As always, Calcbench is on the case. 

Let’s start with Microsoft ($MSFT), which has been investing in OpenAI for years, primarily via cloud computing resources Microsoft provides to the generative AI startup. In its quarterly report from Oct. 29, Microsoft reported a $4.1 billion loss from those investments, up from a $688 million loss in the year-earlier period. See Figure 1, below.

We were intrigued. If Microsoft is reporting a $4.1 billion loss on OpenAI today and a $688 million loss one year ago, what other losses has it disclosed related to OpenAI in the past? 

Alas, we can’t really tell. Microsoft only started reporting OpenAI-specific disclosures one year ago, at the start of its fiscal 2025; that’s the $688 million loss, reported under the “Other Income, Net” line item. Prior to that period, Microsoft didn’t mention OpenAI losses at all.

Even starting in Q1 2025, however, Microsoft described the OpenAI losses in rather vague terms. Microsoft reported an Other Income loss in that period of $683 million, “primarily reflect[ing] net recognized losses on equity method investments, including OpenAI.” 

The word “primarily” is doing a lot of work in that sentence. Investors at that point in time didn’t know whether “primarily” meant almost all of the $683 million loss, or 51 percent of it, or something in between. Only now, one year later, can we see that “primarily” meant essentially all of the Other Income net losses that quarter. 

If we chart Microsoft’s Other Income losses from Q1 2025 (when we get the first mention of OpenAI’s relevance to that line item) forward, we get Figure 2, below.

Again, we don’t know precisely how much OpenAI was responsible for those losses throughout the first four fiscal periods, but clearly it was a lot — and then losses soared in this most recent quarter, to the point where Microsoft started disclosing exact numbers. 

What Else Microsoft Is Saying

We also used the text search feature in our Disclosures & Footnotes Query page to see what else Microsoft has said about its exposure to OpenAI. Tucked away in the Management Discussion & Analysis of last week’s 10-Q we found this (emphasis added by us):

Current year net income and diluted EPS were negatively impacted by net losses from investments in OpenAI, which resulted in a decrease in net income and diluted EPS of $3.1 billion and $0.41, respectively. Prior year net income and diluted EPS were negatively impacted by net losses from investments in OpenAI, which resulted in a decrease in net income and diluted EPS of $523 million and $0.07, respectively.

Umm, wow. Microsoft’s total diluted EPS for its most recent period was $3.72 — so if the company didn’t have that OpenAI loss, diluted EPS would’ve been 11 percent higher. 

Even more interesting is that OpenAI losses went from a $0.07 drag on EPS one year ago to a $0.41 drag today, a six-fold increase. By comparison, total EPS rose only 12.7 percent (from $3.30 EPS one year ago to $3.72 EPS now.) 

So those OpenAI losses are growing, and growing so fast that Microsoft has decided to start reporting them; which means Microsoft believes the OpenAI relationship is material to investors. Going forward, presumably Microsoft will keep disclosing those OpenAI losses — or, in theory, any OpenAI profits, if the company ever starts making money. 

Either way, it’s a useful glimpse into the state of OpenAI and its relationship to Microsoft. You just need to know where to look, and have the right tool to help you translate data into insight.

Debt instruments can have a huge effect on stockholder equity and EPS, depending on the precise nature of the debt that a company issues. Today let’s look at two examples of convertible debt, and how companies try to manage its attendant EPS implications, from the technology firms Snap ($SNAP) and Zillow ($Z). 

First, a refresher on how convertible debt works. Convertible debt is a financing instrument that combines elements of both debt and equity. While the interest rate on convertible bonds is generally lower than the rate on traditional bond instruments, investors gain the option to turn their debt holdings into company shares at some predetermined "conversion price" set in the terms of the debt agreement. 

For the shareholders, the downside of the conversion is dilution — because the conversion of debt into equity increases the number of shares outstanding, which therefore decreases the corresponding EPS.

One way to avoid that outcome is through a type of call option. A call option gives its holder the right (but not the obligation) to buy a specific stock or other asset at a predetermined price — commonly known as the “strike price” — within a set period of time. 

“Capped call” transactions are a hedging tool that convertible bond issuers often use to protect against shareholder dilution. When a company issues a convertible bond, it can buy call options on its own stock with a strike price equal to the bond's conversion price and a cap that limits the counterparty's exposure. 

A capped call transaction effectively raises the price point at which dilution begins, and that shields shareholders from having their ownership diluted until the shares trade well above the conversion price. The trade-off is cost: capped calls typically consume 7 to 9 percent of the debt proceeds upfront, as Calcbench explained in its previous piece using Uber’s ($UBER) $141 million hedge to illustrate. 

Importantly, capped calls involve separate transactions between the issuer of the convertible and third-party underwriters, subject to a separate agreement that lays out terms and conditions. But since capped calls are used to protect against conversion-related dilution, we typically expect the companies to unwind capped calls promptly once the convertible security is redeemed or expires upon maturity of the convertible. 

The logic here is simple: capped calls are costly, and unwinding them is a liquidity-positive event that generates cash inflow. So why pay for a hedge when the dilutive convertible instrument no longer exists? 

