Over the past decade, the belief that artificial intelligence could solve the complexities of the stock market has spread like a wildfire. The notion that humans lack the capacity and capability compared to machines, who will, without fail, consistently beat the market over time. By simply programming a machine, it will produce the ultimate formula making you filthy rich in the process. A radical change in society where anyone can make money, but not just a stable income: a modest fortune.
Unfortunately, though, this is a mere fantasy.
There’s a major flaw in algorithms built solely to predict future market moves: they don’t. They only respect the technical aspects of an asset by taking into account past price movements, avoiding any consideration for future fundamentals. Any veteran trader will tell you the market isn’t there to give away free money. Instead, it’s a competitive environment punishing anyone — or anything — who tries to make a quick buck by trading on reactionary information already priced in.
Technical analysis alone will not make you money. In fact, the myth that it does has fueled an entire industry which preys on the vulnerable: As the homepage of many online brokerage websites illustrates, up to 96% of foreign exchange traders have fallen for the trickery. The truth about the brokerage industry is it makes money when its clients lose. So when your broker offers you a plethora of trading algorithms to choose from, the alarm bells should be ringing.
Still, you may fall for the con, because the trickery itself is seductive: Let the algorithms do everything for you, sit back and relax until you can retire. All the algorithm has to do is choose the right direction: either buy or sell, right?
Wrong.
In reality, feeding an algorithm with data based purely on technicals is the equivalent to putting on a blindfold and aiming at a dartboard. You hit the board 1 out of 10 times, but the rest hit the wall.
The buy or sell illusion is an anchoring effect: a cognitive bias discovered by the renowned psychologists Daniel Kahneman and Amos Tversky where your mind tricks you into believing your chances of winning are much higher than they actually are, due to being presented with a binary choice.
The stock market is one of the most complex systems we’ve created as a species and it cannot be beaten all the time. It’s the collective decision making of not just humans, but also machines, algorithms, and algorithms predicting what other algorithms are going to do next — an infinite loop of complexity. And when you multiply the probability of all these inputs together, the chance of succeeding is miniscule. Realistically, your odds are way less than 50%, and, in some cases, even less than 1%.
It’s clear by now that the complexities of the market can overwhelm a human, but they can also overwhelm machines as they have yet to counter massive market fluctuations. When they do occur, operators are forced to switch off the algorithms and allow human traders to take over. The modern market environment has become so dynamic, machines have failed to protect against huge standard deviation moves associated with black swan events.
For example, in 2015, the foreign exchange markets were a non-volatile asset class. All the major G10 currency pairs were rangebound, moving a few hundred pips here and there. For the EUR/CHF currency pair it was a quiet start to the year until January 5th when the Swiss National Bank (SNB) unexpectedly abandoned its cap of €1.20, causing a colossal intra-hour move of 20%. In a matter of minutes, hedge funds blew up, and retail traders lost a fortune, but the machines did too.
Not only are machines incapable of predicting a black swan event, but, in reality, they are more likely to cause one, as traders found out the hard way during the 2010 flash crash when an algorithmic computer malfunction caused a temporary market meltdown.
Ultimately, A.I is doomed to fail at stock market prediction. Beating the stock market over time, however, is possible. The solution lies with us because we humans have an edge. We have the ability to make informed decisions by analyzing future catalysts of an asset, and the reasons why they will move the price up or down — a strategy artificial intelligence has yet to beat us at.
Success in trading, like in any other discipline, requires hard work and extensive research, but this only results in having a slightly better chance of succeeding. With the best traders only getting up to half their trades right, this shows that if we humans have failed to decipher our own collective minds, then A.I doesn’t have a chance.
