Over the last two years, the cryptocurrency market has generated unexpected, yet consistent returns despite the impact of the pandemic and international conflicts. Although cryptocurrencies are quite new, with Bitcoin first emerging in 2009, the rapid growth of Bitcoin catapulted other cryptocurrencies and investment platforms such as Coinbase, Gemini, BlockFi and others. Regardless of its popularity, cryptocurrency investing comes with many challenges, including technical difficulties. In this post, we'll explore 4 ways to use artificial intelligence for cryptocurrency investing.There are over 4,000 cryptocurrencies today, with more created constantly. Although many people have heard of and invested in cryptocurrencies, decentralized currencies and crypto trading are still new and emerging concepts. Since the first cryptocurrency debuted there has been high volatility and fluctuation in valuations. This has further confused retail and institutional investors and has led to many emotion-based investment decisions.
Understanding the crypto market and executing cryptocurrency investments takes a lot of time and skill. With the emergence of more tech-driven tools, investors and traders are increasingly looking to artificial intelligence and machine learning to make sense of investing. AI and ML are proving to be valuable in crypto markets as crypto investing is adopted by more institutional investors.
Since cryptocurrencies are backed by blockchain technology, AI can work alongside blockchain to address many of the challenges. A few ways in which AI can be used for cryptocurrency investing include more accurate predictions, sentiment analysis on the crypto exchanges, automated crypto trading and better investment monetization.
More Accurate Crypto Market Predictions with AI
One of the biggest problems in cryptocurrency trading is the volatility of the market. Bitcoin's value has proven to be highly volatile in recent years. For example, from October 2017 to January 2018, the price of Bitcoin fluctuated by 5 percent within a 24 hour period. The volatility is largely driven by different perceptions of the intrinsic value of the cryptocurrency and whether it should be treated as a digital asset, good or service. Additionally, the future of Bitcoin has remained unclear, causing countless fluctuations within the crypto exchanges.
In 2021, the cryptocurrency market saw a huge jump in returns due to its recognition by leading tech and business executives and financial firms, sparking a sense of certainty on the future of crypto. Investing in crypto has become more prominent as larger financial organizations such as Goldman Sachs and JP Morgan now offer Bitcoin and other digital currencies to their private wealth management clients. For example, Morgan Stanley was the first big U.S. bank to offer clients who have at least $2 million in assets held by the firm to access Bitcoin in March of 2021. Weeks later, Goldman Sachs announced it would offer wealthier clients Bitcoin and other digital currencies.
As cryptocurrency investing gains recognition and credibility by the biggest U.S. banks and top executives like Elon Musk and Mark Cuban, it continues its way towards mainstream adoption. In 2021, the New York Digital Investment Group (NYDIG) reported that customers of some U.S. banks would soon be able to buy, hold and sell bitcoin through their existing accounts for the first time. NYDIG partnered with Fidelity National Information (FIS) to bring bitcoin services to hundreds of U.S. banks which will allow customers to buy, hold, and sell bitcoin through their bank accounts.
With the increase in options for investing, manual research, extraction, and analysis processes are no longer efficient when it comes to identifying investments and buy/sell signals. AI has been an emerging tool within the financial industry and is even more powerful when combined with blockchain. Larger financial organizations have already implemented AI into their workflows such as Goldman, Citi, and Barclays, while small and medium-sized enterprises are beginning to implement AI as well.
With the popularity of cryptocurrency investing, AI can help overcome the uncertainty of cryptocurrencies. With powerful data analytics, investors can predict and forecast significant events in the crypto market and make well-informed investment decisions. By collecting, cleaning, processing, and analyzing large sets of data, data analytics can provide valuable insights into a digital currency.
Data scientists and developers can create neural networks or forecasting models to analyze the historical crypto market data and generate accurate predictions about a particular cryptocurrency's price at a given date and time in the future.
Additionally, AI with blockchain makes an even more powerful combination. Blockchain keeps a digital record of not only transactions but for anything of value. Since blockchain enables data to be stored and shared in a secure manner, AI can be used to analyze and generate insights from the historical and real-time blockchain data to generate value. Blockchain transactions can also reveal behavioral patterns to help make sense of the drivers in the crypto market. Investors will then be able to generate accurate predictions on cryptocurrencies.