Example 1: Snap

In February and May 2024, Snap repurchased its 2025 convertible notes. Upon completion of the repurchase of convertibles in May 2024, Snap terminated its capped call transactions, recording a $62.7 million inflow from cash from financing. Snap disclosed the transaction as follows (emphasis added):

“Our financing activities for the six months ended June 30, 2024 primarily consisted of the Note Repurchases for $859.0 million, repurchases of our Class A common stock for $311.1 million, and the purchase of the 2030 Capped Call Transactions for $68.9 million, partially offset by the issuance of the 2030 Notes for net proceeds of $740.4 million and the termination of the 2025 Capped Call Transactions for proceeds of $62.7 million.”

But not every company reports a capped call transaction this way. Sometimes you find an outlier. Zillow seems to be such an exception.

Example 2: Zillow

In September 2019, Zillow issued a $500 million convertible note with maturity in 2026, a conversion price of $43.51, and the initial cap price of $80.575. The terms of the convertible and the capped call imply that Zillow purchased an anti-dilution hedge, which protects shareholders from dilution when the stock trades between $43.51 and $80.575. 

Put differently: the hedge effectively raises the dilution threshold to $80.575. On Sept. 27, 2019, Zillow’s stock closed at roughly $29.53, more than 30 percent below the initial conversion price. 

Five years later, in December 2024, Zillow redeemed its 2026 convertible note. In contrast to Snap, Zillow decided to keep the associated capped calls outstanding (again, emphasis added):

“In connection with settling our 2026 Notes in December 2024, we elected to keep the associated capped call transactions outstanding.”

The capped calls were terminated on Aug. 25, 2025, about eight months after the redemption of the convertible note:

“On August 25, 2025, Zillow Group, Inc. (the “Company”) will enter into agreements … to unwind and terminate certain capped call transactions by and between the Company and each Counterparty (such transactions, the “Capped Calls,” and the unwind and termination of the Capped Calls, the “Unwind Transactions”)... Upon settlement of the Unwind Transactions, the Company will have no remaining capped call transactions outstanding.

The Company expects to receive from the Counterparties an aggregate of 3.1 million shares of the Company’s Class C capital stock, which will reduce the Company's Class C capital stock outstanding, and $38.2 million in cash (the “Unwind Amount”), upon the Unwind Transactions. In connection with the Unwind Transactions, the Counterparties may buy or sell shares of the Company’s Class C capital stock in secondary market transactions and/or unwind various derivative transactions with respect to such Class C capital stock.”

Why did Zillow elect to delay the termination of capped calls? We don’t know. Recall, however, that the economics of the capped call transactions is a company buying a call option on its own stock. Buyers of the call options usually believe that the price of the underlying instrument is likely to increase, sending a bullish signal to the market.

One possible explanation is that Zillow's management believed that Zillow's stock price was likely to increase, and incorporated this belief into their decision not to terminate the calls. Zillow’s stock price closed at $76.6 on Dec. 24, 2024 — about 5 percent below the initial cap of $80.575. The stock closed around $88.80 on Aug. 25, 2025, an increase of 16 percent over the eight-month period. For comparison, the S&P 500 increased about 6.6 percent over the same period.

Let’s also remember that Zillow received both cash and shares as part of consideration received for unwinding the capped call transaction. Another possible explanation is that Zillow preferred to receive the shares — effectively reducing dilution — in 2025 rather than in 2024. 

Why would a company do that? Perhaps to match the timing of accretive capped calls unwinding with dilution related to the issuance of shares upon exercise of stock options. 

According to Zillow’s Q2 2025 filing, the company issued 1.32 million Class C shares upon exercise of stock options, 2.97 million shares upon vesting of RSUs, and repurchased 4.2 million Class A and 1.4 million Class C shares in the first half of 2025:

“During the six months ended June 30, 2025, we repurchased 4.2 million shares of Class A common stock and 1.4 million shares of Class C capital stock at an average price of $70.09 and $73.19 per share, respectively, for an aggregate purchase price of $297 million and $103 million, respectively.”

The company also reported the transaction in the following table:

For comparative purposes, during the first six months of 2024 Zillow repurchased 1.1 million of Class A stock and 5.996 million of Class C stock. So the 3.1 million of Class C capital stock received by Zillow in August 2025 as part of the consideration could have potentially reduced the buybacks needed to mitigate the dilutive effect of options issuances and RSUs vesting in 2025. 

Of course, there could also be other reasons besides stock price expectations and buyback considerations that we did not discuss here. But Zillow’s delay in unwinding the hedge looked unusual, certainly interesting enough to ponder a few ideas. 

For the readers interested in conducting similar research in their own companies that they follow, convertible debt, capped calls, and note hedges are all easy to find using Calcbench’s Interactive Disclosure and Multi-Company pages.

For example, we searched “capped call” in the 2024 disclosures of S&P 500 companies and found more than 75 results, including NRG Energy, Super Micro Computer, Las Vegas Sands, and more. From there you can conduct your own analysis much as we did here with Snap and Zillow.

Editor’s note: Olga Usvyatsky is an author of Deep Quarry newsletter and occasional contributor to the Calcbench blog. Usvyatsky enjoys raising interesting questions about financial disclosures, and can be reached at olga@deepquarry.com.

Then, as always, Calcbench squinted more closely at that $28.2 billion in pretax income. Only $17.4 billion of that number came from Amazon’s operating income; another $10.2 billion came from the ever-mysterious line item known as “Other” income. What was that about? 

