Measuring the MAG Effect on Q1 Earnings

YOY Net InC., All  +34.8%

YOY NET INc., Ex Mag 7 +16.8%

YOY Op Inc., All +20.3%

YOY Op Inc., Ex Mag 7 +13.1%

Now that the Q1 earnings season is largely behind us, today Calcbench returns to a question that has lingered over Wall Street for the last six weeks.

To what extent is overall corporate financial performance being propped up by the super-duper stellar performance of the tech giants? 

In aggregate, that Q1 performance looks great: revenue up 11 percent from the year-earlier period, operating income up 20.3 percent, net income up 34.8 percent. No wonder Wall Street indices have been dancing decidedly upward for the last several months.

Look deeper into the data, however, and one can see that much of that aggregate performance is thanks to the so-called Mag 7 stocks:

• Apple ($AAPL)

• Amazon ($AMZN)

• Alphabet ($GOOG) 

• Meta ($META)

• Microsoft ($MSFT)

• Nvidia ($NVDA)

• Tesla ($TSLA)

We stripped out those seven firms from our Earnings Tracker sample, and then re-calculated Q1 performance of all firms without the Mag 7. The result is Figure 1, below.

Metric	All Firms	Ex. Mag 7
Revenue	11.0%	9.4%
Cost of Revenue	10.1%	9.7%
Operating Expense	8.8%	7.4%
SG&A Expense	8.8%	8.6%
Capex	29.5%	10.3%
Operating Cash Flow	20.6%	13.9%
Operating Income	20.3%	13.1%
Restructuring Costs	14.3%	14.5%
EBIT	30.2%	13.9%
Net Income	34.8%	16.8%
Assets	10.5%	7.8%
Cash	11.3%	8.5%
Inventory	7.5%	6.8%
Liabilities	9.8%	7.9%
Total Debt	9.1%	7.0%

As one can see, Q1 performance for the “everyone else” group wasn’t bad, but several important line items — net income and operating income, for example — were much lower. 

Moreover, cost of revenue for this group was 9.7 percent, higher than revenue growth. That’s a warning sign for inflation, and these Q1 numbers only include one month’s worth (March) of higher costs driven by the war in Iran. Inflationary pressures will likely be worse in Q2. 

Our point: that there are multiple story lines on corporate performance lurking beneath all those headline numbers. Financial analysts would be wise to dig into the data to understand what’s really going on, and to anticipate market trends rather than respond to them. 

Calcbench can help you compile your own in-depth analysis in several ways. Our Multi-Company page lets you compare financial data among large groups of companies, all neatly organized by line-item and financial period (of your choosing, of course). The Bulk Data Query page can compile and report data in aggregate form, according to any of hundreds of individual disclosures we track. 

Power users can also inquire about our API, which lets you pipe Calcbench data directly into your own models.