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4 Ways AI Can be Used for Cryptocurrency Investing

Over the past two years, the cryptocurrency market has seen unexpected but consistent returns despite the impact of the pandemic and international conflicts. Although cryptocurrencies are fairly new - Bitcoin first appeared in 2009 - Bitcoin's rapid growth has brought in its wake other cryptocurrencies and investment platforms such as Coinbase, Gemini, BlockFi and others. Regardless of their popularity, investing in cryptocurrencies comes with many challenges, including technical difficulties. In this post, we will explore 4 ways to use artificial intelligence for cryptocurrency investing.There are over 4,000 cryptocurrencies today, and new ones are being created all the time. 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 appeared, there has been high volatility and fluctuations in valuations. This has further confused retail and institutional investors and led to many emotion-based investment decisions.

Understanding the crypto market and making investments in cryptocurrencies requires a lot of time and skill. With the advent of more technology-based tools, investors and traders are increasingly turning to artificial intelligence and machine learning to make sense of investments. AI and machine learning are proving valuable in crypto markets as crypto investments are embraced by more institutional investors.

Since cryptocurrencies are backed by blockchain technology, AI can work with the blockchain to address many of the challenges. Some ways AI can be used for cryptocurrency investing include more accurate predictions, sentiment analysis on crypto exchanges, automated crypto trading, and better monetization of investments.

More Accurate Crypto Market Predictions with AI

Among the biggest problems with trading cryptocurrencies is the volatility of the market. The value of Bitcoin has proven to be very volatile in recent years. For example, from October 2017 to January 2018, the bitcoin price fluctuated by 5 percent in 24 hours. The volatility is largely due to differing views on the intrinsic value of the cryptocurrency and whether it should be treated as a digital asset, commodity, or service. Moreover, Bitcoin's future remains unclear, leading to myriad fluctuations on crypto exchanges.

In 2021, the cryptocurrency market experienced a huge jump in returns as it was recognized by leading technology and business leaders as well as financial firms, which created a sense of certainty about the future of cryptocurrencies. Investing in cryptocurrencies has gained momentum as major financial firms such as Goldman Sachs and JP Morgan now offer Bitcoin and other digital currencies to their private wealth management clients. Morgan Stanley, for example, became the first major U.S. bank to offer Bitcoin access to its clients with at least $2 million in assets in March 2021. Weeks later, Goldman Sachs announced it would offer Bitcoin and other digital currencies to wealthier clients.

As cryptocurrency investing gains recognition and credibility from the largest U.S. banks and top executives like Elon Musk and Mark Cuban, it continues its path toward mainstream adoption. In 2021, New York Digital Investment Group (NYDIG) reported that customers of some U.S. banks will soon be able to buy, hold, and sell bitcoin for the first time through their existing accounts. NYDIG has partnered with Fidelity National Information (FIS) to offer bitcoin services to hundreds of U.S. banks, allowing customers to buy, hold and sell bitcoin through their bank accounts.

With the increase in investment opportunities, manual research, extraction and analysis processes are no longer efficient when it comes to identifying investments and buy/sell signals. AI is an emerging tool in the financial industry and is becoming even more powerful when combined with blockchain. Larger financial organizations such as Goldman, Citi, and Barclays have already integrated AI into their workflows, while small and mid-sized firms are also beginning to implement AI.

Given the popularity of cryptocurrency investing, AI can help overcome the uncertainty of cryptocurrencies. With powerful data analytics, investors can predict important events in the crypto market and make informed investment decisions. By collecting, cleansing, processing, and analyzing large amounts of data, data analytics can provide valuable insights into a digital currency.

Data scientists and developers can create neural networks or predictive models to analyze historical crypto market data and make accurate predictions about the price of a particular cryptocurrency at a specific date and time in the future.

Moreover, AI with blockchain forms an even more powerful combination. Blockchain digitally stores not only transactions, but everything of value. Because Blockchain enables secure storage and sharing of data, AI can be used to analyze and generate insights from historical and real-time Blockchain data to generate value. Blockchain transactions can also reveal behavioral patterns that help understand drivers in the crypto market. Investors will then be able to make accurate forecasts for cryptocurrencies.

Crypto Market Sentiment Analysis

Sentiment analysis refers to the use of AI and NLP 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?

With the rise of cryptocurrencies, AI is becoming more necessary than ever. 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 create and deploy AI models without writing code. No-code AI platforms are changing the face of AI adoption at financial services firms by reducing setup costs and resource consumption. However, not all organizations are able to implement them in their infrastructure. If there is no strategy for deploying AI, implementation can be even riskier.

Four ways to ensure a successful AI implementation are:

1. creating a strategy for AI deployment within the organization.

2. internally educating the team about AI, its use, and the benefits and potential challenges of AI implementation.

3. establishing a clear process for how AI can be improved within the organization.

4. ensuring that AI systems are well protected from data leakage, compliance and security issues.

AI will never be a replacement for humans in investment firms. In fact, combining the talented skills of employees with AI can bring even more value and profitability, especially when investing in cryptocurrencies. However, implementing AI requires a strong internal team, as the humans driving AI-based processes are able to deliver more value through increased profitability.

Changing investor preferences, financial regulations and demographic trends will continue to put pressure on both buy-side and sell-side companies. AI will be an invaluable tool for companies to stay competitive and increase efficiency.

Find out how zerocodeai's no-code AI platform can help with your company's cryptocurrency investments by creating a free demo account.

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