So we dove into Amazon’s footnote disclosures, because you can do that in Calcbench thanks to our Tracing feature and our Disclosures & Footnotes Query page. Soon enough, we found this explanation on Page 30 of the 10-Q, tucked away in the Management Discussion & Analysis:

The net gain of $10.2 billion in Q3 2025 and $14.1 billion for the nine months ended September 30, 2025 is primarily from an upward adjustment for observable changes in price relating to our nonvoting preferred stock in Anthropic, and the reclassification adjustments for the gains on available-for-sale debt securities from the portions of our convertible notes investments in Anthropic that were converted to nonvoting preferred stock during Q3 2025 and for the nine months ended September 30, 2025.

In other words, more than one-third of Amazon’s pretax income for the quarter ($10.2 billion of the $28.2 billion total) comes from its holdings in AI darling Anthropic — a nonpublic company that reportedly doesn’t yet turn a profit.

Don’t get us wrong. Amazon still had $17.4 billion in operating income, and that’s not nothing. Moreover, even if Anthropic isn’t turning a profit, the company is growing like weeds along the Amazon River. Whatever Amazon’s equity or debt holdings in the AI might be, clearly those holdings are worth more today than they were three, six, or nine months ago. Regardless, that’s still a material amount of Amazon’s pretax income tied to financial engineering rather than people buying and selling stuff. 

So we got to wondering: Are any other companies enjoying similar bumps to the bottom line from “other” income?

Spoiler: the answer is yes.

Exploring Other Income

Researching this question was easy. We simply went to our Multi-Company search page and then looked up operating income and “Other non-operating income” for the S&P 500 to see what we’d find.

For Q3 2025 filings so far, we found 178 firms that filed both numbers. Then we expressed Other Income as a percentage of Operating Income, and sorted the answers from highest to lowest. Figure 1, below, shows the 10 firms with the largest Other Income amounts relative to Operating Income.

That’s the list; then you can use the Disclosures & Footnotes Query page to investigate specific companies and why they had such bumper crops of other income.

For example, AT&T ($T) reported $6.25 billion in other income for the quarter, more than all of the telecom giant’s operating income. Most of that $6.25 billion came from the sale of AT&T’s stake in DirecTV to a private equity group:

On July 2, 2025, we sold our interest in DIRECTV to TPG Capital (TPG) and recorded a current note receivable of approximately $3,600, which we expect to receive the majority of by the end of 2025, and a long-term receivable of $500. The disposition of DIRECTV also resulted in the release of approximately $2,900 of historical deferred tax liabilities. We recorded a gain on the sale of DIRECTV of approximately $5,500, which includes the impact of the transfer of deferred tax liabilities, indemnification liabilities and unfavorable contracts…

AT&T reported net income of $9.67 billion for the quarter. If not for that $5.5 billion booked thanks to the DirecTV sale, net income would’ve been less than half of that.

Another adventure in footnote disclosures is Honeywell International ($HON). The company reported $822 million in Other Income, compared to $1.75 billion in operating income. First we traced that $822 million to an Other Income footnote that Honeywell included in its Q3 filing, which included a table (see below) that said most of that Other Income number came from a settlement related to Resideo, a maker of home temperature and security controls that Honeywell spun out in 2018. 

The Other Income footnote directs people to look at the Commitments and Contingencies footnote for more detail about the Resideo issue. We went to that footnote. Long story short, the $802 million is a one-time payout from Resideo to Honeywell to end a long-term indemnification arrangement where Resideo had been paying Honeywell for the costs of environmental matters at old manufacturing sites. 

For the record: yes, Honeywell did report this one-time Other Income gain as an adjustment to net income. The company only reported the number as part of adjusted EPS, rather than adjusted earnings; but the adjustment is in there. 

We could keep going, and perhaps in future posts we will. Our point is simply that the impressive net income and pretax income numbers we’re seeing these days can often be driven by Other Income numbers. There’s nothing inherently wrong with that, but shrewd analysts will keep that question in mind as you assess the long-term earnings quality of the companies you follow. 

All the data is there; Calcbench just helps you find it.

The template, available to Calcbench subscribers on DropBox, tracks numerous airline-industry performance metrics — everything from revenue per available seat mile (RASM) to passenger revenue, load factor, average fuel cost, and more.

We track six U.S. airlines:

• Alaska Airlines ($ALK)

• American Airlines ($AAL)

• Delta Air Lines ($DAL)

• Jet Blue ($JBLU)

• Southwest Air ($LUV)

• United Airlines ($UAL)

Figure 1, below, tracks their quarterly EPS (along the bottom) and quarterly RASM (along the top). 

Or for those of you who prefer to consume your financial data in table format, here’s the RASM data for the last five quarters in Figure 2, below.

Why did we include Q4 with a row of “N/A”? To remind you that our earnings templates automatically capture the latest data as firms file! So when the airlines start filing Q4 data in three months’ time, that information will be whisked from the filings to the templates within minutes, ready for your analysis.

Two caveats. First, for the template to populate updates automatically, you must be a premium-level Calcbench subscriber. If you want a Premium subscription or aren’t sure whether the subscription you have qualifies, email us at us@calcbench.com and we’ll get you squared away. 

