Behind the Memo - The Illusion of Knowledge
Primer: Anna Szymanski, the senior financial writer from Oaktree Capital, interviewed Howard Marks as he discussed the key themes from his recent memo, The Illusion of Knowledge. He explained the difference between macro thinking and macro forecasting, as well as how an investor should move forward without the use of such macro forecasts.
Intro to Howard Marks
Co-founder and co-chairman of Oaktree Capital Management
A great Investor and a great writer
Well known for his investment insights and also his memos that are published publicly on the Oaktree website
His most recent memo is released on 8th Sep 2022, titled The Illusion of Knowledge
He talks about forecasting and why he is not interested in it
Disregard for macro forecast
Howard felt that most of the time, things (e.g. economy, currencies, commodities and markets) continue along a normal long-term path
Most forecasts are extrapolations from the current level or the recent trend
Since most of the time, things continue along that path, most forecasts are correct extrapolations
The problem is that everyone extrapolates so the expectation of extrapolation is built into the prices
When the extrapolation turns out to be true, the trend continues and the market doesn’t react as it is expected to do so
Once in a while, there is a divergence from the trend but nobody can predict it as they are busy predicting extrapolation
Such divergence is not anticipated, hence the events are not priced in, resulting in a strong market impact
Divergences do not happen often, so most forecasts of divergence are wrong
“So if you add it up, we have extrapolation forecasts, which are usually right, but rarely profitable, and forecasts of divergence, which are potentially profitable, but rarely made, and rarely made correctly. And if you put those two things together, in my opinion, the logical conclusion is that most forecasts are not valuable, and do not produce profitability.”
- Howard Marks
Challenging to create helpful macro forecasts
Errors when simplifying and introducing assumptions
There are many participants in the economy (some 300 million of them in the US) and you have to predict the behaviour of all these people without being able to talk to them
Hence one has to make assumptions, usually by extrapolating from the past
Since the interactions between participants are so complex, one has to simplify assumptions
All these introduce the possibility of error
Uncertain inputs
Every model requires input, possibly 1000s of such inputs
Garbage In Garbage Out - if the inputs are not good, the result of the model will also be invalid
“But the question is, if the forecasts are so easily undone by surprising outcomes, random outcomes, and the complexity, then isn't it a mistake of folly to engage in macro forecasting?”
~ Howard Marks
Randomness in the macro environment
In the last two years, there’s been the pandemic, the war and inflation. All these are hard to predict
How people cope with dissonance
People try to rationalize new evidence within their existing forecasting framework. They do not want to see their belief blown up
His son, Andrew, suggested a book, “Mistakes Were Made (But Not by Me)” by Carol Tavris and Elliot Aronson
People hold views and when dissonant information arrives, they had to deal with that information
2 ways to deal with dissonant information
Harmonizing it with prior beliefs
Ignoring it, rejecting it and explaining it away
Since forecasts are rarely, both correct and profitable, people are better off doing without them than relying on ones that are potentially very wrong
When things are highly uncertain and views are unlikely to be correct, it’s better to say I don’t know
Moving forward without forecasting
No easy answer to this as investing is a highly competitive field with very motivated and intelligent people trying to make money
Should not have strongly held views
Can have an opinion but do not bet heavily on them
One of the tenets of Oaktree’s investment philosophy is that their investment decisions are not driven by macro forecasts
Make more neutral assumptions
Would expect that most of the time, the future will be like the past
We won’t be able to foresee which parts of the future will be different from the past
Instead of trying to be right, try to avoid being really wrong
Trying to be right means betting heavily on a forecast where you can either make a lot or lose a lot
Trying not to be wrong is not betting heavily on a forecast in which you forego the opportunity to be an insightful genius and you avoid the possibility of getting involved in a train wreck
“It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.”
~ Mark Twain
Intelligence can sometimes get in the way of investment as it makes people think they can do more than they actually can
Better to spend your time and hard work studying companies in off-the-beaten-path industries and emerging markets
Have the humility to know that you don’t know and that you can be wrong
Rather than win big and lose big, it’s better to just make a good return and avoid such extremes
This also depends on one’s temperament and there are no right or wrong answers
Scary to live in an uncertain world
Despite a lot of evidence to say that macro forecasting doesn’t work very well in the real world, it’s hard for people to accept
People do not like to live in ambiguity, and they much prefer certainty
Most people don’t like to say “I don’t know” when asked what the future holds
Howard finds it very freeing to say so though
“When you say I don't know, the one thing you know for sure is you're not kidding yourself. You're being honest with yourself, and you're being honest with your listener. And I think that counts for a lot. And I'm very glad to do it when it's true, which is often.”
~ Howard Marks
Macro thinking vs Macro forecasting
Howard wrote a note in 2021 regarding the importance of macro implications when investing. In 2022, he wrote about how macro forecasting is pointless. What’s the difference?
In Oaktree, there is a saying that they may not know where they are going, but they certainly know where they stand right now
We should still be able to understand the environment we’re in despite not being able to accurately predict the future
Should know when the market is extremely overvalued or undervalued by historical standards
An example
The average post-war price-earnings (PE) ratio is 16x for SP500
Let’s say today it’s 23x, about 50% higher than the historic average, so the market is precarious
First-level thinking: If the market is way higher than the historic average, one can either short it or reduce one’s positions
Second-level thinking: it’s not enough that PE ratios are above average, but what can make the PE ratios non-high?
Focusing your energy on where you can add value and what actually matters is way better than spending it on predicting the future
Final words
Howard had been storing up quotations on the subject of forecasting for decades
Had fun coming up with the memo
A few of his favourite quotes that he used to head each section in the memo
“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.”
~ Amos Tversky
“There are two kinds of forecasters: those who don’t know, and those who don’t know they don’t know.”
– John Kenneth Galbraith
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