Q2 Bank Earnings Preview Excel 2026: Net Interest Margin Watchlist For July Reports

Q2 bank earnings preview excel is one of the most useful research files an advisor or self-directed investor can build right now, because the July 2026 reporting window is about to compress an enormous amount of information about the US economy into a two week stretch. JPMorgan, Wells Fargo, Citigroup, Bank of America, Goldman Sachs, Morgan Stanley, and a long list of super-regionals and custody banks all report inside that window. This guide explains how to organize that prep work in Excel using live MarketXLS formulas, walks through the key things to watch in net interest margin, deposit costs, loan loss provisions, and capital ratios, and gives you a downloadable workbook to run the same workflow yourself.

The setup heading into the Q2 2026 bank reporting window is unusually rich. Markets are weighing a Federal Reserve that has been on extended pause, a yield curve that has spent most of the last quarter oscillating around steepening attempts, deposit costs that have started to plateau at most large institutions, and renewed scrutiny on commercial real estate inside regional loan books. That backdrop is exactly the kind of environment where a structured, formula-driven Excel template earns its keep. A good preview file does not try to predict the quarter. It helps you ask better questions, in the same way every quarter, so the noise of earnings week becomes signal you can actually act on.

This post walks through the structure of that file, the MarketXLS formulas that make it live, the questions to ask for each bank group, and how the downloadable template translates inputs like portfolio size and risk tolerance into a concrete watchlist. It is built for advisors, wealth managers, and serious individual investors who want a workflow they can rerun every quarter without rebuilding the wheel.

Why a Q2 bank earnings preview excel matters in 2026

Bank earnings act like a live stress test for the broader market narrative. When the Fed is on pause and the path of policy is debated quarter by quarter, large banks sit at the center of several open questions:

1. Are deposit costs still rising, or have they flattened enough to stabilize net interest margins?
2. Is loan growth holding up, or are commercial and consumer credit demand softening?
3. Are reserve builds and provision expense signaling a tougher consumer or commercial real estate outlook?
4. Are capital markets businesses (M&A, equity capital markets, debt issuance, trading) improving enough to offset pressure in core lending?
5. Are valuations already discounting too much bad news, or not enough?

The Q2 2026 reporting season is interesting because each of those five questions has gone unanswered for a quarter. Q1 results came in better than many bears expected, but the Fed kept policy steady afterward and the yield curve did not move decisively in either direction. That means the Q2 results may be the cleaner signal of whether net interest margin pressure is easing on a structural basis or simply by accident of timing.

A Q2 bank earnings preview excel file lets you sit with that uncertainty and structure it. Instead of reacting to one bank's release after market close, you walk into the week with a watchlist, a scoring system, a clear sense of what each bank is being valued on, and a written sense of what a beat or a miss would mean.

That is what this template is built to do.

What's inside the workbook

The downloadable workbook has six sheets, each built around a different research question. Every sheet has a "MarketXLS Functions Used" section at the bottom so you know exactly which formulas power the data and how to extend them to your own watchlist.

1. How To Use

A short tutorial sheet that walks through every workflow step from setting inputs to reading the correlation matrix. It also lists the MarketXLS formulas used in every sheet so users can extend the template to their own watchlist without guessing at function names.

2. Main Dashboard

The Main Dashboard is the front door. It holds the input cells (portfolio size, bank sleeve weight, risk tolerance, max position per bank, and a look-ahead window in days), then a watchlist of 18 major US banks across money center, capital markets, super regional, regional, and custody groups. For each bank, it shows:

• Expected reporting date
• Live price (via =QM_Last(ticker))
• Q2 EPS estimate (via =EPSESTIMATECURRENTQUARTER(ticker))
• Q2 prior year EPS (for the year over year comparison)
• Forward P/E (via =ForwardPE(ticker))
• Price to book (via =PriceToBook(ticker))
• Dividend yield (via =DividendYield(ticker))
• Options-implied 1-day move (sourced from the Options sheet)
• Market capitalization
• A composite score combining EPS growth versus the year ago quarter, dividend yield, forward P/E discount, and price to book discount

The score is not investment advice. It is a sort key. It lets you reorder the watchlist by something other than market cap so the cheap, higher yielding banks with positive estimate revisions float to the top of the table.