Second, you must have the Calcbench Excel Add-in installed and running. 

Once you have those items done, the template will run automatically. Onward and upward!

All banks must set aside some portion of capital to cover loans they’ve extended which might subsequently default. Those are loan loss provisions, disclosed in absolute dollars. You can then calculate a bank’s loan loss ratio by dividing the loan loss provisions into total loans outstanding. 

That ratio gives investors a sense of how confident a bank is about its loan portfolio, and really about the economy overall. A declining loan loss ratio means banks aren’t as worried about the risk of default among their loan recipients; a rising one means the banks are.

So what does that picture look like today? We pulled the results for five major banks: Bank of America ($BAC), Citigroup ($C), JPMorgan Chase ($JPM), US Bank ($USB), and Wells Fargo ($WFC). Figure 1, below, tells the tale.

As one can see, the banks’ loan loss ratios for Q3 2025 (in red) were all lower than their loan loss ratios in the year-earlier period (in blue). Some were only marginally lower, others materially lower — but across all five, lower.

For those curious about the precise amounts set aside for loan loss provisions, we present Figure 2, below.

Again, these numbers are easy to find and analyze in Calcbench. We used our Multi-Company page, where you can create peer groups of companies to study and then pull up any of scores of standard disclosures we track — including numerous bank-specific disclosures, such as loan loss provisions and total loans. 

Hardcore Calcbench subscribers can also use our API to mainline earnings data directly into your own models; or you can use our Disclosures and Footnotes Query page to drill down into a single company’s detailed disclosures. 

After all, these loan loss ratios are only one performance metric among many that banks report about the performance of their loan portfolios. Banks also report loans by category (consumer credit card loans, other consumer loans, commercial loans, real estate loans, mortgage loans, auto loans, and so forth), deposits, and a host of other metrics. 

For example, Figure 3 below, is one small snippet of the disclosures from JPMorgan’s Q3 earnings release.

It’s a lot of data that banks publish. Calcbench captures it all and has it ready for your analysis.

OK, cool cool, we have the data. So how can Calcbench users actually find it? Today we’ll give you three easy-to-follow examples. 

For a Single Company

Let’s say you are researching a single company’s disclosures. Typically, the place to start is the Disclosure & Footnotes Query page. You can find that by scanning your choices along the top of the screen and finding the one that says “Disclosures.” See Figure 1, below (and look for the red arrow).

Once at the Disclosure & Footnotes page, you’ll next need to select the executive compensation disclosures as the specific data you want to see. Those disclosures are filed annually in the proxy statement, not in the quarterly financial statements or the annual 10-K. 

To find them, simply look to the left-hand side of your screen. You’ll see the list of disclosures that Calcbench offers. See Figure 2, below.

Skim all the way to the bottom of that list of disclosures, and you’ll see the compensation disclosures at the bottom under “Related Documents.” See Figure 3, below. 

Click on the choice you’d like, and that data will appear on your screen.

For Groups of Companies

Calcbench subscribers can also search larger groups of companies for compensation disclosures too. First, select the peer group you want to research. (We have a separate post explaining how to select a peer group, or you can use one of our pre-designed groups such as the S&P 500 or the Dow Jones Industrials.) 

For our purposes today, we’ll use the Dow Jones Industrials. Then you go to our XBRL Data page, which lets you search for disclosures by their individual XBRL tag (since all compensation disclosures are tagged). 

Step 2 is to select the fiscal year and period you want to research. You can select any fiscal year you’d like (although the pay versus performance disclosures are new, so if you search prior years you’ll get no results because none exist). For the fiscal period, however, you must select “Y” for the whole year because compensation disclosures only exist in the annual proxy statement.

Step 3 is to select the “statement type” you want from the drop-down menu provided. Scroll down until you reach “proxy statement pay versus performance” and select that choice. 

Then just press search, and you’ll get the results. In our example above, searching the Dow Jones Industrials for their 2024 proxies, we had 866 facts or data points. From here, you can export the data into Excel for your own modeling. That’s all there is to it. 

As a warm-up exercise for data analytics superpowers, the Calcbench analytics team pulled together a quick comparison of return on equity (one of the most important performance metrics banks report) for all three banks for the last eight quarters. See Figure 1, below. 

As you can see, JPMorgan has the best performing ROE overall, but Goldman has the best-performing trendline even though its ROE is starting from a lower base. And we also have Wells Fargo, finally unshackled from years of tight regulatory oversight and trying to put some pep back in its ROE step. Looks like Wells still has a ways to go on that front.

We built the above chart in about three minutes. Start from the Recent Filings page (which typically captures filing data within minutes of the information hitting the Securities and Exchange Commission), and then pull up individual firms’ earnings data on the Disclosures & Footnotes Query page. From there you can find specific ROE disclosures, and then use the Show Tag History feature to see prior periods’ disclosures for the same metric. Paste all that data into Excel and you’re done!

Of course, Calcbench subscribers can also mainline earnings data directly into your pre-existing models using our API or the Calcbench Excel Add-in; or you can search for disclosures across multiple companies all at once using our Multi-Company page. 

You get the idea: Calcbench has the data, and lots of different ways to find it and study it within a few keystrokes. Now get back to work studying more filings!

