How Kasparov’s Weaknesses Can Help You Beat The Market

Stockopedia
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While the upstart Magnus Carlsen looks a phenomenal talent, in the world of chess few would dispute that the achievements of Garry Kasparov are second to none. In spite of Kasparov’s many great achievements he is perhaps unfairly best remembered as being the first world champion to lose a match against a computer – IBM’s Deep Blue in 1997. The news kicked up a media firestorm that challenged the superiority of the human mind over computers, leading to many asking the question – would the game of chess be solved as the lesser game checkers had been several years before? While such propositions are best left to the theorists, it is two lesser known games that Kasparov played against human opponents that are most instructive for the average investor. The question we are seeking to answer is whether ‘lesser’ investors can beat ‘master’ investors, solely by cultivating a better process.

Enter the cyborg…

In an article in the New York Review of Books Kasparov explained that having lost to Deep Blue in 1997 he became fascinated with ‘Moravec’s Paradox’ or the fact that what computers are good at, humans are weak at and vice versa. Computers are excellent at calculation and computation, but humans have far higher levels of strategic intuition, sacrificial awareness and pattern recognition. What if instead of pitting one against the other, the man and machine played in tandem – could it create the highest level of chess ever played?

In 1998 he and another Grandmaster Veselin Topalov played a match in this way armed with laptops loaded with software. While a month earlier Kasparov had beaten Topalov 4–0, in this instance the match ended a 3–3 draw. When both were armed with machines, Topalov had managed to draw level in skill with the usually superior Kasparov.

While such a result raised a few eyebrows, jaws didn’t drop until 2005 when Playchess.com took the ‘Advanced Chess’ idea even further by setting up a big prize-money tournament for all comers – grandmasters, amateurs, algorithms or any hybrid of each. The early rounds predictably showed the technologically enhanced grandmasters destroying all comers, but in the final rounds an astonishing result bore out, the tournament was won by a pair of amateur American chess players. As Kasparov noted:

Their skill at manipulating and coaching their computers to look very deeply into positions effectively counteracted the superior chess understanding of their grandmaster opponents”.

The crowd nearly ‘krushes’ the master…

At the same time as the computational power of computers was wowing the chess world, the capacity of the internet was bringing previously diffuse networks of people closer together with extraordinary results. Still nursing wounds from his defeat by the brute force of Deep Blue he agreed to take part in a chess match (this time sponsored by Microsoft) against ‘The World’. The idea was to allow one move every 24 hours with each move played by The World to be decided by a free for all internet vote. More than 50,000 people voted on moves throughout the game leading to an extremely hard fought battle that flummoxed Kasparov until he eventually prevailed as victor some 62 moves later. As explained in a tremendous article by Michael Nielsen Kasparov was apparently so stunned by the level of the chess played that he wrote an entire book about it admitting he’d spent more energy on it than any other game in his career.

How had ‘The World’ managed to achieve this feat? The average participant was magnitudes poorer in ability and their strategy and tactics were completely public on internet forums. Kasparov himself had apparently reviewed them extensively throughout the match – how could he have struggled so much?

There had been four teenage masters co-ordinating the efforts of the World Team who made public recommendations on each move, but according to Nielsen the critical individual was the 15 year old US Women’s champion Irina Krush.

Shrugging off flames and personal insults, she worked to extract the best ideas and analysis from the forum as well as building up a network of strong chess-playing correspondents’.

The quality of Krush’s networked contributions were so high that every move played by the World Team between moves 10 and 50 were recommended by her. Kasparov described Krush’s move 10 as ‘an important contribution to chess’ and the level of the resulting play reinforces the idea that the opinion of the crowd, well coordinated by a central well networked facilitator can solve problems way beyond those of the individuals alone.

The above examples both serve to illustrate how amateurs in any game can raise their playing level to that of the greatest players and beyond by fusing the capabilities of modern technology with an effective process. Kasparov wrote that:

 “Weak human+machine+better process [is] superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process”.

Process is power…

For Kasparov substitute the stock market as a whole. The market is a very worthy almost all knowing opponent that even the majority of fund managers struggle to beat. Many professional investors go about beating the market by gathering more and more knowledge and analysing stocks more and more deeply, but if there’s one lesson to take from the progress of the lesser chess players above, it is that knowledge isn’t necessarily power – ****process**** is power. Rather than focusing on being a better analyst, it may be more profitable to focus on creating a better process using increasingly available computational and social inputs.

These ideas clearly are a perfect fit for investment but they may not be developed enough in the public sphere for individual investors to benefit. While the wisdom of the crowd is evident in the ability of individuals to read bulletin boards, the nature of forums leaves a lot to be desired. As opposed to the structured consensus decision making evidenced in the Krush-Kasparov match above, investors using forums often individually herd into similar high risk names with poor aggregate results. Likewise the use of checklists, algorithms and quantitative approaches by individual investors is a niche practice rather than a common one.

We are attempting to make our own contributions to these fields with some of the quantitative tools developed for our subscribers at Stockopedia but the bar could be pushed so much further given the progress of development on the web. Meanwhile, in spite of some commendable attempts, crowd enhanced decision making tends to still only happen effectively in small investment clubs or offline teams rather than in investment products available to the wider public.

These are some of the things I’d like to see solved in coming years. We are always thinking about these ideas, so if you have any thoughts to add to the debate, let me know in the comments below.

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