3. NIM and Profitability

This sheet zooms in on the operating model. For each bank it shows:

• Last reported net interest margin (NIM)
• Change versus the prior quarter in basis points
• Return on equity (via =HF_ROE(ticker) or =ReturnOnEquity(ticker))
• CET1 capital ratio
• Q1 2026 EPS surprise percent
• A "bank health" label that flags Strong, Neutral, or Watch based on a simple rule (positive NIM trend, ROE at or above 10 percent, CET1 at or above 10 percent equals Strong)

The point of this sheet is to separate banks where the operating story is improving from banks where the operating story is deteriorating, before the earnings prints rather than after.

4. Options-Implied Moves

This is the pre-earnings sheet. For each bank you build the at-the-money straddle that expires immediately after the reporting date and back out the implied 1-day move from:

Implied move % ≈ (ATM call price + ATM put price) / spot price

The sheet shows spot price, the chosen ATM strike, the implied move in percent, a bull case at spot times one plus the implied move, a bear case at spot times one minus the implied move, and the Q1 2026 EPS surprise percent for context. Comparing the implied move to the bank's historical surprise pattern is one of the more useful pre-earnings reads you can do in a few minutes.

The MarketXLS formulas you need here are =QM_Last(ticker), =QM_GetOptionChainActive(ticker), =QM_STREAM_OPTIONIMPLIEDVOLATILITY(...) for the live IV on each contract, and =EARNINGS_DATE(ticker) to pick the right weekly expiration.

5. Portfolio Allocation

This sheet is where the inputs from the dashboard turn into dollars and shares. It pulls portfolio size, bank sleeve percentage, and max position percentage from the dashboard, computes the bank sleeve in dollars, then for each name calculates an equal-weight dollar allocation, the maximum dollar position implied by your max position rule, and how many shares that translates into at the live price.

The intent is to keep position sizing rule-based, not vibes-based. Especially during earnings weeks, it is easy to chase the name with the biggest implied move. The portfolio sheet keeps the discipline in front of you.

6. Correlation and Beta

The last sheet shows, for each bank, beta versus the S&P 500 and 90 day return correlations versus three benchmarks:

• XLF (broad financial sector ETF)
• KRE (regional bank ETF)
• SPY (broad market)

The read is straightforward. When a bank's correlation with KRE is consistently very high (above 0.85), it is mostly trading as a regional bank rate proxy. When the correlation is much higher with XLF and SPY, the bank is trading more on its capital markets and fee mix exposure than on regional credit. Money center banks tend to sit between those two profiles.

That distinction is useful because it tells you which macro variable you should care about when you watch the print. For a regional name, the post-earnings move is often driven by the deposit and CRE update. For a money center, the trading and investment banking commentary tends to swing the tape more.

The big questions for each bank group in Q2 2026

A good Q2 bank earnings preview excel template does the table work for you. The reading is on you. Here is how to think about each group as the reports start landing.

Money center banks (JPM, WFC, C, BAC)

The single most important data point for this group is the net interest income trajectory. Deposit costs have been the swing variable for the last several quarters. The market is watching for:

• Whether deposit beta is finally rolling over from the highs of the tightening cycle
• Whether non-interest-bearing deposit mix is stabilizing or still leaking to higher cost alternatives
• Whether loan growth is positive year over year, particularly in commercial and industrial books
• Whether commercial real estate provisions are flat or stepping up materially from Q1

Card and payments commentary from JPM and BAC is also a clean read on the US consumer. If credit losses on card portfolios are stable rather than rising, that is a constructive signal for the broader consumer discretionary thesis going into Q3.