Crypto Market Sentiment Analysis
Sentiment analysis refers to the use of AI and natural language processing to analyze the sentiment or opinions of people about a certain topic. Within cryptocurrency investing, an overall positive sentiment on a digital currency can predict that the price will increase, while an overall negative sentiment would predict a price decrease.
To determine the sentiment of the cryptocurrency market, large amounts of varied data must be collected, processed, and analyzed. This includes news, blogs, articles, forums, social posts, stock message boards and even the comments related to them. Using AI, large amounts of data from the internet, as well as blockchain data can be processed at scale and can quickly analyze the sentiment-whether it is negative, neutral, or positive.
By analyzing various signals, AI and machine learning can identify manipulations in the market through unusual behaviors observed in the sentiment indicators. Once a sentiment is attached to the data, investors can apply the insights they found.
Common types of sentiment analysis that are beneficial in interpreting the cryptocurrency market include:
- Polarity: Polarity analysis analyzes the statements and labels them based on whether they are positive, negative or neutral. Once the overall score is considered, analysts and investors will establish a trend for similar statements and labels to be analyzed in the same way.
- Tone/emotion: NLP can be used to analyze the emotion or tone of the text. Insights are drawn by analyzing different kinds of emotions that appear.
- Aspect-based sentiment analysis: Aspect-based sentiment analysis categorizes data by the specific company or service and identifies the sentiment attributed to each one. This can include analyzing customer feedback by associating sentiments with a product or service.
Automated Crypto Trading Strategies
Since AI can simulate human intelligence, investors and analysts often use AI in high-frequency trading strategies. Traders who are able to execute trades on the cryptocurrency exchanges quickly are more profitable. High-frequency trading is a form of algorithmic trading used by investment and hedge funds where a computer will execute a large number of orders within fractions of a second.
High-frequency, automated cryptocurrency trading signals will be beneficial to maximize investments. The algorithms based on mathematical computation data, predictive analytics, and forecast methodologies can analyze the markets and buy or sell cryptocurrencies within seconds.
Most large investment banks and hedge funds already carry out high-frequency trading through automated trading platforms. Financial algorithms can provide quick and efficient analyses and help investors make the most informed crypto trading decisions. Once a pattern is detected, investors can also automate the trading process and execute high-frequency trading with cryptocurrencies.
Monetizing Crypto Insights
Crypto traders rely heavily on various signals. However, with unstructured data dominating the digital landscape, it can be nearly impossible to generate accurate signals manually. Large amounts of data must be clean, relevant, and accurate before analyzing them to uncover investment insights.
AI allows data scientists and developers to build methods that traders can use to obtain relevant and clean information on a platform. With AI's natural language processing techniques, data can be classified and extracted by specific characteristics including the currency name, document type, currency founder, and more. With AI's capabilities, data scientists can offer accurate trading insights in a manner that is understandable to non-tech-savvy traders or investors through an intuitive dashboard or interface. Investors and traders can then increase their profit using the insights gained.
Is using AI for crypto investing right for your firm?
AI is becoming more necessary than ever with the emergency of cryptocurrencies. With innovations in AI, it can also be more accessible to non-technical users through a no-code environment. A no-code AI platform provides an intuitive user interface where data scientists and analysts can build and deploy AI models without writing any code. No-code AI platforms are changing the narrative of AI adoption for financial services firms due to lower set up costs and consumption of resources. However, not all firms are fit to implement it within their infrastructure. If there isn't a strategy in place on how to use AI, it can be even riskier to implement it.
Four ways to ensure successful AI implementation include:
- Creating a strategy to use AI within the firm.
- Educating the team internally on AI, how it will be used, and the benefits and potential challenges of implementing AI.
- Setting a clear process for ways AI can be improved within the firm.
- Ensuring that the AI systems are well protected from any data leaks and compliance and security issues.
AI will never be a replacement for the people within investment firms. Combining employee's talented skills with AI can bring even more value and profitability, especially within cryptocurrency investing. However, implementing AI requires a strong internal team framework as the people guiding the AI-based processes will be able to deliver more value through increased profitability.
Changing investor preferences, financial regulations, and demographic trends will continue to pressure both buy-side and sell-side firms. AI will be an invaluable tool for firms to remain competitive and increase efficiency.
Find out how Accern's No-Code AI platform can help with your firms cryptocurrency investments by requesting a demo.
