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What Chess Master Garry Kasparov’s Loss to IBM’s Deep Blue in 1997 Can Teach You about Trading in Today’s Markets

A specter is haunting today’s financial markets — the specter of “algorithmic trading.”

Today, quantitative or algorithmic trading is responsible for more than half of the trading in U.S. stock markets. This development signals a fundamental shift in the character of financial trading.

It marks the rise of the importance of computers and artificial intelligence in the way the world’s most sophisticated investors make their investment decisions.

Garry Kasparov and IBM’s “Deep Blue”

I recently listened to a podcast with Garry Kasparov where he discussed his new book, “Deep Thinking:  Where Machine Intelligence Ends and Human Creativity Begins.”

Kasparov was the world’s #1 chess player for over 20 years.

He is best known to the U.S. public for losing a chess match to IBM’s Deep Blue computer in 1997.

In the interview, Kasparov concedes that human chess players today don’t have a prayer against today’s powerful chess computers.

Why?

Computers don’t get tired. They don’t get moody. They don’t make mistakes.

They are never “off their game.”

Meanwhile, a human chess player only has to screw up once to lose a match.

The same reasoning applies to trading in the financial markets.

Click here to read the full article, “What Chess Master Garry Kasparov’s Loss to IBM’s Deep Blue in 1997 Can Teach You about Trading in Today’s Markets.“

Source: Human Events

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