We can start with the top line numbers on the income statement, which all looked good. Revenue was $16.67 billion, up 6.35 percent from the year-ago period. Operating expenses were up only 4.96 percent, pretax income was up 13.8 percent, and net income popped 11.4 percent. See Figure 1, taken from our Company-in-Detail page. 

Cool stuff, but we love airline earnings releases for all the non-GAAP metrics they also report — and which Calcbench captures and indexes too.

Most notably, airlines report total revenue per available seat mile (TRASM) and cost per available seat mile (CASM) to keep investors informed about how efficiently the business is getting paying customers into seats. Figure 2, below, charts Delta’s performance on both metrics since the start of 2021.

In fact, let’s have some fun and calculate “profit per available seat mile,” which presumably would be known as PASM. This isn’t a metric Delta or other airlines actually report, but you can calculate it easily enough by subtracting CASM from TRASM. Hence we arrive at Figure 3, below.

PASM might seem volatile from quarter to quarter, but that trendline in red has a nice upward slope. 

For Calcbench subscribers who are diehard airline analysts, we also have our Airlines Earnings Template. The template is a spreadsheet available on DropBox that tracks numerous disclosures in the airline sector, including:

• TRASM, or revenue per available seat mile

• CASM, costs per available seat mile

• Load factor, which is the percentage of seating capacity filled by customers

• Fuel consumed

• Average fuel cost per gallon

• Percentage of revenue coming from passengers

• EPS

The template populates automatically with the latest data as airlines file their numbers; we should have Q3 data from all the big players before Halloween. The template only works if you are (a) a Calcbench professional-level subscriber; and (b) have installed our Excel Add-in — but once you do that, you’ll have all the latest data at your fingertips. (If you need help with any of that, contact us at us@calcbench.com.) 

Congrats to Delta. Many more Q3 releases will arrive soon!

By Stephen F. O’Byrne

Pay versus performance (PvP) disclosures give investors the ability to measure key pay dimensions for public companies and the executives leading those businesses. Investors can do this first by calculating relative cumulative pay and relative cumulative Total Shareholder Return (TSR); and then by calculating the regression trendline relating the natural log of relative pay to the natural log of relative TSR.

Such a regression analysis provides insight into four “dimensions” of executive pay. 

• The slope of the trendline provides a measure of incentive strength, what I call “pay leverage.” Pay leverage is the percentage change in relative pay associated with a 1 percent change in relative shareholder wealth. 

• The correlation between the two provides a measure of alignment. 

• The intercept provides a measure of performance-adjusted cost — that is, the pay premium at peer group average performance. 

• The ratio of pay leverage to pay alignment (that is, the slope divided by the correlation) provides a measure of relative pay risk.

All that might sound a bit complicated. Let’s consider an example. First is the pay leverage trendline for Pfizer CEO Albert Bourla, in Figure 1, below. 

Figure 1: Bourla at Pfizer 

Next is the same for Verizon CEO Hans Vestberg (Figure 2, below). 

Figure 2: Vestberg at Verizon

The peer group used to compute relative TSR for Pfizer is the NYSE ARCA Pharmaceutical Index. The peer group used to compute relative TSR for Verizon is the S&P 500 Telecommunications Services Index. 

In both examples, the solid line is the regression trendline. The dashed line is a line with a slope of 1.0 and an intercept of 0.0. It’s included in the graph to show how the company differs from a hypothetical “Perfect Correlation Pay Plan” where relative pay always equals relative performance.

What the Numbers Tell Us

When we perform a regression analysis of log relative pay on log relative performance, that gives us a window into the company’s success in achieving the three objectives of executive pay: (a) providing strong incentives to increase shareholder value, (b) retaining key talent; and (c) limiting shareholder cost. 

For example, the slope of the trendline for Bourla at Pfizer is 1.45. This means that a 1 percent increase in relative shareholder wealth increases the CEO’s relative cumulative pay by 1.45 percent. This provides a very strong incentive to increase shareholder value. 

In contrast, the slope of the trendline for Vestberg at Verizon is only 0.23. This means that a 1 percent increase in shareholder wealth increases the CEO’s pay by only 0.23 percent. Comparing the two graphs shows that Bourla’s incentive to increase shareholder wealth is roughly six times greater than the incentive for Vestberg.

The intercept is the pay premium at peer group average performance. It provides a negative measure of retention risk, and a positive measure of shareholder cost. The pay premium for Pfizer is 0.70. It’s stated in natural logarithms. We can convert it to a percentage premium by taking the anti-log. The percentage premium is 101 percent (= exp(0.70) – 1). 

This tells us that Pfizer pays 101 percent above market at average performance. This pay premium limits retention risk because Pfizer pays above average for average performance, so the CEO would have more reason to stick around. It also raises shareholder cost for the same reason. The pay premium shows that Pfizer strikes a balance between limiting retention risk and limiting shareholder cost heavily in favor of limiting retention risk. 

The natural log pay premium for Verizon is -0.30. The percentage pay “premium” is -26 percent. This pay premium shows that Verizon strikes a balance between limiting retention risk and limiting shareholder cost modestly in favor of limiting shareholder cost.

So let’s chart a course for analysis adventure, shall we? 

