If you are an investment management professional, you will inevitably be asked the question about where we think the markets are headed? By clients, media, friends and family alike. ‘We don’t know’ is our preferred response every single time. This recent memo from Howard Marks reminds us that we should keep it that way. The memo is about the reasons why forecasts are rarely helpful.
“In order to produce something useful – be it in manufacturing, academia, or even the arts – you must have a reliable process capable of converting the required inputs into the desired output. The problem, in short, is that I don’t think there can be a process capable of consistently turning the large number of variables associated with economies and financial markets (the inputs) into a useful macro forecast (the output).”
He shows how complicated modelling an economy is:
“The U.S., for example, has a population of around 330 million. All but the very youngest and perhaps the very oldest are participants in the economy. Thus, there are hundreds of millions of consumers, plus millions of workers, producers, and intermediaries (many people fall into more than one category). To predict the path of the economy, you have to forecast the behavior of these people – if not for every participant, then at least for group aggregates.
A real simulation of the U.S. economy would have to deal with billions of interactions or nodes, including interactions with suppliers, customers, and other market participants around the globe. Is it possible to do this? Is it possible, for example, to predict how consumers will behave (a) if they receive an additional dollar of income (what will be the “marginal propensity to consume”?); (b) if energy prices rise, squeezing other household budget categories; (c) if the price for one good rises relative to others (will there be a “substitution effect”?); or (d) if the geopolitical arena is roiled by events continents away?”
He quotes Niall Ferguson from a recent article on the currently most debated topic of inflation:
“Consider for a moment what we are implicitly asking when we pose the question: Has inflation peaked? We are not only asking about the supply of and demand for 94,000 different commodities, manufactures and services. We are also asking about the future path of interest rates set by the Fed, which – despite the much-vaunted policy of “forward guidance” – is far from certain. We are asking about how long the strength of the dollar will be sustained, as it is currently holding down the price of U.S. imports.
But there’s more. We are at the same time implicitly asking how long the war in Ukraine will last, as the disruption caused since February by the Russian invasion has significantly exacerbated energy and food price inflation. We are asking whether oil-producing countries such as Saudi Arabia will respond to pleas from Western governments to pump more crude. . . .
We should probably also ask ourselves what the impact on Western labor markets will be of the latest Covid omicron sub-variant, BA.5. UK data indicate that BA.5 is 35% more transmissible than its predecessor BA.2, which in turn was over 20% more transmissible than the original omicron.
Good luck adding all those variables to your model. It is in fact just as impossible to be sure about the future path of inflation as it is to be sure about the future path of the war in Ukraine and the future path of the Covid pandemic.”
Marks then adds how this need to predict the future affects investors in the real world:
“I imagine that for most money managers, the process goes like this: “I predict the economy will do A. If A happens, interest rates should do B. With interest rates of B, the stock market should do C. Under that environment, the best performing sector should be D, and stock E should rise the most.” The portfolio expected to do best under that scenario is then assembled.
But how likely is E anyway? Remember that E is conditioned on A, B, C and D. Being right two-thirds of the time would be a great accomplishment in the world of forecasting. But if each of the five predictions has a 67% chance of being right, then there is a 13% probability that all five will be correct and that the stock will perform as expected.”
He then has a jibe at economists who aren’t held accountable for their forecasts:
“As I mentioned in my recent memo Thinking About Macro, in the 1970s we used to describe an economist as “a portfolio manager who never marks to market.” In other words, economists make forecasts; events prove them either wrong or right; they go on to make new forecasts; but they don’t keep track of how often they get it right (or they don’t publish the stats).
Can you imagine hiring a money manager (or being hired, if you are a money manager) without reference to a track record? And yet, economists and strategists stay in business, presumably because there are customers for their forecasts, despite there being no published records.”
But it isn’t easy to keep saying ‘I don’t know’ either:
“You’ll soon tire of saying “I don’t know” to friends and strangers alike. After a while, even relatives will stop asking where you think the market’s going. You’ll never get to enjoy that 1-in-1,000 moment when your forecast comes true and The Wall Street Journal runs your picture. On the other hand, you’ll be spared all those times when forecasts miss the mark, as well as the losses that can result from investing based on over-rated knowledge of the future. But how do you think it feels to have prospective clients ask about your investment outlook and have to say, “I have no idea”?
For me, the bottom line on which school is best comes from the late Stanford behaviorist, Amos Tversky: “It’s frightening to think that you might not know something, but more frightening to think that, by and large, the world is run by people who have faith that they know exactly what’s going on.””
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