Can Algorithmic Or Automated Trading Beat Human Trading?

fxfarmerashik · April 6, 2019

Hi guys, automated trading or algorithmic trading is a gift of modern science. Algorithmic or automated trading using Artificial Intelligence (AI) technology can undoubtedly be very useful for detecting market signals.

Because of this, traders become more profitable in less time. But the question is: can automated trading or algorithmic trading beat a human trader? So today, I am going to write about this topic.

Therefore, without wasting time, let's start.

First, it is worth mentioning that Wall Street relies heavily on algorithmic trading, especially in the stock market. However, do not forget the important aspects - the entire AI (artificial intelligence) -based negotiation process - involving large sums of money - is ultimately traced by humans, who act as supervisors at different stages and in different periods.

While it is true that human factors control all markets, many institutional investors prefer to implement several automated trading tools to reduce the risks associated with emotions.

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Last week, Bloomberg announced that Ashok Krishnan, Head of Automated Trading at the Global Markets Division of Bank of America, had collaborated with Morgan Stanley's Phil Allison and UBS's Mark Goodman to promote and develop business-centric machines. trading of bonds and currency pairs stocks.

This shows that trends prevail even in markets that traditionally refuse algorithmic trading. Some people think that, overall, humans are winners. If you do not believe it, you can ask your algorithm to try to defeat Meir Barak, the brand's founder in his direct trading room.

Experienced traders and best-selling author of "The Market Whisperer", he stressed that active trading was not done for robots. Barak inspires day traders via your YouTube trading channel, calling for active involvement in the trading process.

Automated trading conquers the stock market in real terms, but this is the problem: this concept can be applied to institutional investors with long-term goals. Daily traders and even swing traders have to be somewhat skeptical about the idea that it's possible to organize multiple apps and sleep, because the money will flow.

The concept of passive income seems interesting, but active trading requires a lot of involvement and even pressure, especially for beginners. Let's compare the daily negotiation process with problem solving - no systematic approach has been determined for a given problem.

If it is a calculation problem with many limitations, the AI will solve it according to a predetermined set. However, the weakness of AI is that it will not be able to build the whole context of the problem - it will not understand that restrictions are restrictions.

Artificial intelligence may be ideal for automating multiple processes, but it can not realize the context in the same way that it can not realize itself - we are far from singularity, are we? Humans are very good at understanding the context of different scenarios and how they can affect certain markets or assets.

Context is not an intellectual problem but an emotional problem and, as we all know, all markets are ultimately motivated by emotions. If you take the time and look around, you will easily notice that we are constantly dealing with people in the world who are by definition spontaneous and unpredictable.

So the context of different things always changes. Machine learning and artificial intelligence usually apply to large data sets, which involve an extraordinary amount of information. Although this may help traders to identify market signals based on programmed sets and those established among a large number of financial instruments.

It is important to understand that the relationship between these instruments is changing and that IA is not always precise, even to find good entry points. , not to mention the active trade. In addition, some AI-based models may work well during certain market cycles, but they will eventually fail at the end of the cycle.

The stock market is known for its volatility, internal variety and spontaneity. This is why it is quite difficult to configure the AI to apply a set of features to two or more different titles. Nobody denies the fact that there are strong correlations, but the situation becomes tricky when the context is not understood.

The AI-based model could perhaps explain and analyze perfectly the behavior of a stock while avoiding to do the same thing with the other stock. This is actually what happened to the Black - Scholes model.

The formula was implemented in the late 1960s by Fischer Black and Myron Scholes, who created an investment company on the model they had developed.

This has worked well until market conditions change and they lose a considerable share of investor funds. Note that this example is about the investment world, but with regard to day trading, things are even more difficult because of the short-term volatility.

So, do you agree with my opinions on this topic? And let me know if you want me to cover everything for you.