The past year has been witness to the unexpected revenues the cryptocurrency market has generated despite the impact of the pandemic. Despite cryptocurrencies as new entrants in the financial industry, with Bitcoin as the eldest among its counterparts in 2009, the growth spurt of Bitcoin resulted in the offshoot of other cryptocurrencies and investment platforms such as Gemini, Coinbase, BlockFi, and others. Just like in other investment portfolios, cryptocurrency investing is paired with its challenges and technical difficulties. The use of artificial intelligence (AI) in the field of the financial industry has become widespread. The following are the ways that artificial intelligence can be used for investing in cryptocurrency.
Predicting Crypto Market Trends Accurately
Volatility is considered to be one of the biggest problems in cryptocurrency trading. The past few years have seen the market price fluctuation of Bitcoin in the past few years. For instance, the Bitcoin price fluctuated by 5 percent within 24 hours from October 2017 to January 2018. Different factors affect the volatility of the market, such as how cryptocurrency is viewed intrinsically and categorising whether it is an asset or a currency. Furthermore, the uncertainty of Bitcoin has resulted in its fluctuations within the crypto market.
Currently, leading tech and business gurus and financial institutions recognised the significance of the cryptocurrency market that resulted in a huge jump in returns, which provided a cloud of certainty on the future of crypto. In addition, cryptocurrency investing became even more widespread as top financial institutions such as JP Morgan and Goldman Sachs started to offer Bitcoin and other cryptocurrencies to their private wealth management clients this year. Morgan Stanley was ahead among all other US banks to provide Bitcoin access to clients who own at least $2 million in assets. After two weeks, Goldman Sachs followed through when it released a statement that it would offer wealthier clients Bitcoin and other cryptocurrencies.
More U.S. banks and top business executives such as Mark Cuban and Elon Musk backed and recognised cryptocurrency investing. This resulted in the movement towards the adoption of cryptocurrency investing mainstream. Some US bank clients will be able to purchase, hold, and sell bitcoin through their current accounts, as reported by the New York Digital Investment Group (NYDIG) earlier in May. The collaboration between NYDIG and Fidelity National Information (FIS) to allow bitcoin services to hundreds of US banks will enable clients to engage with cryptocurrency trading in their bank accounts.
Investing has increased in its alternatives. Thus, it is no longer sufficient to use extraction, analysis, and manual research processes when targeting investments and identifying signals to engage in cryptocurrency. The emergence of AI as a tool within the financial industry will make it more powerful when combined with blockchain. AI has already been integrated within larger financial institutions such as Citi, Goldman, and Barclays, while other small and medium-sized businesses are starting to dabble with AI. For more information about cryptocurrency investing, Bitcoin Era is one of the best sites to visit!
With the rising status of cryptocurrency with its investors, AI can eliminate cryptocurrency uncertainty. Investors can use data analytics to predict and forecast crucial activities in the crypto market and make well-informed investment decisions. Data analytics uses the steps to collect, clean, process, and analyse large sets of data to provide significant views into a virtual currency. Forecast models and neural networks can be created by data scientists and developers to analyse old cryptocurrency market data and provide accurate predictions about the price of cryptocurrency at a specific time and date in the future.
Moreover, the combination of AI and blockchain is a powerful duo. Blockchain does not only record transactions but also anything of value. Data is stored and shared securely in a blockchain. Thus, this enables AI to analyse and produce insights from the historical and real-time blockchain data to produce data. Moreover, patterns in behaviour are also revealed in blockchain transactions to determine the factors that influence the crypto market. Thus, crypto investors will be able to generate predictions accurately.
Crypto Market Sentiment Analysis
Sentiment analysis combines the use of natural language and AI to analyse the opinions and sentiments of individuals about a certain topic. In the cryptocurrency market, the price of a digital currency is predicted to go up when there is an overall positive sentiment, while the price of a digital currency is predicted to go down when there is an overall negative sentiment.
To conduct the process of determining the sentiment of the cryptocurrency market, there must be a collection, processing, and analysis of large amounts of data. Sources of data include blogs, articles, news, forums, social posts, and comments. The use of AI enables the processing of large amounts of data from the web plus that of blockchain data where it can be processed and analyse the sentiment of whether it is neutral, positive, or negative. Various signals can be analysed by AI and machine learning to determine market manipulations through inconsistent behaviours observed in the sentiment indicators. Investors can determine the steps to be done with the sentiment attached to the data. Polarity, aspect-based sentiment analysis, and tone/emotion are some of the common kinds of sentiment analysis that are beneficial in interpreting the cryptocurrency market.
Aspect-based sentiment analysis. Data are categorised by the specific company or service that determines the sentiment linked to each one. Customer feedback is analysed by linking sentiments with a product or service.
Polarity. Statements and labels are analysed based on whether these are positive, negative, or neutral. Analysts and investors use the overall score to determine the trend for similar statements and labels to analyse.
Tone/emotion: Natural language processing is used to analyse the tone or emotion of the text. Different kinds of emotions that appear can be analysed.
Automated Crypto Trading Strategies
Crypto investors use AI in high-frequency strategies since AI can mimic human intelligence. Traders who act quickly on trades generate more revenues than those who are slower to execute.
For investors who are into cryptocurrency, the integration of AI has become a necessity. Innovations in the field of AI allows non-technical users to access it through a no-code environment.
If you are into cryptocurrency investing, be sure to check and research the said market because of the risks involved in it.