Learning Not To Repeat Today’s Bad Numbers For Stocks, Inflation, And Covid
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The bad numbers for stocks, inflation, and Covid are respectively 3,850, 8.5%, and 1,000,000. When the S&P 500 dropped below 3,850 this month, stocks fell into bear market territory. When the CPI rose by 8.5% year-over-year during the first quarter of 2022, U.S. inflation was higher than at any time in the past forty years. When official deaths from Covid in the U.S. crossed 1,000,000 this month, the Corona Research Center at Johns Hopkins University described the event as “a morbid milestone.”

The recent bad numbers for stocks, inflation, and Covid all stem from the psychology which leads people to underestimate risks. People who underestimate risks tend to behave imprudently, and then find themselves surprised and disappointed by the unfavorable outcomes that follow.

Three of the key psychological culprits which lead people to underestimate risks are excessive optimism, overconfidence, and confirmation bias. In this respect, people are prone to see the world through rose colored glasses, to lack imagination about how different the future might be relative to the present, and to discount or ignore warning signals that run counter to their views.

Today’s bad numbers reflect missed warning signals, not hindsight bias. In the past, too many experts simply underestimated the risks associated with stock market froth, inflation, and Covid deaths; and I would support this contention by referring back to my prior Forbes blog posts, and my other writings.

In respect to stocks, as long ago as 2017 I argued that on fundamental grounds, U.S. stocks were seriously overvalued. In 2018, I wrote about the overvaluation of Amazon’s stock. Amazon

AMZN
is one of the two A’s in FAANG, the other A being Apple

AAPL
. In 2019, I wrote about the overvaluation of all five FAANG stocks, along with the stocks of Microsoft and Tesla

TSLA
. In 2020, I discussed the overvaluation of Facebook, and in 2021 I revisited the overvaluation of Amazon’s stock.

Earlier this month, an article in Barron’s discussed the sharp decline in FAANG stocks, indicating that they “may not reach bottom soon.” The article notes that “for FAANG stocks, the earnings forecasts are coming down.” Of course, if previous analysts’ forecasts displayed excessive optimism, then the revisions will come down more than they otherwise would in response to declining fundamentals. Keep in mind that while the stocks making up the S&P 500 have declined by about 20%, stocks making up NASDAQ

NDAQ
have declined by 30%. Overestimating future cash flows lies at the heart of overvaluing stocks on fundamentals, and analysts’ overestimation of FAANG free cash flows has been a constant theme of mine.

In respect to inflation, in April 2020, at the beginning of the first Covid surge, I pointed out that policy makers responding to the crisis needed to be mindful about using excessive stimulus to address the economic downturn. Specifically, I wrote: “[A]lthough fiscal and monetary stimulus has limited ability to increase real output, stimulus can increase the price level. The challenge for policy makers is to aim for a stimulus package that is neither too weak and allows for deflation, nor too strong and produces inflation… The attempt to achieve both low unemployment and a high real wage will lead to ever increasing inflation, as workers set nominal wages in anticipation of higher future inflation.”

Less than a year after my publishing this post, in February 2021, Harvard economist Larry Summers issued a stark warning to then newly installed President Biden about the need to avoid overstimulating the economy. The headline for a CNN article on this point read: “Larry Summers sends stark inflation warning to Joe Biden.” It seems that an excessively optimistic, overconfident President Biden succumbed to confirmation bias and ignored the warning; and as the expression goes, the rest is history, with the Fed now raising interest rates and the economy slowing in response.

As for U.S. Covid deaths crossing one million, this was a risk I wrote about in March 2020 at the outset of the pandemic. The headline for that post was “Risk High That Psychological Pitfalls Will Cause U.S. COVID-19 Outbreak To Be More Fatal Than The Spanish Flu.” In that post I pointed out that adjusting for how much higher the U.S. population is now relative to a century ago, the risk was high that U.S. Covid deaths would surpass one million.

In April 2020, I wrote a series of Forbes posts criticizing official forecasts of deaths from Covid as being ridiculously low. For example, during that month Dr. Anthony Fauci suggested that total deaths from Covid in this country would ultimately be approximately 60,000. The Institute for Health Metrics and Evaluation at the University of Washington suggested that total deaths would be less than 100,000. The Administration projected that ultimate deaths would be around 250,000. In retrospect, these estimates reflect very strong biases associated with excessive optimism and overconfidence, two of the three pitfalls I have singled out for this post.

In my March 2020 post, I wrote: “There is reason to believe that psychological pitfalls will continue to plague U.S. efforts to combat the COVID-19 outbreak. The risk is high that these pitfalls will make the COVID-19 pandemic more fatal for this country than the Spanish flu. To fight COVID-19, we must also address these pitfalls.” Well, as a consequence of strong confirmation bias, we failed to address those pitfalls. The warning signals were clearly present for all to see in the output from mainstream epidemiological models. Those signals were simply ignored.

We cannot go back in time to avoid past mistakes. However, perhaps, just perhaps, we can collectively show enough wisdom to learn the lessons from our mistakes, by being mindful about the need to manage our psychological vulnerabilities in order to mitigate our susceptibility to behavioral pitfalls. The first mitigation step is to pay attention to warning signals, not to ignore warning signals. Doing so would help reduce the frequency of bad numbers in the future, and not just for stock prices, inflation, and Covid deaths.

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