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Q1 US GDP, No Cheap Stocks

By datatrekresearch in Blog Q1 US GDP, No Cheap Stocks

We’ll cast both a macro and micro net today in Data, but pull both together at the end of the discussion.

Macro: Is US economic growth at 8 – 10 percent, or 2 percent, or flatlining? It all depends what data you want to use.

The New York Fed’s Weekly Economic Index says there’s no economic acceleration underway. This uses high frequency inputs like Federal tax receipts, steel production and rail traffic to come up with its assessment. As you can see, WEI has gone nowhere since mid-December:

Alternatively, you could look at the Atlanta and NY Fed’s nowcasting models, which use more traditional economic indicators as released through the quarter to estimate current period GDP growth. While neither model was assembled to actually deliver a meaningful number before the end of a calendar quarter, a data-hungry world has forced them to play this role.

Since the NY Fed Nowcast typically reads lower than Atlanta’s model, we’ll show you that one. The latest reading of 8.7 percent Q1 2021 GDP growth is up from a 5.0 percent estimate at the start of the year.

The Atlanta Fed’s estimate is slightly higher, at 10 percent currently, while the Blue Chip economists’ current guess is more like 3 percent (link below to see a graph of both).

Our take on all this: while we doubt US GDP growth is 10 percent, it should be better than Q4 2020’s 4.1 percent as unemployment continues to decline and consumer spending improves. The US economy – and the GDP calculation – is 70 percent personal consumption. Most of that (45 points of the 70) is services, with goods only playing a supporting role (the other 25 points). The NY Fed’s WEI model doesn’t capture as much of this activity as the Nowcast and GDPNow, so we understand why it is lagging.

As far as what this analysis means for stock prices, it gives us further confidence that earnings estimates are still too low for 2021 and 2022. Recall from last night’s piece that Wall Street analysts have stopped bumping up their numbers now that earnings season is over. If the US economy is accelerating the way the NY/Atlanta Fed models show, then not only will Q1 earnings come through better than expected but Q2 and Q3 should also outperform expectations. We are, after all, about to see further direct fiscal stimulus.

Moving on to our Micro point: every few months we like to compare US equity valuations for “Big Tech” and non-Tech companies. We find the approach is more intuitive than industry valuations. For example, the large cap Consumer Discretionary sector trades for 34.4x future 12-month earnings just now. That makes it the most expensive group in the S&P 500, but Amazon’s 78x multiple skews that number materially.

Here is the data:

Big Tech forward PE multiples:

  • Apple: 28.2x
  • Microsoft: 30.9x
  • Amazon: 77.8x
  • Google: 31.7x
  • Facebook: 22.7x
  • Average: 38.3x
  • Average ex-Amazon: 28.4x

15 largest non-Tech names in the S&P 500:

  • Berkshire Hathaway: 23.6x
  • JP Morgan: 14.3x
  • Johnson & Johnson: 16.8x
  • Disney: 147.3x
  • UnitedHealth: 18.4x
  • Proctor & Gamble: 21.3x
  • Home Depot: 20.6x
  • Bank of America: 14.4x
  • Comcast: 21.7x
  • ExxonMobil: 31.3x
  • Verizon: 10.8x
  • Abbott Labs: 23.9x
  • AT&T: 9.0x
  • Chevron: 23.5x
  • Coca-Cola: 24.1x
  • Average: 37.3x
  • Average ex-Disney: 25.1x

The bottom line here is that there’s not much of a difference between Big Tech’s 38x forward multiple and non-Tech’s 37x. Even if you exclude the oddballs (Amazon and Disney), the normalized multiples are 28x for Tech and 25x for non-Tech. Both, we would note, are higher than the market’s 21.5x forward multiple (FactSet Data).

The real question about whether to overweight Big Tech vs. non-Tech (but still dominant companies in their sectors) is therefore not actually about valuation because neither is cheap. It comes down to which list of companies has a better chance to show upside earnings surprises. Our stance remains that cyclicals (Energy, Financials, Consumer Discretionary ex-Amazon) will do that better than Big Tech. But make no mistake: you’re paying multiples that already anticipate a lot of structural earnings improvement. Given the macro point we outlined earlier, they should be able to beat estimates. And that’s why macro is so important to micro just now…

Sources:

Atlanta Fed GDPNow model: https://www.frbatlanta.org/cqer/research/gdpnow

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