Let me confess and say that I am a huge fan of Howard Marks’s writings. For those of you who have never heard of him, Howard Marks is the co-founder and co-chairman of the Oaktree Capital, a firm that is considered to be one of the largest investors in distressed securities worldwide. Marks is famous for his expertise in investing in high-yielding bonds and, through Oaktree, made a name for himself by generating stellar returns during the Great Financial Crisis (GFC) in 2008-09.
Marks is famous for his memos that he publishes for free on Oaktree’s website. In the investing community, his memos are considered to be a must read. I have heeded to this advice and been binge-reading his memos for the past several weeks. In a world that is so focused on news/ breaking news/ current affairs, his memos help me take a step back and deeply introspect about my own investing strategy and mindset. This is such a crucial aspect of investing that, unfortunately, receives so little attention in the community that I am a part of.
Each memo is a treasure trove of information and there is a lot to unpack. Therefore, to reinforce the learnings, I thought of creating a new series on my blog that would be dedicated to my reflections from reading these memos. I may or may not choose each and every single memo, but instead choose the ones that really resonated with me.
To kick things off, I will start with the most recent memo titled “The Illusion of Knowledge” (published Sep 8. 2022).
All Economic Forecasting is Flawed
The memo starts off by discussing how there is a strong human tendency to attempt to forecast about just about any subject. Marks argues that the premise of forecasting itself is flawed. According to Marks, all forecasting assumes that the environment around us can be modeled, in some shape or form, with some notion of deterministic behavior i.e. for a given set of inputs, these are going to be outputs.
Marks states that modeling an economy is simply impossible. He writes:
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.
…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?
This is a sound argument with some merit. If an economy could be modeled as a mathematical model, the richest people on the planet would have been statisticians and mathematicians. And while the community at large is obsessed with questions about “Will there be a recession? Has inflation peaked? What will be the course of the Ukraine war?”, the truth of the matter is that none of these are predictable because the number of variables involved is far too large to account for in a simplistic model.
So why do people forecast then?
Clearly, forecasting is futile. Forecasting about economy is even more sillier. And yet if you browse around the CNBC, social media and/or your favorite news medium, these avenues are full of people making bold predictions.
To give an example:
Here is a certain famous YouTuber who shall not be named (but you can easily figure out who he is) who goes on to predict how “China’s ENTIRE Economy Is About to Collapse”. And what is better is he has even given a time frame that this is going to happen within 29 days. Now how on earth can someone predict this with such precision? Consider some other factors: we are talking about the collapse of one of the largest economies of the world with a incredibly complex political structure, predictions being made by someone who is NOT a reputed economist, or political strategist, or an expert in China, and someone who is sitting in some other corner of the globe with no sense of ground realities in China.
I could this dismiss this as laughable buffoonery, but when I actually see the number of people following this account and taking this as serious advice and consider this as part of their “research” to base their financial decisions, I SHUDDER to think of the consequences.
What is worse is that this does not appear to be a one-off and we have such predictions being made from this account and other such similar accounts with such regularity and at around the same time. One cannot help but think that there is something else at play here.
Enough about YouTubers. Lets get back to the topic of forecasting.
I somehow get a sense that these forecasters are enamored with the thought of getting one of these predictions right, so this could be their “Haha, I told you so.” moment. Or maybe it is our society’s craze with placing such forecasters at a higher pedestal if they happen to get one prediction right. For instance, the media is obsessed with following Michael Burry’s stock market moves, especially given that he was one of the first forecasters of the GFC and subprime mortgage crisis. Thoughts being: surely Michael Burry knows what he is doing, he got it right once, and he might get it right again. Right? I really don’t know. But there is one glaringly obvious flaw in this reasoning: it makes the assumption that all previous recessions or bear markets have some common characteristics making it easy to predict its onset. Again it is the falling into the same trap of trying to predict the onset of a complex situation through a simplistic model.
Do we really need to care?
Marks ends his memo with the question of what should the average investor focus on as far as forecasting. I share his opinion in that the average investor will be better served by resigning to the notion that all forecasting in general, and economic forecasting in particular, is futile and more importantly unnecessary.
Instead, it is far better to play this game by working out the probabilities. In my valuations, I use a standard project management technique called building a three-point estimate. This is a fancy name to a rather simple concept. The idea to come up with three scenarios: best-case, worst-case and most-likely estimate and work out our valuations based on these estimates. Of course, fundamentals with each business could change depending on new inputs at which point we may have to re-asses our valuations accordingly. In summary, it is better to be reactionary than to speculate (with some false notion of certainty).
What are your thoughts on forecasting? I am really curious to know.