An algorithm is simply a set of rules or a process to automate decisions.
It can be highly complex or as simple as you want to make it. It can be rigid or flexible. It can be precise or good enough. There is a range of opinions on all of those possibilities as to what is best.
The one thing Daniel Kahneman knows is that algorithms are better than humans when making decisions (emphasis mine):
An algorithm could really do better than humans, because it filters out noise. If you present an algorithm the same problem twice, you’ll get the same output. That’s just not true of people.
You can combine humans and machines, provided the machine has the last word! Humans have a lot of valuable inputs; they have impressions, they have judgments.
But humans are not very good at integrating information in a reliable and robust way. And that’s what algorithms are designed to do.
In general, if you allow people to override algorithms, you lose validity because they override it too often. Also, they override on the basis of their impressions, which are biased, inaccurate, and noisy. Decisions may depend on someone’s mood at the moment.
People are easily influenced by noise. Also, there’s always noise to be influenced by.
Especially with investing. It’s almost all noise. But noise is only one of the reasons. We all have built-in biases to deal with too.
So having a set of rules helps to avoid big mistakes.
Except, investors override their rules to the detriment of performance. And if they don’t track their overriding decisions they’re blind to the mistake.
Joel Greenblatt wrote about the errors of investors ways after he studied the performance of those following his Magic Formula strategy. Investors were given the option to self-manage their accounts or have it “professionally managed” i.e. automated (emphasis mine):
Well, as it turns out, the self-managed accounts, where clients could choose their own stocks from the pre-approved list and then follow (or not) our guidelines for trading the stocks at fixed intervals didn’t do too badly. A compilation of all self-managed accounts for the two year period showed a cumulative return of 59.4% after all expenses. Pretty darn good, right? Unfortunately, the S&P 500 during the same period was actually up 62.7%.
“Hmmm….that’s interesting”, you say (or I’ll say it for you, it works either way), “so how did the ‘professionally managed’ accounts do during the same period?” Well, a compilation of all the “professionally managed” accounts earned 84.1% after all expenses over the same two years, beating the “self managed” by almost 25% (and the S&P by well over 20%). For just a two year period, that’s a huge difference! It’s especially huge since both “self-managed” and “professionally managed” chose investments from the same list of stocks and supposedly followed the same basic game plan.
Let’s put it another way: on average the people who “self-managed” their accounts took a winning system and used their judgment to unintentionally eliminate all the outperformance and then some!
Greenblatt summed up the poor performance of what investors often do wrong:
- They avoid the “worst” looking stocks, assets classes, and only buy what looks “good”, or
- They follow a strategy until it underperforms for a year or two, or
- They follow a strategy until it loses money along with the market, or
- They chase good performance by buying more instead of selling when they should.
The easiest way to explain it is investors lose faith in the process or never trust it to start, while the algorithm never second-guesses the process. It never makes emotional decisions. It never wavers.
This isn’t limited to Greenblatt’s strategy. It’s universal.
Michael Mauboussin spent a good portion of an interview for Graham & Doddsville discussing the importance of trusting the process because of the noise, bias, and behavior that can infect our decisions.
There’s a great essay that I learned about from Atul Gawande, who wrote The Checklist Manifesto. It was an essay written in the 1970s by, of all things, two philosophers about medicine. The question was, “why do doctors fail?” They said it basically comes down to two things. The first is ignorance, meaning you just don’t know what you’re doing. You don’t know how to do this particular operation or whatever it is. The second way doctors fail is execution. People just don’t do what they know they should be doing. When you read the Checklist Manifesto, it’s much more about the latter than the former.
When I think about investing, it’s really trying to bring both of those things to bear.
To me, those are the two big areas: just getting better and executing effectively day in and day out. I think Gawande’s major contribution to the world is really recognizing that there’s huge upside to just executing what we already know how to do. It’s remarkable how often people deviate from their process.
Trusting the process is not easy, but it’s a prerequisite for investing success. It takes time. It takes self-reflection and openmindedness. It requires a willingness to learn, experiment, fail, keep trying, and constantly improve upon what works. Few people will suffer through that but those that do get rewarded.
Where Humans Meet Machines: Intuition, Expertise, and Learning
Kahneman Interview: Intuition, Expertise, Learning, Humans, and Machines (video)
Adding Your Two Cents May Cost a Lot Over the Long Term
Graham & Doddsville Spring 2018 (pdf)
- To Be a New Fool in the World – J. Zweig
- The Pygmalion Effect: Proving Them Right – Farnam Street
- “If I Were Wrong, What Would It Look Like?” – M. Housel
- The 300 Secrets* to High Stock Returns – Chicago Booth Review
- The Hidden Risk of Passive and Index Hugging – R. Bookstaber
- These Earnings Beats Aren’t Real, It’s Mostly Accounting Gimmicks – Marketwatch
- The Old Allure of New Money – R. Shiller
- This is Why We Can’t Have Nice Things – Epsilon Theory
- How the Enlightenment Ends – H. Kissinger
- The Bill Gates Line – Stratechery
- The Key to Everything – F. Dyson
- How One Company Scammed Silicon Valley and How it Got Caught – NY Times
- 5 Books Worth Reading this Summer – B. Gates
- Summer Reading List 2018 – B. Ritholtz