No Profit Pollyannas Allowed
At this point, I'm not sure anyone is as optimistic about the outlook for US corporate profits as company analysts (still) are.
To be fair, they probably don't deserve the starry-eyed Pollyanna label. Just because a given analyst is predisposed to optimism when it comes to his or her coverage universe, doesn't necessarily mean that person everywhere and always dons rose-colored glasses. An analyst might be optimistic (unrealistically so, even) about the companies with which he or she is intimat
Considering where we were March 2020 this seems pretty sedate. Good boring.
Best wishes to the people of Ukraine and to the people throughout the world who are going hungry because of the invasion.
I’d be willing to bet that wage pressure subsides 2023. Tech and housing related wages will lead the way. A lot of tech talent is flooding the market with the massive layoffs across major and minor players and that’ll create downward pressure on pay. The housing industry will be next as more people start to leave due to lack of work. Not sure if that’ll bleed into the services sector, but I wouldn’t be surprised if margins in tech hold up well next year.
I have started to reassess my view of housing in the Bay Area due to the massive decrease in valuations across many tech companies. That equity ain’t looking nearly as good as it used to for a lot of folks in the industry and I imagine that’s where a lot of down payments were coming from.
In other news we also have a bank failure: the Woke Bank (a concept bank) trump/theil is a failure and shutting down now.
Company analysts tend to underestimate fixed costs and operating leverage at inflection points.
I was taught to track incremental margins, e.g. (3Q22 gross profit – 3Q21 gross profit) / (3Q22 revenue – 3Q21 revenue), and make sure my forecast incremental margins were consistent with those delivered in prior downturns and upturns. I was also taught to build as much fixed cost detail as possible into models. The result tends to be earnings forecast below consensus at the start of downturns and above cons at upturns.
For example, suppose company revenue is $100, COGS is 70% of revenue with 50% of COGS ($35) is fixed cost and 50% ($35) is variable (proportional to revenue), SGA is 25% of revenue with 80% of SGA ($20) is fixed and 20% ($5) is variable. Result is EBIT $5.00 (5.00% EBIT margin). Suppose revenue declines -5% to $95. Result is EBIT $2.75 (2.89% EBIT margin). Revenue declines only -5% but EBIT declines -45%.
(This might describe a manufacturing company with high asset intensity hence sunstantial depreciation in COGS, plus all the manufacturing labor, factory, warehousing, distribution, etc costs in COGS, that generally have to be paid regardless of product volume or price.)
Most company analysts will not slash EBIT forecast that much, until reality compels it. Why – various possible reasons, but most Street company models don’t actually have much fixed cost detail.
You can do that for whole industries and sectors, as well as for companies. I don’t know how the top-down strategists do it, but I’ll bet the best ones, with substantial resources, are looking at incremental margins by industry.
In my SP500 valuation model, I think (from memory) I have something like 2023 revenue -5% and EBIT -28% YOY.
Now throw in inflation, which few current analysts (me included) are accustomed to modeling.
jyl- thanks for posting the details of your analysis. As a retired CPA, I appreciate the detail.
Which assumptions that you made or other factors that you did not even take into consideration are you most worried about not being accurate- besides the general “catch all” of inflation?
I can’t really model for inflation with any detail. For each company, or industry, you’d have to know or estimate the input costs (COGS in raw materials, intermediate goods, transport, energy, hours worked, wages, etc) and inflation’s effect on each, as well as price and volume for the output (sales), and then similar for SGA. That is too detailed for anyone but a specialized company analyst, which I no longer am, and even they will have a hard time getting that level of detailed information. Add in the company’s hedging, and FIFO/LIFO effects (is the revenue recognized today from products/services that entered inventory last quarter or three quarters ago?), and all the other adjustments (write-offs, valuation allowances, etc) and it just isn’t possible for an external analyst to get it right or, sometimes, even sort of right. The further you get down the income statement the harder it is, and when trying to forecast cash flows or balance sheets, it is even harder.
The other thing to consider is that the value of sellside analysts to their research customers (large institutional investors) is primarily management access, gauging investor sentiment, coming up with trade ideas, and gathering/disseminating company/industry information flow, secondarily in forecasting this quarter’s metrics (and there more directionally than exact point numbers), and only tertiarily – is that a word? – in forecasting earnings or cashflow several quarters or years out. They have to prioritize their resources. A publishing analyst with 15 or 20 companies under coverage may only have one or two junior analysts doing the modeling, and it is easy for a young analyst to sink an entire workday into updating and revising forecasts for a single company.
When I was a buyside company analyst, I used to wonder why sellside models were not more sophisticated, eventually I understood.
It doesn’t make it easier that I, like most current investors, was not in the business when we last had high inflation. I’ve been around longer than some (since the late 1990s) but high-single-digit or double-digit inflation is still something from the history books. The commonly available data sources (the standard Bloomberg, Factset, etc subscriptions) don’t even show much company financial data earlier than 1990 or so. Companies, industry structure, and data collection were so different in the 1970s-1980s. You can look at a strategist’s note saying that industry X outperforms in inflationary periods based on data from 1950-present, but is the industry the same today as it was then?
We (investors) are feeling our way through unfamiliar waters with only moldy old charts of the “Here Be Sea Monsters” variety. Which makes things interesting and entertaining, and full of opportunity, but not easy.