First are the primary financial disclosures on the income statement. Revenue was up 3.25 percent from the year-earlier period, while operating expenses were up only 1.91 percent, largely thanks to a steep decline in fuel expenses. That ultimately led to pretax income up 6.54 percent, and net income up 6.74 percent. See Figure 1, below.

OK, but that’s all just the usual stuff you can pull from anywhere. Calcbench subscribers can also pull a trove of non-GAAP data about Carnival too, including:

• Passenger cruise days (PCDs), which is the number of cruise passengers on a voyage multiplied by the number of revenue-producing ship operating days for that voyage.

• Available lower berth days (ALBDs), which measures the potential capacity of a ship. It’s somewhat analogous to available seat miles in the airline industry, and revenue per ALBD is akin to revenue per available room (“revpar”) in the hotel business.

• Occupancy rate, which can often be above 100 percent on cruise lines when more than two people share a berth (say, a family with children sleeping on a cot).

• Passengers carried, which should be self-explanatory.

Carnival reports all those non-GAAP metrics and more; and Calcbench tracks all those non-GAAP metrics too. This allows for some fun calculations when comparing GAAP and non-GAAP disclosures. 

For example, Carnival reports two types of revenue from customers: ticket sales, and onboard spending. So we compared onboard spending with passengers carried, to derive average onboard spending per passenger. See Figure 2, below.

Carnival’s fiscal Q3 is June through August, so maybe passengers double up on spa treatments or arcade games to beat the summer heat. But as the trend-line in red shows, passengers haven’t been pinching pennies yet for onboard expenses. Consumer spending on the high seas is alive and well.

You can also track cruise costs per ALBD, which is a non-GAAP metric Carnival reports directly; no complex Excel formulas required. See Figure 3, below.

But the figure above does include a number of highly volatile factors — above all, fuel. So Carnival also reports “adjusted cruise costs per ALDB excluding fuel” to give analysts a better sense of recurring costs. See Figure 4, below.

These costs are increasing somewhat more sharply than the unadjusted costs from Figure 3, but amid the brisk revenue growth, nothing is amiss in the overall picture. Plus we can see that fuel is a highly volatile part of the overall cruise cost picture, given how jagged the quarter-to-quarter fluctuations are in Figure 4 compared to Figure 3.

Oddly enough, Carnival’s share price is down today after its stellar earnings report. More specifically, the share price popped at the open, as everyone digested the excellent report; then tumbled as soon as management gave its earnings call at 10 a.m. ET. See Figure 5, below.

We don’t know why that happened, but we do know that Carnival offers reams of data to help analysts understand the company’s performance. All of it is there for the taking — especially with easy data extraction and analysis tools like Calcbench.

New compensation disclosures available in corporate proxy statements (all of them indexed by Calcbench and readily exportable into your financial models) are meant to give investors a better sense of executives’ pay compared to the performance of the companies they lead. This is known as “pay versus performance,” or PvP. 

Today we explore why one new disclosure — compensation actually paid (CAP) — provides far more useful information than the Summary Compensation Table (SCT) disclosures that companies have reported for years. It provides great new insight for financial analysts, corporate governance professionals, and others who are trying to assess the value and effectiveness of executive compensation. 

CAP is more informative because the number reflects changes in the value of an executive’s unvested equity, akin to the mark-to-market disclosures companies report for investments; SCT only reflects the grant date value of the equity award. If we do a regression analysis of relative pay vs. relative total shareholder return (TSR) using both measures, the information gap becomes clear. 

Consider the two figures below as an example. Both are for Pfizer CEO Albert Bourla. Figure 1, on the left, shows relative CAP pay versus relative TSR. Figure 2, on the right, shows relative SCT pay versus relative TSR. (Spoiler: CAP shows that Bourla has a much stronger pay incentive than what traditional SCT tells us.)

In each figure, the solid line is the regression trendline. The dashed line is a line with a slope of 1.0 and an intercept of 0.0; it’s included in the graph to provide perspective and to show how the company differs from a theoretical “Perfect Correlation Pay Plan” that makes relative pay equal to relative performance.

Figure 1                         Figure 2

This relative pay versus relative performance regression provides measures of four pay dimensions. 

The slope of the trendline provides a measure of incentive strength, which can be described as “pay leverage.” Pay leverage is the percentage change in relative pay associated with a 1 percent change in relative shareholder wealth. The correlation provides a measure of alignment. The intercept provides a measure of performance-adjusted cost; that is, the pay premium at peer group average performance. 

The ratio of pay leverage to pay alignment (the slope divided by the correlation) provides a measure of relative pay risk. Relative pay and relative TSR in Figure 1 are cumulative measures, while relative pay in Figure 2 is based on annual SCT pay, not cumulative SCT pay. 

We use annual rather than cumulative SCT pay in Figure 2 because a perfect correlation of relative annual, not cumulative, SCT pay and relative cumulative TSR is needed to provide a perfect correlation of relative cumulative CAP pay and relative cumulative TSR.

When we compare Figure 1 against Figure 2, we see that CAP pay provides much more accurate information for investors. An investor looking at SCT pay for Bourla would conclude that he has a very weak incentive to increase shareholder value, because his pay leverage is only 0.17. But CAP pay shows that Bourla has a very strong incentive, with pay leverage at 1.45 — almost nine times greater than what the investor sees in SCT pay.

