John Rogers: In Investing, Brains Are More Reliable Than Machines. Here’s Why

John Rogers: In Investing, Brains Are More Reliable Than Machines. Here’s Why
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Just read a great article by John Rogers from Ariel Appreciation, who illustrates why brains are more reliable that machines in the world of investing. It reminded me of an article by Scientific American which says, “Computers are good at storage and speed, but brains maintain the efficiency lead”. The article went on to say:

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For decades computer scientists have strived to build machines that can calculate faster than the human brain and store more information. The contraptions have won. The world’s most powerful supercomputer, the K from Fujitsu, computes four times faster and holds 10 times as much data. And of course, many more bits are coursing through the Internet at any moment. Yet the Internet’s servers worldwide would fill a small city, and the K sucks up enough electricity to power 10,000 homes.

The incredibly efficient brain consumes less juice than a dim lightbulb and fits nicely inside our head. Biology does a lot with a little: the human genome, which grows our body and directs us through years of complex life, requires less data than a laptop operating system. Even a cat’s brain smokes the newest iPad—1,000 times more data storage and a million times quicker to act on it.

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Here's an excerpt from the article by John Rogers:

Man vs. machine. It is an old, well-trodden debate. There is little question that technological advances have forever changed and improved our lives in ways big and small. But now, some are predicting that machines and their algorithms will supplant humans in the investment firm of the future.

I will be the first to admit that technology helps me do my job better. I still remember my days of skimming through S&P tear sheets to find new ideas. Now a phone in my pocket can provide everything from tick-by-tick stock quotes to pages upon pages of corporate filings.

But here is the thing: data alone isn’t enough. As Albert Einstein once supposedly said, “Information is not knowledge.” Those promoting artificial intelligence would lead one to believe it is all about replicating human judgment in a superior manner. The data part may be easy for machines but the human part isn’t. This is where computers meet their limits and our brains can triumph. Much of the investment world is captivated by using quantitative models to solve math problems when so much of investment success involves untangling behavioral problems through slow, hard, qualitative analysis.

You can read the article at the WSJ here.

This article was originally posted at The Acquirer's Multiple.

The Acquirer’s Multiple® is the valuation ratio used to find attractive takeover candidates. It examines several financial statement items that other multiples like the price-to-earnings ratio do not, including debt, preferred stock, and minority interests; and interest, tax, depreciation, amortization. The Acquirer’s Multiple® is calculated as follows: Enterprise Value / Operating Earnings* It is based on the investment strategy described in the book Deep Value: Why Activist Investors and Other Contrarians Battle for Control of Losing Corporations, written by Tobias Carlisle, founder of The Acquirer’s Multiple® differs from The Magic Formula® Earnings Yield because The Acquirer’s Multiple® uses operating earnings in place of EBIT. Operating earnings is constructed from the top of the income statement down, where EBIT is constructed from the bottom up. Calculating operating earnings from the top down standardizes the metric, making a comparison across companies, industries and sectors possible, and, by excluding special items–earnings that a company does not expect to recur in future years–ensures that these earnings are related only to operations. Similarly, The Acquirer’s Multiple® differs from the ordinary enterprise multiple because it uses operating earnings in place of EBITDA, which is also constructed from the bottom up. Tobias Carlisle is also the Chief Investment Officer of Carbon Beach Asset Management LLC. He's best known as the author of the well regarded Deep Value website Greenbackd, the book Deep Value: Why Activists Investors and Other Contrarians Battle for Control of Losing Corporations (2014, Wiley Finance), and Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors (2012, Wiley Finance). He has extensive experience in investment management, business valuation, public company corporate governance, and corporate law. Articles written for Seeking Alpha are provided by the team of analysts at, home of The Acquirer's Multiple Deep Value Stock Screener. All metrics use trailing twelve month or most recent quarter data. * The screener uses the CRSP/Compustat merged database “OIADP” line item defined as “Operating Income After Depreciation.”
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