I want to make something clear before I get trolled on Twitter or LinkedIn. This post is not a criticism of chiropractors, quants or factors. It’s not a criticism of anyone. It’s just consideration of the limitations of using a single model to explain how the human body, financial markets or anything in this world works.
Models are useful. But a large part of their usefulness lies in understanding their limits!
For a chiropractor, every health issue is caused by a misalignment of the spine and its impact on the nervous system. This is known as subluxation. No matter what the problem or the symptoms, the treatment is always the same – manual readjustment of the spine.
I suffer from neck and back pain and I have found chiropractors to helpful. But it was a physiotherapist who correctly figured out that my problems were due to a disk in my neck, not a misalignment of my spine. Why didn’t any one of the four chiropractors that I’d seen over the years pick this up? Probably because they weren’t looking for it.
What does any of this have to do with investing and quants? A chiropractor is a medical professional that works with a single mental model of how the body works. Every symptom encountered has to be explained using the model. Relying on a single model has its risks as Charlie Munger explains.
What are the models? Well, the first rule is that you’ve got to have multiple models—because if you just have one or two that you’re using, the nature of human psychology is such that you’ll torture reality so that it fits your models, or at least you’ll think it does. You become the equivalent of a chiropractor who, of course, is the great boob in medicine.
It’s like the old saying, “To the man with only a hammer, every problem looks like a nail.” And of course, that’s the way the chiropractor goes about practicing medicine. But that’s a perfectly disastrous way to think and a perfectly disastrous way to operate in the world. So you’ve got to have multiple models.
And the models have to come from multiple disciplines—because all the wisdom of the world is not to be found in one little academic department.
The danger, as Munger points out, is torturing reality to fit our model. This danger can apply to many facets of life and it certainly applies to most investment approaches.
So why single out quants? Because the increasing use of quantitative strategies creates the need for a clear understanding of what quant investing can and can’t do.
‘Revenge of the Nerds’
Quantitative investing strategies are becoming increasingly popular. At last count, there is $607 billion USD invested in smart beta ETF/ETPs around the world and it’s growing fast. More and more investors realise that the stock-picking ‘jocks’ fail to beat the market most of the time. The ‘nerds’ have finally become cool.
The underlying mental model behind smart beta is the factor. Factors are an incredibly powerful and useful mental model for understanding the sources of investment risk and return. As Professor Andrew Ang explains, “factors are to asset classes what nutrients are to food”.
What could be dangerous about such a powerful and useful idea? The implicit belief that unless something can be measured and identified as a factor it doesn’t really exist.
Just as the chiropractor treats a patient only by adjusting their spine, the factor-based quant determines (there are many other types of quant strategies) how to invest only by looking for factors. Factor-based quants answer every question with the same set of statistical tools and the same approach.
Remember Charlie Munger’s admonition: “… all the wisdom of the world is not to be found in one little academic department.”
One way to illustrate the limits of what a factor-based quant approach can do is to explore an investment strategy that quants struggle with: growth investing.
Growth – It’s in the Future
There’s almost no research on growth as a factor. The closest that I could find is a recently published paper from Research Affiliates. You might be thinking; how can that be? What about:
- All of the studies demonstrating that value beats growth?
- Research into factors such as revenue and earnings growth?
- Price momentum?
- Factors such as profitability and reinvestment?
The academic studies demonstrating that “value” beats “growth” usually assume that growth is simply the opposite of value. The opposite of cheap is not growth, it’s expensive. Yes, there is an overlap between growth stocks and high valuations. But they’re not the same thing. Obviously, stocks that are expensive (i.e. high price) and deliver disappointing growth relative to expectations are going to underperform. Meanwhile stocks that continue to grow can outperform provided that growth continues to exceed investor expectations.
Studies examining the performance of historical revenue and earnings growth show that past growth does not predict future growth. This makes perfect sense because investors can’t measure future growth. They try to proxy future growth by looking for past growth and assuming that it will continue.
This is a problem for two reasons. Firstly, it ignores the tendency for growth to slow. Conspicuous growth generally attracts competition. Increased competition makes it harder to grow. Secondly, it’s hard to profit from a factor such as historical revenue growth. It’s likely to already be in the price due to other investors using historical growth as a proxy for future growth.
Price momentum could be caused by growth in sales and earnings but it could also be caused by many other reasons. Yes, there is an overlap between growth stocks and momentum stocks. That’s why momentum is often used as a proxy for growth because it can be easily measured. But they’re not the same thing.
For example, Amazon ($AMZN) has experienced extraordinary long-term growth over the twenty years that it’s been a public company. But it’s also experienced frequent and severe drawdowns or period when price momentum would have been absolutely terrible.
Growth is driven by the business, not by the stock price. If you own a true growth stock, you don’t trade it, you hold it and let it compound over time. Consequently, a true growth strategy should have relatively low turnover.
Profitability is a measure of business quality, not growth. Again, it’s true that there’s a fair degree of overlap between profitability and growth. Not only that, profitability tends to exhibit greater persistence than growth making it a more reliable quantitative factor.
A profitable company has the means to fund its own growth, but it still needs opportunities in which to reinvest profitably. It has to invest in projects where the return on capital exceeds the cost of capital.
Notice the common thread in the discussion on quants and growth? It’s that quants can never measure and invest in growth directly. They’re forced to rely on proxies that partially overlap with growth but aren’t really growth.
The reason is that quants can’t measure and invest growth because there’s no data. Growth is in the future, it hasn’t happened yet. None of the other commonly used factors have this problem. For example:
- Value is measured using price (current information) vs assets (historical information) or normalised earnings (historical information)
- Size is measured using market capitalisation (current information)
- Momentum is measured using price (current information)
- Low volatility is measured using volatility, beta, et cetera (historical information)
- Profitability is measured using return on capital (historical information) and the fact that profitable companies tend to remain profitable in the future (despite reversion to the mean)
Growth investing requires imagination. Now quants might counter that this is not ‘evidenced based investing’. But there’s no getting around the need for imagination. Even a value strategy requires imagination. It’s just a different kind of imagination.
The growth investor imagines the future of a company, its growth in revenues and earnings. The value investor imagines that investors will eventually realise that a company is undervalued and move to close the gap between price and intrinsic value. Every decision involving the future involves imagination.
Investing should always be based on evidence but, when it’s all said and done, it also requires faith!
The Limits of Factors
Every model has its blind spots and some models are better than others when it comes to solving certain kinds of problems. Factor-based strategies are less useful in areas where there is little or no information (e.g. growth investing) Are there any other areas where they might struggle? There are several, but this is a topic for a future post.