 trillion in market cap and are well-known representatives of each factor. Most advisors will not use them as-is. Here is the workflow for adapting the workbook to your own positions:

1. Open the Inputs sheet and update the portfolio size, risk tier, and tilts to match your mandate.
2. In the custom watchlist section, add up to five additional tickers you want to track. The cells are pre-formatted with the yellow input style and link automatically to a watch table.
3. On the Dashboard sheet, you can replace any of the thirty default tickers with your own holdings. Edit column A in the screener block and every formula in that row regenerates.
4. Use the Scenario Analysis sheet as a discussion checklist with your investment committee. Ask: which scenario are we implicitly tilting toward, and what would make us change our mind?
5. Rebalance per the cadence set in the Inputs sheet. The Strategy sheet's entry / exit triggers give you a structured criterion.

The whole workbook flows from the Inputs sheet, so adapting it to a different mandate (more conservative, larger portfolio, different benchmark) is a five-minute exercise. Everything downstream propagates.

A Word on Factor Investing as Discipline, Not Doctrine

The value vs growth conversation invites strong opinions, and the dashboard is not designed to take a side. It is designed to make the conversation more disciplined.

The two strongest claims in factor investing - "value always wins long term" and "growth has structurally changed in the era of platform economics" - are both partially right and both incomplete. The historical record shows long stretches where each side dominates, mean-reversion cycles that sometimes take five years to play out, and macro regimes where the relationship breaks entirely.

A dashboard does not solve that. What a dashboard does is shorten the time between "the regime might be changing" and "I noticed it changed." That is enough.

FAQ

What is the difference between the value vs growth dashboard sample and the template?

The sample workbook ships with static values filled in across all thirty tickers as of the data-as-of date on the cover, so it works without any add-in installed. Every data cell carries a comment showing the live MarketXLS formula that would produce it. The template workbook uses live MarketXLS formulas in every data cell, so prices, multiples, and spreads update on open. Both have identical dashboard design.

Can I add my own tickers to the value vs growth dashboard?

Yes. The Inputs sheet has a custom watchlist section with five yellow input cells. Add a ticker and the workbook treats it as part of your watch list. To replace the default thirty in the main screener, edit column A of the screener block in the Dashboard sheet; every row's formulas regenerate against the new ticker automatically.

Why is the growth basket P/E so much higher than the value basket P/E in this dashboard?

The growth basket concentrates in technology and communication services mega-caps where current trailing earnings are still small relative to expected future earnings, so trailing P/E ratios look high. The value basket concentrates in financials, energy, staples, and healthcare where earnings are more stable but growth expectations are lower. The spread is the headline observation - it is what you are tracking.

How often does the value vs growth dashboard update?

The template version uses MarketXLS formulas that refresh on workbook open and via the standard refresh-all command in Excel. Prices, multiples, dividend yields, and growth metrics all pull from the MarketXLS data feed. The sample version is a static snapshot.

Which Excel version do I need to run the value vs growth dashboard?

The workbook is built with openpyxl and uses standard Excel features - conditional formatting, data validation, embedded charts, KPI tile-style merged cells. It opens cleanly in Excel 2016 and later, Excel for Microsoft 365, and Excel for Mac. The live template version requires the MarketXLS add-in for the formulas to compute; without the add-in the cells show as #NAME errors.

Is the value vs growth dashboard a backtest or a forward-looking tool?

Neither, strictly speaking. The Historical Performance sheet shows twelve months of indexed performance, which gives context. The Scenario Analysis sheet projects illustrative ranges across five macro regimes, which is forward-looking but explicitly educational, not predictive. The Dashboard itself is a current-state monitoring tool - it tells you where the factor spread sits right now and how the constituents stack up.

Can I use the value vs growth dashboard for international stocks?

The default tickers are US large-caps because that is where the MarketXLS coverage is deepest and where the factor index history is cleanest. The formulas themselves work on any covered ticker, so you can swap in international names. Expect some data-availability gaps on smaller international stocks.

The Bottom Line

A value vs growth dashboard exists to compress a complicated factor question into a glanceable view. The workbook in this post does that with KPI tiles, a thirty-name screener, scenario analysis, allocation mechanics, and twelve months of indexed history - all driven by verified MarketXLS formulas that keep the data current.

The point is not to take a side in the value vs growth debate. The point is to monitor the spread with enough rigor that you notice when it changes. Build the dashboard once, set your inputs, and check it at every rebalance window.

Download the templates:

• - pre-filled snapshot, formula comments on every cell
• - dashboard-grade workbook with live data

To see how MarketXLS turns Excel into a full institutional-grade equity research platform, visit marketxls.com or book a demo. For more dashboard-style workbooks like this one, browse the recent magnificent 7 valuation dashboard, the sector valuation heatmap, and the equity risk premium dashboard.

This article and the accompanying workbook are educational only and are not investment advice. Past performance is not indicative of future results. Always consult a licensed financial advisor before making investment decisions.