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CRYPTOCURRENCY

The use of artificial intelligence in cryptocurrency trading

artificial intelligence

In the bitcoin market, 95% of traders lose money. Assume you’re a math teacher in a primary school. You have a class of 30 students, and one day you ask them how much they will get if you multiply 25 by 80. No matter what year or how old they are, just one youngster has the perfect response. Traders of cryptocurrency are in a similar scenario. However, the outcome would be different if they were given the option of using a calculator, as well as if traders were permitted to use additional assistance.

In 2018, there was a lot of information accessible concerning the spread and advancement of artificial intelligence, which was a little hazy at first but has gained traction due to its widespread application in a variety of industries. At the time, videos of Elon Musk and Stephen Hawking warning about the dangers of unchecked artificial intelligence were all over the internet. There was, however, information on how to use AI to diagnose cancer.

The first was to keep the general public away from the innovation because no one knew how it could be utilized; however, the second prompted an essential question: why not employ something sophisticated enough to be a legitimate cancer fighter against the Bitcoin market as well?

Because it was clear that the new technology had a lot of power. Equities have been traded for almost 400 years.  Traders have amassed enough data for the next generation of investors during the course of this time.

The cryptocurrency market and artificial intelligence

The cryptos did not exist until Satoshi Nakamoto, an unnamed person, published the whitepaper for bitcoin. They also didn’t use artificial intelligence to trade. A large amount of research and development is required for such technology. Not the kind of knowledge that can be gained by watching a 20-minute YouTube video every day.

The question that occurs to me is how those two can be made to function together. Many people are striving to finance using AI Machine Learning. AI’s strong suit is pattern recognition. Models can be taught to tell the difference between an apple and a pear. The theory is that if AI can recognize patterns in pricing data, it will be able to forecast which way the price will move next. You can now buy and profit because the AI has detected the pattern.

Financial data contains a number of statistical peculiarities that need a one-of-a-kind methodology. Machine Learning models are hundreds of times more complicated than theory-based models, but there is a list of EA trading robots that have been of great assistance to professional traders, and the trading process is no longer as tedious as it was before due to the technical assistance, but it is also true that it requires special knowledge to use it properly. They’re more complex to design, test, and deploy.

Humans have never identified patterns simply based on their intuition. The amount of data and noise available to the human mind is simply too much for it to process. This is linked to Lopez de Prad’s concept of “microscopic alpha.”  Simple connections that may be uncovered by human intuition have already been exhausted, and more advanced procedures are becoming more necessary to extract alpha in the future.

The pivotal moment

The b-cube project was one of the first companies to launch this innovation. Central Supelec has accepted the b-cube project into its incubation program. As a result of this project, they may be able to develop a partnership with the Paris-Saclay University.

Which university is the best in the world at mathematics?  

This means they’ll be able to use the university’s quantitative finance lab, as well as interact with lecturers and interns. This cooperation helped a lot of people get jobs at the company.

Artificial Intelligence (AI) in Cryptocurrency Trading

cryptocurrency trading

 

  1. Social media and news sources were used to conduct sentiment research. NLP is used to absorb, store, filter, and process these data in real-time (Natural language processing). They gauge how people feel about a certain coin. Market sentiment, which can be positive or negative, greed or fear, has a significant impact on the market.
  2. Machine learning is used to absorb a variety of negatively associated qualities and recognize trends in many dimensions, such as volume and price sentiment, or blockchain-related data, such as mining speed, size, and movement, transactions, whale wallet movements, and so on.
  3. Rather than considering the art of artisanally creating individual strategies, the company opts to create them in batches in an industrial setting, employing a pipeline that allows for proper testing, deployment, and selection. Meta-strategies are another term for them.

From March to July 2020, they made a profit of +15.31 percent. However, there was a considerable surge after that. On August 9th, they were already at +46.1 percent. This was already a good outcome. They achieved a profit of +65.84 percent from March to October 2020.

The organization may now employ the same Bot that has aided them by more than 60% in the last eight months. A Finance Futures account is required, as well as a 59Eur monthly subscription. The Binance account requires API connectivity.

Conclusion:

Finally, we can say that it is possible to make a consistent profit in the bitcoin markets. This is no longer an exclusive product, but rather one that is available in stores. Examine past results to discover how well you did on your own account. All of the information about the achievement is currently available on the internet. It should be mentioned, however, that trading cryptocurrency comes with its own set of dangers, and the information supplied in the article does not imply that the AI implementation assures a profit of 100 percent. The decision on whether or not to participate in the sector should be made with the assistance of a financial counselor.

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