Capital markets and custody (GS, MS, BK, STT, NTRS)

For Goldman Sachs and Morgan Stanley, the question is different. Net interest income matters less. What matters is:

• Investment banking advisory and underwriting fee trajectory (did the Q2 deal calendar translate into actual revenue)
• Equity and fixed income trading revenue compared to a year ago
• Wealth management asset and revenue growth (especially Morgan Stanley)
• Operating leverage as the firm grows asset management and wealth fees

For custody banks (BK, STT, NTRS), the watchlist is fee revenue tied to global asset prices, securities lending revenue, NIM on the small balance sheet, and capital return. These are not pure rate plays. They behave more like fee operating businesses with a rates kicker.

Super regionals and regionals (USB, PNC, TFC, MTB, FITB, HBAN, RF, KEY, CFG)

This is the group with the most differentiation in 2026. Every one of these banks has a different commercial real estate footprint, deposit mix, and securities portfolio. Things to flag for each name on the dashboard:

• NIM trend (the headline number, but also the components - asset yields versus deposit costs)
• Office CRE exposure as a percentage of total loans
• Reserve coverage on CRE
• Tangible book value per share growth (proxies for capital generation after dividends)
• Buyback pace versus dividend - some regionals will lean harder on buybacks if their stock is trading at a discount to book

The Q1 2026 numbers gave the regionals more credit than was widely expected. Q2 is the chance to confirm whether that was a one quarter improvement or the beginning of a real recovery.

Building the dashboard in Excel - real formulas

The template is built so you can copy the structure to your own watchlist with minimal editing. Here are the formulas the workbook actually uses, verified against the MarketXLS function library.

Pricing and valuation block

=QM_Last("JPM")                            // live last price
=Last("JPM")                               // snapshot last (alias)
=ForwardPE("JPM")                          // forward P/E using next 12 month consensus
=PriceToBook("JPM")                        // trailing P/B
=BookValuePerShare("JPM")                  // book value per share
=DividendYield("JPM")                      // annual dividend yield percent
=DividendPerShare("JPM")                   // trailing dividend per share
=MarketCapitalization("JPM")               // market capitalization

Earnings block

=EARNINGS_DATE("JPM")                      // next expected earnings date
=PREVIOUSEARNINGSREPORTDATE("JPM")         // most recently reported date
=EPSESTIMATECURRENTQUARTER("JPM")          // Q2 2026 consensus EPS
=EPSESTIMATENEXTQUARTER("JPM")             // Q3 2026 consensus EPS
=EPSESTIMATECURRENTYEAR("JPM")             // FY 2026 consensus EPS
=EPSESTIMATENEXTYEAR("JPM")                // FY 2027 consensus EPS
=EarningsPerShare("JPM")                   // trailing twelve month reported EPS

Profitability and growth block

=HF_ROE("JPM")                             // return on equity (high-frequency feed)
=ReturnOnEquity("JPM")                     // trailing ROE
=QUARTERLYREVENUEGROWTHYOY("JPM")          // revenue growth year over year
=QUARTERLYEARNINGSGROWTHYOY("JPM")         // earnings growth year over year
=Revenue("JPM")                            // trailing revenue
=Sector("JPM")                             // sector classification

Options block (for the implied move sheet)

=QM_GetOptionChainActive("JPM")            // live option chain
=QM_STREAM_OPTIONIMPLIEDVOLATILITY("JPM"...)  // streaming implied vol on a contract
=OPT_OPENINTEREST("JPM"...)                // option open interest

Correlation block

=Beta("JPM")                               // beta versus the S&P 500
=StockReturnCorrelation("JPM","XLF",90)    // 90-day correlation vs XLF
=StockReturnCorrelation("JPM","KRE",90)    // 90-day correlation vs KRE
=StockReturnCorrelation("JPM","SPY",90)    // 90-day correlation vs SPY

This is the entire stack you need to rebuild every sheet in the workbook from scratch. You can also use these formulas to extend the watchlist beyond the 18 names already covered - the template is structured so adding a row at the bottom just requires the ticker.

