95 percent of bitcoin traders lose money in the market. Assume you are a primary school math instructor. You have 30 students in your class and one day, you ask them how much they will receive in case of multiplying 25 by 80. Only one child has the correct response, it does not matter the year or how old they are. Crypto traders are in a similar situation. However, the result would be different if they had the opportunity to use a calculator, as well as if traders are allowed to use additional help.
In 2018, there was plenty of information available about the spread and advancement of artificial intelligence, which was quite vague from the beginning but its wide implementation in many different fields has raised awareness about it. Videos of Elon Musk or Stephen Hawking warning of the risks of unregulated artificial intelligence flooded the internet at that time. However, there was also information on how to utilize AI to diagnose cancer.
The first one was making the general public stay away from the innovation that nobody knew exactly how it could be used, however, the second one raised an important question to why not utilize something that is clever enough to be a respectable opponent of cancer against the Bitcoin market as well? Because it was vivid that the new system had big capabilities. For more than 400 years, equities have been traded. Traders have gathered enough information for the next generation of investors throughout this period.
Crypto market and AI
The cryptos did not exist until Satoshi Nakamoto, an anonymous individual, posted bitcoin’s whitepaper. Furthermore, they did not trade using artificial intelligence. Such technology necessitates a significant amount of research and development. Not the kind of information that is possible to pick up by viewing a 20-minute Youtube video every day.
The question that comes into mind is how it is possible to make those two work together. Many people are attempting to use the Machine Learning of AI to finance. Pattern recognition is a strong suit for AI. Models can be trained to distinguish between an apple and a pear. So the idea is that if the AI can spot patterns in price data, it can predict which way the price will go next. Now that the AI has recognized the pattern, you may purchase and profit.
Financial data has a variety of statistical characteristics that necessitates a unique approach. Machine Learning models are hundreds of times more complicated than theory-based models, however, there is a list of EA trading robots that have provided professional traders with great help and the trading process is not as tiresome due to the technical assistance as it was before, but it is also true that it requires special knowledge how to use it properly. They are a lot more difficult to create, test and deploy. They are not the result of human reasoning. Human researchers have never discovered patterns using solely their intuition. The amount of data and noise available is simply too much for the human mind to comprehend. This is closely connected to Lopez de Prad’s idea of “microscopic alpha”. The simple connections that might be discovered by human intuition have already been exhausted and more advanced approaches are becoming more necessary to continue extracting alpha.
The turning point
One of the first companies that started this innovation was the b-cube project. The b-cube project has been accepted into Central Supelec’s incubation program. They also might be able to form a collaboration with the Paris-Saclay University as a result of this initiative. Which is the world’s number one mathematics university. This means that they will have access to the university’s quantitative finance lab, as well as lecturers and interns. Many employees got into the company through this partnership.
Usage of AI in crypto trading
- Sentiment research based on social media and news sources. These data are absorbed, stored, filtered, and processed in real-time using NLP (Natural language processing). They assess market sentiment towards a specific coin. The market is heavily influenced by market mood, which may be either good or negative, greed or fear.
- Machine learning is used to absorb various negatively correlated characteristics and recognize trends in different dimensions, which could be related to volume and price sentiment or blockchain-related data, which consists of the speed of mining, size, and movement, transactions, movements on the wallet of the whales, etc.
- Rather than contemplating the craft of generating individual strategies in an artisanal manner, the company chooses to generate them in batches in an industrial setting, using a pipeline that allows for appropriate testing, deployments, and selection. Those are also called meta-strategies.
They made a profit of +15.31 percent from March to July 2020. But then there was a significant jump. They are already at +46.1 percent on August 9th. This was already a decent result. From March to October 2020, they made a profit of +65.84 percent.
The company might now use the same Bot that has helped them by more than 60% in the previous eight months. This will need a Finance Futures account as well as a 59Eur monthly subscription. API connectivity is required for the Binance account.
Finally, we can state that making a steady profit in bitcoin markets is doable. This is no longer exclusive, but rather a product offered to stores. Examine previous outcomes to see how you might have fared on your own account. So far, all of the details about the achievement are available on the internet. However, it should be noted that trading cryptocurrencies involves its own risks and the information that was provided in the article does not directly mean that the AI implementation guarantees 100% profit. The decision on whether to engage in the industry or not should be made depending on the decision made with the help of a financial advisor.