The Bigger Picture

Figure 3, below, widens the lens. It compares pay-versus-performance and SCT data for a sample of 1,097 companies, all with the same CEO for the four-year period of 2020-23. 

The PvP disclosures tell investors two things. First, that CEO pay leverage is almost three times greater, 0.60 vs. 0.22, than it appears from SCT pay data; and second, that CEO pay alignment is more than twice as great, 0.66 vs. 0.29, than it appears from SCT pay data. 

Alignment is the correlation of relative pay and relative TSR. Alignment squared is the percentage of the variation in relative pay that is explained by relative TSR. When we look at alignment (r-sq), we can see that the information from the CAP disclosures is dramatically different from the SCT pay information. 

The CAP disclosure shows that relative TSR explains 44 percent (0.66 x 0.66) of the variation in relative pay for the median CEO. Meanwhile, the SCT pay disclosure shows that relative TSR explains only 8 percent (0.29 x 0.29). In other words, the CAP disclosure tells us that alignment (r-sq) is more than five times greater than it appears from the SCT pay disclosure.

If you’d like to learn more about proxy statement disclosures or see for yourself how Calcbench can help with your research, view our first post on the new pay-versus-performance disclosures and look for more coverage soon!

Disclosures about CEO compensation are reported in the proxy statement. Typically that data is difficult to find, extract, and study, but the crack software development team here at Calcbench has developed a few techniques to find and present those disclosures in the crisp, easy-to-navigate interface that subscribers know and love. 

Let’s start with an example from Walmart ($WMT) so you can see what we mean. 

First, use the Disclosures and Footnotes Query tool to search Walmart’s disclosures. Look for the “Related Documents” menu on the left side of the screen, open that menu, and you’ll see an option for “Pay Versus Performance” at the bottom. Click on that choice, and you’ll see something like Figure 1, below. We’ve added a red arrow to show you where the pay-versus-performance option is.

That’s how you find the data; it’s just those two steps of pulling up the footnote disclosures of the company you want to research and selecting the pay-versus-performance choice. The much bigger questions are how to understand this data (because there’s a lot!) and how you might put it to productive use.

What Is This Data Anyway?

The Securities and Exchange Commission adopted rules requiring these enhanced compensation disclosures in 2022. Companies must now report more details on compensation of the “principal executive officer” (the “PEO,” who is typically the chief executive officer at the company), plus an average of compensation paid to the other named executive officers.

In our Figure 1 above, the PEO is Walmart chief executive Douglas McMillion. The other “NEOs” are the rest of Walmart’s senior management team, such as CFO John Rainey and Kathryn McLay, head of Walmart International.

You can also see two separate columns for “Summary Compensation Table Total” and “Compensation Actually Paid,” for both the PEO and the other NEOs. What’s the difference? Summary Compensation Table Total includes equity awards valued at the date of grant; Compensation Actually Paid includes the value of current year equity awards valued at the stock price at the end of the year, plus the change in value during the year of unvested equity awards made in prior year. More simply, Summary Compensation Table pay is called “grant date pay” while Compensation Actually Paid is “mark to market pay.”

Most interesting to us, however, is the performance data reflected in the Total Shareholder Return columns. 

Those TSR numbers are based on the hypothetical return a shareholder would receive if he or she had invested $100 at the start of the pay-versus-performance period we’re looking at (including cumulative dividends, all re-invested). Essentially, TSR numbers let the investor see whether the company’s returns are appreciating as quickly as executives’ compensation.

For example, Figure 1 covers fiscal years 2021 through 2025 for Walmart. The TSR calculations start from the beginning of fiscal 2021. So at the end of that first year, the $100 you invested was worth $124.77; by the end of fiscal 2024, it was worth $153.75. Then TSR surged in this most recent fiscal year, to $277.55.

Meanwhile, we can also see that Walmart’s TSR underperformed its peers for the first few years of the five-year lookback, but overperformed in this most recent year. You can also see that McMillion’s compensation actually paid followed a roughly similar arc (look at that huge bump he received this year), and you can quickly eyeball gains in revenue and net income for the five fiscal years too.

How Can Calcbench Help?

If you’re an investor analyst trying to understand how much money is going to executive compensation or whether those executives are earning their keep, pay-versus-performance disclosures are a great resource. 

Calcbench has all that data neatly tracked and presented, and as usual you can export the data in table format into Excel.

Overall, proxy statements offer tons of data about executive compensation and performance. Calcbench indexes and collates it all, so we’ll have more posts in coming days and weeks about how subscribers can harness all this information and ways you might put it to good use in your analysis.

Today we want to revisit that issue from a different angle: how is all that spending changing the nature of the tech giants’ balance sheets? 

For many years, those balance sheets were notable for two basic traits: (a) lots of cash; and (b) lots of goodwill or other intangible assets. Physical assets — land, buildings, and equipment typically listed under the Property, Plant, and Equipment line item — accounted for a relatively small part of the tech giants’ overall assets. 

Well, that’s changing.

Figure 1, below, shows the ratio of “PP&E” assets versus total assets for four tech giants leading the AI arms race: Amazon ($AMZN), Google ($GOOG), Meta ($META), and Microsoft ($MSFT). 

