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Trading – Man vs. Machines: Part 2 of a Continuing Series on “How Algorithm Trading Can Supercharge Your Trading Profit”

Trading room – Friday 16 Nov 2018

 

Part 2 – Man vs. Machine: Kasparov vs. Deep Blue

In the first part of this series on how algorithm trading can supercharge your trading profit, we look at an introduction to the world of algorithm trading and how it is a force that has changed and continued to disrupt the global investment and trading world.

You can read Part 1 here on Introduction: When humans and machines collide.

Obviously, before we look further at the power of big data analytics and algorithm trading, we would like to look at how it all started with an astounding event in 1996/1997 that captivated the entire world attention.

Courtesy of an article by Mark Anderson, Professor in Computing and Information Systems at Edge Hill University, we have this introduction to start with below:

On the seventh move of the crucial deciding game, black made what some now consider to have been a critical error. When black mixed up the moves for the Caro-Kann defense, white took advantage and created a new attack by sacrificing a knight. In just 11 more moves, white had built a position so strong that black had no option but to concede defeat. The loser reacted with a cry of foul play – one of the most strident accusations of cheating ever made in a tournament, which ignited an international conspiracy theory that is still questioned 20 years later.”

But of course, the above was no ordinary game of chess.

It’s not uncommon for a defeated player to accuse their opponent of cheating – but in this case, the loser was the then world chess champion, Garry Kasparov. The victor was even more unusual: IBM supercomputer, Deep Blue.

Let’s put the story in perspective. Over 20 years ago, World Chess Champion Garry Kasparov took on IBM and its super-computer Deep Blue in the ultimate battle of man versus machine. This was a monumental moment in chess history and was followed closely around the world.

This match appealed to chess players, scientists, computer experts, and the general public (and obviously businesses were always looking at the commercial aspect of it though it was not so apparent at that time).

At the time of the match, Kasparov was the reigning world chess champion. He was put to the ultimate test carrying the weight of humanity on his shoulders heading into this iconic chess battle.

 

Kasparov had initially beaten Deep Blue in a 1996 six-match game but he grew bold and challenged the Deep Blue IBM programmers to another re-match in 1997 which captivated the world by storm.

The much-anticipated six-game rematch of man vs. machine in 1997 then brought much excitement as Deep Blue programmers had gone back over the one-year since the last match in 1996 to beef up their programs with the rapid progress of the seeds of machine automation and artificial intelligence then (AI).

Courtesy from an analysis in chess.com, we follow the progress of this historic match below:

 

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Game 1

Kasparov was shocked at Deep Blue’s play in this game. Move 44 in the first game is said to be the result of a computer “bug” when the machine could not figure out what move to play and simply collapsed with a win to Kasparov.


Game 2

Game number two of the 1997 match was the most controversial encounter of the match. After the loss, Kasparov made it known that he felt that the IBM team cheated by receiving outside information from a grandmaster (human) starting with move no 36.

However, in a later interview almost 20 years later in 2016, Kasparov said after much analysis and looking at both his own and the computers’ play that he takes back his conclusions on what happened during this game.

 

Game 3

Coming in to play game three of the match, Kasparov’s focus would be put to the test after round two’s conflicts with the Deep Blue team. The question would be if Kasparov could continue the match and put this game behind him in order to bring out his best chess. The interesting part of game three is Kasparov’s anti-computer opening which was somewhat of a revolution at the time. The position after 48 moves was exhausted, and the game was drawn.

 

Game 4

Kasparov used the same strategy this game as the last game by playing a slightly offbeat opening to keep the computer of any special book it might have programmed. Deep Blue gained a space advantage and some slight initiative, but Kasparov was able to keep the game balanced. The game ended in a drawn rook and pawn endgame.

 

Game 5

Game five was another draw, but this game was a real fight from both sides. Even though the final position has Kasparov queening a pawn, Deep Blue’s pieces were coordinated enough to force a perpetual check.

 

Game 6

The final of the 1997 match of Kasparov vs. Deep Blue shocked Kasparov and the world. Deep Blue played a very aggressive move by sacrificing a knight on move eight! Kasparov never recovered from this stunning move and went down in flames in just 19 moves.

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So, there we have it. In defeating Kasparov on May 11 1997, Deep Blue made history as the first computer to beat a world champion in a six-game match under standard time controls.

Kasparov had won the first game, lost the second and then drawn the following three. When Deep Blue took the match by winning the final game, Kasparov refused to believe it.

 

Kasparov argued that the computer must actually have been controlled by a real grandmaster. He and his supporters believed that Deep Blue’s playing was too human to be that of a machine.

Meanwhile, to many of those in the outside world who were convinced by the computer’s performance, it appeared that artificial intelligence had reached a stage where it could outsmart humanity – at least at a game that had long been considered too complex for a machine.

 

However, in reality, there is much to learn from this historic game. But how is this related to trading using algorithm programs in today’s world?

The initiated would have seen that the behavior of Kasparov and Deep Blue in an analogy merely reflects the behavior of traders and algorithm trading programs versus the market today, which is remarkable to prove that human behavior of emotions and application of intelligence never changes (as highlighted in their behaviors highlighted in red above in the match coverage above).

 

How many times would a trader rant and swear at losing trades but refuse to take profit on winning trades? Most traders would rather blame market conditions whey they lose or lost appetite to trade rather than assessing the shortfall in their trading plans.

But would a machine do better than human intelligent thinking, intuition, and instincts to avoid obviously foolish trades on stocks such as those operated by pump and dump (syndicate) operators or a penny stock counter which could display erratic price movement?

Can “automation” approaches on some trading systems replace human thinking as in a purely automated trading system or robotic trades which some are being touted or marketed as to be very good with no input needed from the trader?

But again, we are running ahead of time.

In the upcoming Part 3 of this continuing series, we look at the actual reality of this historic game in 1997 and by understanding history and its evolution, traders may gain a better insight on how they can use automation, algorithm trading and “artificial intelligence” programs in their actual trading plan and learn to manage their shortcomings as well.

Meanwhile, consider joining and networking with us at mPower Algorithm and mPower Trading and learn more about our specialized approach to trading using big data analytics and algorithm.