A simple scoring framework

The Main Dashboard uses a transparent composite score so the watchlist can be sorted by something more interesting than alphabetical order. The formula adds four components:

1. EPS growth versus the year ago quarter, weighted 40
2. Dividend yield in percent, weighted 4
3. Forward P/E discount versus 18 (capped at zero from below), weighted 1.2
4. Price to book discount versus 3 (capped at zero from below), weighted 5

A bank that is showing positive EPS growth, paying a healthy dividend, trading at a forward P/E under 18, and trading at less than three times book scores higher. A bank that is shrinking EPS, low yield, premium multiple, and well above book scores lower.

This is deliberately simple. The scoring is not a buy recommendation. It is a sort key designed to focus attention. The fact that USB, TFC, and CFG screen well today does not mean they will outperform after earnings. It means they are the names where the gap between price and the metrics you tracked is widest. That is a useful prompt for a deeper look at deposit beta, CRE exposure, and management guidance for the back half.

How to read the options-implied moves

The implied move math is straightforward but the interpretation deserves care.

When the at-the-money straddle on a bank expiring just after earnings is priced at, say, 4 percent of the stock, the options market is saying it expects roughly a 4 percent absolute move in the first session after the report. There is a 68 percent chance the actual close is inside that band, roughly speaking, since the straddle pricing is a one standard deviation estimate.

Three useful comparisons:

• Implied move versus the average absolute move over the bank's last eight earnings reports
• Implied move versus the Q1 2026 surprise percentage
• Implied move versus the broad market 1-day implied move for the same date (use SPY or XLF straddles as a benchmark)

A bank whose implied move is materially above its historical realized move is one the market is bracing for. That can be a setup for an implied volatility crush trade for option sellers, or it can be a red flag if your fundamental work is already cautious. A bank whose implied move is at or below its historical realized move can be an interesting setup for option buyers who think the print is going to be more eventful than the market expects.

None of those are recommendations. They are reads. The template gives you the inputs in one place so the read is fast.

Connecting the workbook to your portfolio

The Portfolio Allocation sheet is where the workbook stops being a research file and starts being a planning file. The inputs flow directly from the Main Dashboard:

• Portfolio size becomes the denominator for every percentage based rule
• Bank sleeve weight defines how much capital the bank sleeve can hold in dollars
• Max position per bank caps any single name as a percentage of the portfolio
• Equal-weight allocation gives you a baseline distribution

The shares column uses the live price (=QM_Last(ticker)) so a 4 percent target position translates immediately into a round share count. The notes column lets you flag higher liquidity tier names (typically JPM, BAC, GS) if you want to weight them differently than smaller regionals.

The point of having the allocation sheet linked to the dashboard inputs is simple. When you change the bank sleeve from 12 percent to 18 percent, every dollar figure on the portfolio sheet updates. When you raise the max position from 3 percent to 5 percent, the cap on each name updates. There is no manual reconciliation.

What this template is not

A Q2 bank earnings preview excel template is not a forecasting model. It does not pretend to know whether JPM will beat or miss the quarter. It does not pretend that NIM will expand or contract. It does not generate buy or sell signals.

What it does is organize the inputs that matter, in one place, with the formulas that pull them in automatically, so you walk into earnings week with a structured view rather than a flurry of headlines.

That is the difference between a research workbook and a feed.

Download the templates

Both files are linked below. The static sample file is filled with illustrative numbers from June 14 2026 so you can see the structure end to end without any add-in. The live MarketXLS template version is the formula-driven version - prices, valuations, dividend yields, beta, and correlations update every time you open the file.

Download the templates:

• - Pre-filled with illustrative data so you can see every sheet without an add-in
• - Live-updating workbook driven entirely by MarketXLS formulas

Both files include the same six sheets, the same scoring system, the same portfolio allocation math, and the same MarketXLS Functions Used section at the bottom of every sheet so you can extend the workbook to your own watchlist.

