Impact of Artificial Intelligence on Cryptocurrency Trading

crypto Trading

Much of the fuss about Artificial Intelligence (AI) and Machine Learning (ML) has focused mainly on robotics, but evidence suggests that the financial sector is doing the most to harness these instruments. The widespread use of robo-advisors is a prime example of this trend. Banks also use AI to detect fraud and market manipulation and it is used by hedge funds to shape trading strategies.

The new kid on the finance block is Cryptocurrency. Millions have hoped on and continue to hop onto the cryptocurrency bandwagon since the 2017 crypto-boom. This is not an indication of greater technological understanding. Many people still have a vague understanding of how cryptocurrency works as a medium for investment. An abundance of these coins, their fluctuating valuations, and seasoned investors ' lack of faith in them do not help the situation.

While stock message boards such as Investors Hangout might help the average investor analyze the wild crypto-market, it takes AI's power to profitably navigate these murky waters. AI has the potential to significantly impact crypto investments.

Forecast and Predictions
Developers have built models based on neural networks to counter the uncertainty of cryptocurrency valuations that are becoming increasingly effective in making predictions in crypto markets. We will evaluate the prevailing exchange rates for cryptocurrencies to arrive at market forecasts every minute. The significance of the forecast depends on many variables, including the quantity of computational power, the sophistication of the mathematical models used and the quality and quantity of the data analyzed.

High-Frequency Trading

High-frequency trading is about capitalizing on price spikes. This program trading platform uses AI's power to analyze technical indicators across multiple markets and execute orders in response to market-moving trades across different exchanges. Traders can tailor a dataset of parameters on which they want the software to base its decision making. They can refine those settings and extend the dataset to improve the performance of the AI.

Sentiment Analysis

Analysis of sentiment involves analyzing data from blogs, articles, social media, stock message boards, video transcripts, and many other sources in order to understand market feelings on a given topic. Emotion can be the biggest asset or handicap for any trader and there is no denying its influence on investment decisions. AI can direct investments towards profitable trends by analyzing these emotions.

Fundamental analysis
In many ways one similarity between stocks and cryptocurrency is the use of fundamental analyzes when making trade decisions. Similar to stock, coin valuation involves the assessment of qualitative and quantitative factors, e.g. analysis of macroeconomic factors in a particular crypto-company or the whole market. At fundamental analysis AI is faster and more accurate compared to human traders.

Final thoughts

Investors have always been quick to embrace the latest technologies and AI is no exception to this. As its use extends further into banking, many questions regarding regulation and ethics have been raised. Used in the right way, AI can significantly improve a lot of people's financial situation in society, but if misused, it only amplifies the class difference between tech savvy and tech inept.

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