As you can see, the ratio for all four firms has been increasing steadily since late 2023, roughly one year after the debut of ChatGPT. (ChatGPT is owned by OpenAI, but Microsoft provides the bulk of the computing infrastructure for it.) 

It’s particularly striking to see the swift increases for Microsoft (in green) and Google (in blue), since their AI systems are the two largest. In contrast, Amazon (in red) has seen less of an increase, but started from a higher base. Then again, Amazon’s PP&E includes all the warehouses, vehicles, and other equipment for its e-commerce operations, so its PP&E spending is unlike those of the other three tech giants. 

Figure 2, below, shows the ratio of goodwill to total assets for the same time period.

This chart tells a very different tale: that goodwill is declining as a portion of total assets. The exception is Microsoft and that gigantic spike in goodwill at the end of 2023, but that coincides with Microsoft’s acquisition of Activision-Blizzard, with boatloads of goodwill in tow.

And for a company-specific perspective, we offer Figure 3, below. This one shows how several important line-items on the balance sheet of Microsoft have evolved over time. 

Again we see that big jump in goodwill, as well as a big jump in cash, in latter 2023 as Microsoft digested the Activision-Blizzard deal. Overall, however, the big message in Figure 3 is the larger and larger red line, which represents PP&E. 

That line-item went from $74.4 billion in Q2 2022, to $135.6 billion in Q2 2024, to $205 billion in Q2 2025. And while Figure doesn’t include all assets, among the four assets it does track, PP&E went from 43.5 percent of the total at the start of 2022 to 54.3 percent in Q2 2025.

In other words, the AI arms race is slowly but surely transforming the tech giants from primarily light assets (goodwill, intellectual property, and other intangible assets) to increasingly heavy assets (PP&E). That has important implications for free cash flow and other performance metrics, which in turn has important implications for financial analysis and investment decisions. 

Calcbench subscribers can find this data in several ways, all of them easy:

• The Company-in-Detail page lets you see one specific company’s primary financial statements, including the balance sheet, in line-item detail. (Here’s the Microsoft example.) You can then look back through prior periods as much as you’d like.

• The Multi-Company page lets you see specific disclosures from one or more companies; first looking at specific periods and then expanding to a time-series of data if that’s your cup of tea. (Again, the Microsoft example.)

• Our Bulk Data Query page lets you pull together aggregate data from potentially huge groups of companies. This is great if you want to see how Figure 3 might look in aggregate for, say, the entire S&P 500 or all companies in the tech sector as defined by SIC code.

• Or, for power users with their own advanced analytics capability, you can always use our API to export our data directly into your own models and data feeds. Email us at us@calcbench.com for details.

And the results for all of the above pages can always be exported quickly and easily to Excel!

First, the overall picture for Brown Forman ($BF) wasn’t great. Sales, gross profit, operating income, and net income were all down from the year-earlier period, resulting in a 12.8 percent decline in EPS. That alone is enough to make investors pour a stiff shot of Brown Forman’s flagship product, Jack Daniels.

Tucked in the guts of Brown Forman’s earnings release, however, was even more grim news. The company also provided a breakdown of growth in net sales by geographic operating segment — and reported a 62 percent decline in sales from Canada. See Figure 1, below.

Why did that drop happen? Brown Forman never expressly mentioned tariffs as the cause, but it did say this about sales growth in its “Developed International” geographic segment: 

Net sales in the Developed International markets declined 8% (-9% organic) due to soft consumer demand impacted by macroeconomic and geopolitical uncertainty. The decline was led by lower volumes of Jack Daniel’s Tennessee Whiskey in Germany and the United Kingdom, along with the absence of American-made alcohol from retail shelves in most of the Canadian provinces. 

Translation: Europeans are unhappy about U.S. tariffs on European goods, so they’re boycotting the famous American brand Jack Daniels. Canadians are even more unhappy about tariffs, and are yanking Brown Forman liquor from their shelves entirely (which they can do because most liquor sales in Canada are run through government-managed liquor stores). 

We then used our “See Tag History” feature to pull up net sales growth in Canada for the prior eight quarters. See Figure 2, below. 

This news caught our attention because, as we’ve said before, Calcbench has tools to help analysts model a company’s exposure to overseas markets. That, in turn, can help you understand how much of a company’s business might be at risk either from tariffs directly (if those overseas markets impose their own retaliatory tariffs) or from consumers in those markets who sour on the U.S. company even without retaliatory tariffs (as seen in this Brown Forman example). 

Calcbench subscribers can do so by visiting our Segments, Rollforwards, and Breakouts page, pulling up the geographic segments filter for the company (or companies) you want to research, and then type “Canada” into the search field. If the company reports a Canada segment — and be warned, many companies don’t — you’ll then see that revenue, and can get a sense of how important Canada is to the company you’re researching.

We previously did this exercise using Japan instead of Canada, to identify S&P 500 firms with significant exposure to the Japan market. You can do the same for Canada, Mexico, China, Europe, or any geographic segment. If the company reports that segment, we’ll have the data. 

Anyway, Brown Forman is a sobering reminder (you’re darned right that pun was intentional) that tariffs can crimp a company’s sales even without tariffs directly applied. Tariffs are now a geopolitical issue, so you need to understand a company’s whole international sales picture. 

As always, Calcbench can deliver that data for you.