Howard Marks released his latest memo this week on the intersection of people, computers, and investing. He offers an interesting perspective on the current trends in passive investing, algorithmic investing, and artificial intelligence.
The gist of the entire memo can be summed like this: whether the decision-making process behind investing is better off in the hands of humans or computers and how that might impact markets?
Let’s cover a couple things first.
There will always be a select few people with an exceptional skill set to do it all manually (arguably, even they have an internal set of rules they follow). As for the rest of us, the evidence points to real benefits in using a rules-based or algorithmic process. So I believe the real discussion for the majority of investors revolves around just how rigid, flexible, or adjustable those rules should be.
Every single index fund follows a rules-based strategy because each index follows a distinct set of rules. And “smart beta” funds and quantitative strategies just use alternative rules. Index funds were never a magic bullet. They still carry market risk. It’s not a solution for every investor misbehavior. They only solve the problem of a fund manager underperforming a benchmark after fees.
With that out of the way, what first stood out in the memo is how the popularity of indexes and other strategies might impact stock prices. Marks suggests that inclusion has its benefits, initially, based on money flows.
The second-level analysis concerns stocks that are part of the indices versus those that aren’t. Clearly with passive investing on the rise, more capital will flow into index constituents than into other stocks, and capital may flow out of the stocks that aren’t in indices in order to flow into those that are. It seems obvious that this can cause the stocks in the indices to appreciate relative to non-index stocks for reasons other than fundamental ones.
The third level concerns stocks in smart-beta funds. The more a stock is held in non-index passive vehicles receiving inflows (ceteris paribus, or everything else being equal), the more likely it is to appreciate relative to one that’s not. And stocks like Amazon that are held in a large number of smart-beta funds of a variety of types are likely to appreciate relative to stocks that are held in none or just a few.
What all of the above means is that for a stock to be added to index or smart-beta funds is an artificial form of increased popularity, and it’s relative popularity that determines the relative prices of stocks in the short run.
Price distortions like Marks describes are nothing new. There’s a long history of new investment vehicles becoming extremely popular and impacting prices — money flows in, prices bubble up and then pop. Could it happen with index funds, ETFs, and smart-beta? It’s absolutely likely. Even a sound premise can be taken to extremes.
Investors are phenomenally consistent at recognizing “whats working” now. That feeds the popularity contest that drives the market in the short term. Which creates a positive feedback loop. Where money flows, prices rise, returns increase, driving more inflows, higher prices…until it stops. Popularity wanes. Which sets the stage for a negative feedback loop. Money flows out, prices fall, returns suffer, more outflows, lower prices…
Over longer periods this creates cycles — for markets, for indexes, for factors like value, for rules-based strategies — causing things to go in and out of favor.
An exceptional formula, arrived at on the basis of exceptional intelligence and insight, conceivably can do the job, although maybe just for a limited time.
It seems obvious that a formula’s application and popularization eventually will bring an end to its effectiveness. Let’s say (in an incredibly simplified example) your study of the market shows that small-company stocks have beaten the market over a given period, so you overweight them.
a) Since “beating the market,” “out-appreciating” and “out-performing” often are just the flip side of “becoming relatively expensive,” I doubt any group of stocks can outperform for long without becoming fully- or over-priced, and thus primed for underperformance.
b) And it seems equally clear that eventually others will detect the same “small-cap effect” and pile into it. In that case, small-cap investing will become widespread and – by definition – no longer a source of superiority.
To reiterate, George Soros’s Theory of Reflexivity says the behavior of market participants alters the market. Thus no formula will be a winner forever. For me, that means the achievement of superior returns through quantitative investing requires the ability to constantly and correctly update the formula. Since investing is dynamic, the rules relied on in quantitative investing have to be dynamic.
So markets are dynamic and evolving. The only thing that appears to be static is human nature. That’s been the ultimate problem for a while now.
Human nature abhors underperformance. Investors literally can’t stand it. They lack the patience to stick around long enough to see the cycle renew itself.
Of course, sticking around is the secret sauce. The failure to do so is what sets the conditions for later success. That is why broad strategies like value work over time. It’s why rules-based strategies work. Because they sometimes look like “failing” strategies. So it shouldn’t shock anyone that sticking to a strategy — following its rules — improves results.
However, the rules used to define those strategies might have to change over time because of the dynamic nature of markets.
Ben Graham regularly updated some of the rules he used with each new edition of The Intelligent Investor. Some of his old rules still work. Some stopped working long ago. Others work so infrequently, that by the time they start working again, most people forget they exist.
So how do you separate what’s out of favor from no longer working? That’s the hard part. The only real answer is to pick a strategy, stick with it, and constantly improve on the underlying tactics or rules. That’s what Graham did. That’s what Marks suggests.
That seems like a fairly common sense conclusion. If markets are constantly evolving, then the underlying tactics should evolve too.
(All great strategies do two things well: attempt to limit your misbehavior and take advantage of other’s misbehavior. It’s the arbitrage of human nature. It’s not instantaneous. It needs time to work. Because of that, it’s important not to be overly meddling with the rules simply because it’s not working now.)
- The Behavioral Economics Guide 2018 – BehavioralEconomics.com
- Trust the Process – Alpha Architect
- Tails, You Win – M. Housel
- In Defense of the Value Premium – L. Swedroe
- The Original Flash Crash (or Why Liquidity Fears Are Nothing New) – A Wealth of Common Sense
- The Trap of Insightful Selection – S. Godin
- The Power of a Low-Cost Advantage – MOI Global
- Mistakes were Made. (And, Yes, by Me.) – J. O’Shaughnessy
- Interview with Jim O’Shaughnessy (podcast) – Bespokecast
- A Machine has Figured Out Rubik’s Cube All by Itself – MIT Tech Review
- Forty-Five Things I Learned in the Gulag – The Paris Review