Many macroeconomic relationships are difficult to understand and therefore more difficult to predict. Unfortunately, we also can’t rely on financial numbers when they are first published. The reason is that many of the main characters go through several rounds of adjustments afterward. In August 2011, zero employment growth was reported in the United States, which helped trigger stimulus measures by the Obama administration. The Wall Street Journal wrote, “Job growth is stalling,” economists reported, “The economy is now failing,” and the stock market fell 2 percent on the day the numbers came out. The reality was very different, and the final figure showed 133,000 new jobs. In the first quarter of 2015, near-zero growth in the US economy was initially reported, but later an upward revision occurred to 3.3%. During the first half of 2023, US job growth proved to be about 250,000 weaker than first reported. We have seen similar instances of revisions also from the UK and European economies this year.
Uncertainty over the numbers has increased since the pandemic
After the pandemic, the number of major revisions increased. Macroeconomists, who are supposed to make forecasts, disagree with each other much more than before. According to The Economist, the range of GDP estimates from US analysts was twice what it was before the pandemic. Several possible reasons have been cited, including that the pandemic, problems with supply chains, and the war in Ukraine have all disrupted the so-called seasonal adjustment made to many economic data.
Another reason may be that far fewer people than used to respond to surveys, which are the starting point for many major mood and personality surveys. The so-called most important figure of the month is the US labor market report. Before 2020, about 60 percent of the 651,000 companies that receive questions about employment status responded. Today, the percentage of respondents is only 42 percent. Another relevant data point is the number of jobs advertised in the USA. According to the Wall Street Journal, the response rate to these numbers (JOLTS) fell by more than half to 32 percent. A low response rate increases the likelihood of revisions and therefore the possibility of incorrect investment conclusions and decisions.
Even correct financial forecasts can be of low interest
Even if one is lucky enough to predict economic outcomes correctly, one still cannot know how the financial markets will react. The prevailing mood among market participants shifts from optimism to pessimism based on changing perceptions about what will happen in the economy, with corporate profits or with interest rates. In recent years, we have not only had many examples of positive economic surprises leading to higher prices in the markets, but we have also witnessed many events in which positive macro surprises, on the other hand, led to lower prices. It also happened that negative economic surprises led to higher prices. After the financial crisis, changes in the reaction pattern were linked to whether aggregate numbers increased or decreased the likelihood of changes in monetary policy, especially in the USA.
Even today, we live in a “good news is bad news” climate, where positive news from the US or European economy, taken in isolation, increases the likelihood of interest rates rising – which in turn may be seen as a threat to the US economy. . Profitability and debt servicing capacity of a business. Unfortunately, there is no harm in knowing in advance when “good news” turns into “good news” again.
“Old news = no news”?
In addition to the fact that the overall numbers may be wrong and that no one can know how financial markets will actually react, the utility value of “smart short-term bets” may be challenged by a third factor. In Western stock markets, 60 to 75 percent of all transactions are executed through algorithm-based strategies. These are machines that analyze a much larger amount of information than humans, and make decisions in a split second. In practical terms, this means that any clear opportunities for high returns in the short term are hijacked by data strategies before we humans have time to react. If a company notifies the markets of a breakthrough in a new market or with a new product, the machines will immediately raise the company’s stock prices. Investors who eventually come in have to buy at higher prices, which means a lower expected return.
What does this have to do with amateur tennis?
One of the most interesting writers on asset management today is Howard Marks, head of Oaktree Capital Group in the US. In his final comment, he made an interesting comparison between investments and tennis.
The best tennis players in the world tend to win matches because they have more winners than their opponents. In other words, offensive strikes of great danger that the opponent cannot return. At the amateur level, tennis, on the other hand, is about the exact opposite. Those who emerge victorious from lower-level matches rarely win due to risky winning moves, but rather by making fewer mistakes than their opponent. Simply recovering the ball with relatively low risk increases the likelihood that the opponent will be the one to make a mistake and hit the ball or go into the net, and that you win the point.
Mark’s analogy fits well with what I believe is the appropriate approach to asset management. Unless one is among the category of professional investors who can have a glimmer of hope of making the majority of short-term bets, the focus should instead be on avoiding making mistakes. In other words, reduce the risk of mistakes and wrong investments through extensive use of risk diversification, accepting development that is a little more boring, but also more valuable over time.
So the recipe becomes very simple, but it still requires a lot of effort; Make a long-term plan, build a broad portfolio with good financing solutions, and let time and value creation in the economy do the work.
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