As the title makes clear, I do not hold these people in high regard. How many times do these people have to be wrong before anyone stops taking them seriously or pays them any mind? Why hasn’t technology made them obsolete? It’s the only profession, afik, where people are paid envious sums of money and have status to be habitually wrong, or in which the value proposition is so detached from the pay. A common critcism is that pro athletes are overpaid, but at least they are good at their jobs and provide quantifiable economic value in terms of ratings and ticket sales. But what are financial analysts good at or good for?
The apparent uselessness of analysts has become so obvious it has attracted media attention, ironically by very the media who broadcast those predictions, like Forbes and Bloomberg:
Financial analysis falls into one of two camps: Stuff that is likely wrong based on some unsubstantiated hunch, wishful thinking, or motivated by the personal bias or financial interest of the forecaster (e.g. Peter Schiff predicting ‘dollar collapse’ for the 15th year in a row, while pushing gold coins), or stuff that is so vague that it offers no actionable insight or value (e.g. “We see a 40% chance of recession in the next 2-3 years.”). Gee thanks, but how does one make use of this?
The vague predictions tend to be across the map, so a third of predictions will be bearish or pessimistic, a third neutral, and a third bullish or optimistic about the economy or stock market. Yet we are led to believe that somehow this represents value creation that justifies their huge salaries, or that these people are somehow better-informed than the masses or more accurate than flipping a coin, when in either case they aren’t. Why does someone need to be paid $600,000/year to say there will be a ‘40% chance of recession next year’ when a Magic 8 Ball can do the job for free?
Other commentary is more political and falls into either camp (e.g. “Inflation expected to rise if Trump wins a second term, due to trade tensions and tariffs.”) Thanks, but again, so what. People made this prediction in 2016 after he was elected, and not only did stocks surge, but inflation actually fell due to Covid. The financial media benefits by collecting ad revenue as people click the headline out of curiosity or fear to see if BlackRock’s ‘dire recession forecast for 2024’ is true. The loser is the consumer or viewer who acts on said prediction and sells their stocks too soon.
Here are forecasts in 2016 warning of Trump tanking the stock market and economy:
(Albeit some forecasts were optimistic.)
And again in 2024:
The stock market would go on to surge from 2016-2019, until falling due to Covid, not anything specifically attributable to Trump’s economic/trade policy. This is not to defend Trump; similar incorrect predictions were voiced by the conservative media during Obama’s terms, too, like fears of Obamacare tanking the healthcare sector. Given that bear markets and recessions tend to be much briefer than bull markets, stocks tend to do well regardless of who or which party is in charge.
Below is a 25-year chart for XLV, an ETF which tracks the healthcare sector. It’s evident Obamacare, which was signed into law in 2010, was not as bad as feared as far as profits are concerned (even if it may have inconvenienced patients, which is a different matter; the focus on this post is on investing):
A major problem with financial analysis is it tends to be lagging. As the market rallies, forecasts tend to be increasingly optimistic; conversely, forecasts tend to be increasingly pessimistic as the stock market falls. Bearish predictions reached a climax during early 2009, early 2023, and March 2020 during Covid as the market fell, which had anyone acted on said advice would have sold at the worst possible time. A famous and humorous example of this was analysts slashing their Enron stock forecasts, only after the stock had lost 99% of its value–thanks for the heads up!
Let’s assume there is a 50-percent likelihood of recession next year according to Goldman Sachs, or U.S. GDP is expected to grow by 4.3% instead of 4.5%, or the stock market is overvalued according to certain metrics, what am I supposed to do with this? Should I sell half my holdings? How meaningful is a .2% percent shortfall of GDP? What if the recession never comes? If the Nasdaq gains 20-30%/year–as it has consistently since 2009–after only two years I would need another crisis or bear market on the order of magnitude as 2008 or 2022 just to get back to the original point where I sold. Given the rarity of such events, spaced apart by 8-12 years, I would likely be forced to buy back at a higher price.
Goldman Sachs recently put out a notice calling AI “overhyped, unreliable, and expensive” which went viral. But again, but so what? Someone could have said the same about the World Wide Web in 1995-1999. Sure, the internet at the time seemed overhyped, AOL was famously unreliable, and tech stocks were indeed expensive, but in hindsight it was just the beginning. Or social marketing in 2008-2011 as Facebook was just taking off; Facebook/Meta would go on to be worth over a $1 trillion and one of the most successful and profitable companies in existence.
Conversely, wearable cameras (e.g. Go Pros) were overhyped around 2014 and soon fizzled out as camera phones became cheap and powerful. But delivery apps had staying power well after Covid, such as Uber and Door Dash. However, Peloton, whose bikes surged in popularity during pandemic, didn’t make it, as inventory piled up and the stock subsequently lost 95% of its value. Same for Zoom, a Wall Street pandemic-era favorite, which eventually lost out to Telegram, WhatsApp, and Signal. VR has been on the cusp of breaking out for decades now–always falling short of prime time–but LLM-powered chatbots took the world by storm seemingly overnight.
The lesson here is something being overhyped and expensive now does not inform us of the future. Maybe no one knows.
Some of these people are not analysts at a financial firm per se, but are CEOs, whose inevitably-wrong predictions are broadcast by the financial media in spite of the obvious conflict of interest and the impossibility of objectivity of someone whose business stands to profit greatly if said prediction comes true, which it almost never does.
Hundreds of individuals and firms have predicted Bitcoin would be at $100k by now after the halving and the ETF approval; instead, the price has languished between $55-$70k. Six-figure Bitcoin, let alone a million dollars, is looking increasingly out of reach.
For example, Tom Lee (if at first you don’t succeed, try again):
Other examples include Michael Saylor of MicroStrategy and Cathie Wood of Ark Investments, both of whom for years have promised that $1 million per Bitcoin was ‘just around the corner’, only for prices to crash like in 2022. As far as they are concerned, it doesn’t matter what Bitcoin does. Any media coverage amounts to free advertising, which is always welcome even if those who heed said advice lose money.
Perhaps I’m painting with too broad of a brush, but I have yet to see anyone who is good at the profession. These people are being paid a lot of money on the assumption that their insights or perspectives are superior enough to justify their salaries, and I don’t see it. There are good doctors, good engineers, but no good analysts. I’m not just talking predicting the future, but also interpreting what the data means on a more practical level, such as what are the implications of slightly-weaker-than-expected GDP. When analysis conflicts, like bullish and bearish forecasts for the same company, then this only compounds the ambiguity. May as well just toss a coin.
Overall, the U.S. economy is remarkably adaptable, consumers tend to be resilient and quickly bounce back from adversity as we saw during Covid when stimulus money flooded the economy and customers flooded the stores after the lockdowns were lifted, and that corporate profits tend to be rather well-insulated from macro factors or policy like inflation, the threat of war, or tariffs. Maybe investors ought to just ignore such forecasts, as not only are they of little to no actionable value, but also likely inconsequential to the market. Maybe it’s time for these analysts to give it a rest. These people who well-paid to provide expertise are clearly failing at that, spreading only fear or uncertainty instead.