Frequently asked questions

When does Q2 2026 bank earnings season start?

The unofficial start is mid-July, typically the second full week. JPMorgan, Wells Fargo, and Citigroup usually report on the Tuesday of that week, with Bank of America, Goldman Sachs, and the custody banks following on Wednesday and Thursday. The regionals fill out the following week. Your Q2 bank earnings preview excel workbook should be set up by the first week of July so the watchlist is locked in before the calendar gets busy.

How do I track net interest margin in Excel?

Net interest margin is not always a single MarketXLS function because the precise definition varies bank by bank. What works well is to pull the reported NIM from each bank's most recent earnings press release or 10-Q, type it into the NIM and Profitability sheet, and use =HF_INTEREST_INCOME(ticker) and =HF_DEPOSIT_LIABILITIES(ticker) as cross-checks on the underlying balance sheet items. Then you have a reported NIM plus the components driving it, in one place, in a format that is easy to update next quarter.

Which bank stocks have the highest options-implied moves in Q2 2026?

The implied move depends on the option chain at the time you look, so the answer changes as you approach the earnings date. Generally, regionals with high CRE exposure (KEY, HBAN, RF, FITB) and second-tier money centers (C, WFC) tend to trade with higher implied moves than the largest, most liquid names like JPM and BAC. The Options-Implied Moves sheet in the workbook gives you a one place read so you can compare across the watchlist.

Can I use this template for Q3 or Q4 earnings?

Yes. The structure is quarter-agnostic. The dashboard sorts on expected report dates, the EPS estimate formula reads the current quarter consensus, and the dividend, NIM, and correlation sheets do not care which quarter you are previewing. When Q3 reporting season comes, the same workbook becomes a Q3 preview by virtue of MarketXLS updating the live data.

What is CET1 and why does it matter for bank earnings?

CET1 is the Common Equity Tier 1 capital ratio. It measures a bank's core capital against its risk weighted assets. In the US, the largest banks operate well above regulatory minimums, but the absolute level and the trajectory matter because they determine how much capital is available for dividends and buybacks and how much room a bank has to absorb a credit cycle. Tracking CET1 alongside NIM and ROE in a Q2 bank earnings preview excel template gives you a fuller read than looking at EPS in isolation.

How is this different from a generic bank dashboard?

A generic bank dashboard tracks current prices and valuation. A Q2 bank earnings preview excel template is built for a specific reporting window. It groups names by reporting day, includes a pre-earnings options-implied move read, tracks Q1 2026 surprise as context, and ties the watchlist to your portfolio sizing inputs. The shelf life is one reporting season, but it can be reused every quarter.

The bottom line

Q2 2026 bank earnings are landing into one of the more interesting setups in recent years. The Fed is on extended pause, the yield curve has been indecisive, deposit costs are stabilizing at most large institutions, and commercial real estate is the wildcard in regional loan books. The right way to prep is not to predict the prints. It is to build a structured watchlist, plug in live data, define a scoring rule that you can defend, and walk into the week with a written sense of what beats and misses would actually mean.

That is the entire point of the Q2 Bank Earnings Preview Excel template. It uses MarketXLS formulas for every price, every consensus estimate, every valuation ratio, every dividend metric, and every correlation, so the workbook stays alive instead of going stale a few days after you build it. The downloads above give you both the static sample to inspect and the live formula version to use.

If you would like a walkthrough of how the formulas power each sheet, or how to extend the watchlist to your own list of bank stocks, you can book a demo and the team will walk through it with you. For more on the underlying functions, see the MarketXLS function reference and the related bank earnings tracker and net interest margin tracker posts from the Q1 cycle.

Disclaimer: this article is for educational purposes only. It is not a recommendation to buy or sell any security. Past results do not guarantee future returns. Always do your own research and consult a licensed financial advisor before making investment decisions.