The transformer of the Crypto Currency Market – Artificial Intelligence

Despite the impact of the epidemic, the cryptocurrency market has delivered surprising but consistent profits over the previous year. Despite the fact that cryptocurrencies are relatively young, with Bitcoin being the first to appear in 2009, their quick growth has resulted in the introduction of other cryptocurrencies and investment platforms such as Coinbase, Gemini, BlockFi, and others. Investing in cryptocurrencies, despite its rapid growth in popularity, comes with a number of problems, including technological difficulties.

Today, there are over 4,000 cryptocurrencies, with more being generated all the time. Despite the fact that cryptocurrencies have grown in popularity due to their huge but unexpected returns, prospective investors are still confused. Despite the fact that many people have heard about cryptocurrencies, the concept of a decentralised currency and how it is transacted is still relatively new. Furthermore, there has been tremendous volatility and change in prices since the debut of the first cryptocurrency, Bitcoin. This has further perplexed retail and institutional investors, leading to investing decisions based on emotion.

Understanding and implementing bitcoin investing requires a great deal of skill and patience. Investors and traders are increasingly turning to artificial intelligence and machine learning to help them make sense of investing as more tech-driven tools become available. As institutional investors become more interested in crypto, AI and machine learning are proving to be useful.

Because cryptocurrencies are based on blockchain technology, AI can work in tandem with blockchain to solve many of the problems. More accurate predictions, sentiment research on the crypto markets, automated trading, and superior investment insights are just a few ways AI can be used for cryptocurrency investing.

Here are four ways artificial intelligence (AI) can be used for cryptocurrency trading, thanks to the rise of AI and the proliferation of AI use cases across the financial industry.

• Analysis of the Cryptocurrency Market Sentiment

Sentiment analysis is the application of artificial intelligence (AI) and natural language processing to examine people’s feelings or thoughts on a given issue. When it comes to cryptocurrency investing, a good overall attitude on a digital currency can indicate price increases, while a negative overall sentiment can anticipate price decreases. Large amounts of varied data must be collected, processed, and analysed in order to determine the sentiment of the bitcoin market. This includes news, blogs, articles, forums, social media posts, stock message boards, and even comments on them. Large volumes of data from the internet, as well as blockchain data, can be processed at scale using AI, and the sentiment—whether negative, neutral, or positive—can be promptly analysed. AI and machine learning can detect market manipulations by monitoring multiple signals and looking for unexpected trends in sentiment indicators.

• Insights into Cryptocurrency Monetization

Various signals are heavily relied upon by cryptocurrency traders. However, with unstructured data dominating the digital landscape, manually generating reliable signals might be practically impossible. Before evaluating large volumes of data for investing insights, it must be clean, relevant, and correct. Data scientists and developers can utilise AI to provide techniques for traders to acquire relevant and clean data on a platform. Data may be classified and extracted using AI’s natural language processing techniques based on certain features such as currency name, document type, currency founder, and more. Data scientists can use AI to provide accurate trading information in a way that non-technical traders or investors can grasp using an accessible dashboard or interface. The information acquired can then be used by investors and traders to boost their profits.

• Trading Strategies for Cryptocurrency that are Fully Automated

Investors and analysts frequently utilise AI in high-frequency trading methods because AI can replicate human intellect. Traders who can execute trades rapidly are more profitable than traders who can execute trades slowly. Investment and hedge funds use high-frequency trading, which is a type of algorithmic trading in which a computer executes a huge number of orders in fractions of a second.

• Predictions for the Cryptocurrency Market that are Accurate

Manual investigation, extraction, and analysis methods are no longer efficient when it comes to identifying investments and buy/sell signals when the number of investment alternatives grows. AI has become a popular tool in the financial business, and when integrated with blockchain, it becomes even more powerful. Larger financial institutions, such as Goldman Sachs, Citigroup, and Barclays, have already integrated AI into their workflows, while small and medium-sized businesses are starting to do so as well.

The author is Tanisha Gupta.