Increase Profitability In Cryptocurrency Trading With The Help Of Artificial Intelligence

 

Table of content

• Introduction

• The future belongs to artificial intelligence

• Younger crypto market more difficult to assess

• Mining limit as a parameter

• AI can help predict cryptocurrency prices

• The future belongs to artificial intelligence

• Conclusion

 

The future belongs to artificial intelligence

Artificial intelligence is the better investor in the long run. It can process more data with machine learning and, thanks to algorithms, define patterns of price developments, recognize deviations and act faster at the given point in time. This also applies to cryptocurrencies. In the case of coins and tokens, artificial intelligence recognizes the chances of the numerous volatilities and anomalies such as over or undervaluation.

 

For the cryptocurrency market, artificial intelligence has its own parameters. In some cases, it is more difficult to evaluate than traditional markets because coins and tokens are still virtual money. Actually, other currencies are also based on a value assignment. The value of a banknote or gold bar is determined in the same way by a valuation based on scarcity and acceptance as that of a coin or token. The acceptance of central bank money and even more so of physical gold is still higher.

 

Younger crypto market more difficult to assess

On the other hand, the crypto market is much younger than others. Centuries of experience in the development of grain prices provide enough parameters or make it easier to recognize or increase new factors than in the young market for digital currencies. Thirdly, coins and tokens are still an unclear, incompletely regulated market, which makes predicting participant behaviour even more difficult. Many coins are valued, but viewed with scepticism. They quickly become objects of speculation and struggle with high volatility.

 

AI can try to consider the specific market behaviour of crypto investors. Predicting the reaction of investors to changes in the law and court rulings could help to predict the price development in an acute case. Coin investors react nervously to messages such as social media posts - tweets, Telegram posts or announcements on Reddit. In general, however, this prediction is very complex because such cases are still too rare and the causality of decisions and interactions is very complex and only clear and obvious in retrospect - or often only appears unambiguous.

 

Mining limit as a parameter

The most important and most reliable parameters for defining a normal or abnormal development of the coin and token prices are statistical in nature. Possible parameters for the price development of cryptocurrencies would be its mining limit or the computing power available for it. By analysing the number of followers of a coin and taking fake followers into account, you can also estimate the potential of a currency. A look at the GitHub platform for managing open source software projects also helps to assess a coin. The insight into the code as well as the change history helps to assess the quality and the progress of the development.

 

In addition, young, immature markets such as crypto are more volatile, but are also characterized by more stable and more pronounced trends. In the case of an ICO, a high volatility and fast resale of tokens must be assumed - the rapid increase often comes before the fall, which is not free, but only a price correction. In the end, however, a coin rate will normally move in a certain price corridor. This range is usually derived from the previous value ratio to other currencies. Further parameters are the existing trends in price development or the number of transactions in a cryptocurrency.

 

AI can help predict cryptocurrency prices

The search for the decisive factors of a price movement can be carried out completely independently by an AI. In a first step, it then checks all - including unlikely - parameters for their relevance to price development. But hybrid human-machine strategies are also more effective in the crypto market.

 

Here, economic experts and computer scientists of the AI and the machine presumably specify relevant factors. These are then examined by the AI for their relevance and the type of correlation and permanently checked, supplemented or improved using machine learning methods so that patterns of the smallest price fluctuations can also be interpreted correctly and quickly in the future.

 

Based on these parameters, an artificial intelligence defines the algorithms, to automatically and early determine the best time to buy or sell. As soon as a corresponding trading signal is issued for an abnormal overvaluation by the market observation, the transactions are carried out.

 

Numerous tried and tested methods such as Decision Tree, Random Forest, Gradient Boosting or neural networks are suitable for defining algorithms and decisions. When it comes to probability-based investments, even older approaches such as Decision Tree still do a very good job.

 

The future belongs to artificial intelligence

The future of investing in cryptocurrencies belongs to artificial intelligence. Because in the long run it will be superior to human experts, to analyse large amounts of data, to constantly check parameters of a price development and to develop and permanently validate algorithms for trading strategies.

 

However, humans should still be the trigger and be able to decide whether to use and stop AI-defined trading strategies. Every AI - including investment AI - requires safety valves: either automated through stop losses or manually, when it deems it appropriate.

 

Conclusion

Based on a number of such factors, AI algorithms develop a forecast of the next expected price developments and then make decisions about the type and timing of investments. Trend and breakout, mean reversion, volatility and market events are just a few examples of strategies that AI technologies use to invest in crypto. In order to ensure success, algorithms combine different decision-making options and - as in sports betting - also rely on opposing events in order to minimize errors in the event of a wrong decision. This balances out risks. The algorithms also control investments in derivatives, options or futures.

 

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