How Artificial Intelligence and Machine Learning can help us boost trading?

Over the past 60 years, AI and machine learning have played an important role in the real world of science fiction. While this technology is still working to improve with its ambitions, it has already greatly improved our lives.

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The word AI has been misused and used unnecessarily, making us think that everything from a taxi app to a toothbrush runs through it. In fact, the technology behind these inventions is changing the world now. It speeds up diagnoses in hospitals, move cars without drivers, create music and write for novelists.

The purpose of AI is to replicate human level intelligence and that's the goal that people haven't reached yet. It's more accurate to talk about "machine learning" than AI. Machine Learning (ML) is a technology that teaches a machine to perform better when you skillfully augment its given data. The amazing thing about this is that the hard work that people have to struggle with during their daily routine can be done automatically.

Now with all the definitions that have been carefully crafted, let's just ask ourselves one question that bothers us like traders. What about trading and financial investing? Can ML conquer these areas?

The trading field is a bit difficult to apply to ML as it involves not only rational factors that affect price fluctuations but also a lot of psychological, environmental, political and economic changes that take place in the market and create ups and downs. Engineers can teach machines how to predict continuity and results by analyzing moment-to-moment data. For example, buying and selling one stock over a decade. But what should they do with other helpful information?

ML experts combine learning, emotional analysis, and scientific graphs to predict stock trading results. Sensitive signals analyze news headlines or complete articles in social media and news agencies and link them to sales data collected through learning.

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First, learning the machine and then extracting meaningful words and no attention to noisy information. Then through the science graph, it studies how to allocate these words in stock in the questions. For example, a simple search won't connect Bill Gates and Microsoft Stock, while knowledge will have a graph. Thus, even some of the things mentioned in the article that are related to the stock can be analyzed in the machine as meaningful data.

This whole process requires a lot of time and resources. But it is already worth the effort. Indicators of investor sentiment are sold to banks, pro-traders, hedge funds, social trading platforms and so on.

It should always be kept in mind that trading signals are not a direct call in a process but an up-to-date information that inform you of market opportunities. Your risk depends on the tolerance, the investment horizon, and the trading strategies you stick to. It's still up to you to decide which signals to follow.

Traditionally, indicators are set by analysts. But when it comes to data analysis, ML has a huge advantage. It can pass a large number of metrics through various means in a relatively short period of time. Nowadays, if used correctly and responsibly, ML analyzes most of the past data and can generate trading signals in a more lasting perspective.

However, many companies use ML capabilities through scans and scanned data produces more indicators all day long 24/7. According to experts, you should not just agree to these notifications and avoid them when making market decisions. Therefore, if followed wisely, trading indicators developed by ML can improve your risk / profit ratio.

At some point, trade becomes normal. You do more or less the same thing every day, and your mind starts to see them jumping back and forth like sheep. It can make your brain sleepy or exhausted. Your eyes may glaze over, and you may not notice when the transaction is not as smooth as it should be.

With ML, you will never face such a hassle! A machine is taught to analyze millions of samples, and when a slight discrepancy appears, you will be notified. In most cases, abnormal patterns are dangerous. The ability to explain unusual behavior can save traders from losing money when investing in large amounts.

In addition, ML can help you deal with personal data. When new traders create an account with a broker, there can be counterfeiters with fake identities and malicious intent. With applicable AI and ML, authenticity verification is faster, which is why international brokerages such as accept more and more new traders and prevent identity theft.

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High frequency trading (HFT) is complex algorithmic trading. The computer processes a large number of orders in seconds and helps to make a profit from the slightest difference in prices. These algorithms are beyond human capabilities. This is the field where ML is making an excellent entry with its fast and accurate calculation capabilities.

The supercomputer has detected features that indicate a future increase or decrease in price movement and bids according to this forecast. Unfortunately, HFT exists in the universe and cannot be accessed by day traders.

Who will win? AI and ML are pushing our heels - that's the reality and the current reality. In 2021, there is no place for "AI for AI". The technologies under consideration have moved from experimental foundations to everyday life and have been able to gain rapid dominance in many areas.

However, due to its complex nature, there is still a bit of blood in trading when it comes to machine learning and artificial intelligence. Computers are helping to process large amounts of past data and are learning to replicate the consciousness of traders in patterns. The latter is a difficult task, so it requires a lot of time and resources. But already experts can offer additional insights into the market by processing social media posts, financial statements, and news. They teach machines to separate relevant and irrelevant information for long-term strategy and to generate trade signals.

ML is used to eliminate fake identities and identify counterfeiters. In addition, technology is not suitable for high frequency trading.

Right now we are cooperating with machines and there is no animosity involved. What's next - only time will tell?

Thank you for reading! Stay Safe!👋😌

References:

1-https://idapgroup.com/blog/machine-learning-for-trading/
2-https://www.nanalyze.com/2020/05/machine-learning-for-stock-trading-strategies/