As anyone who has tried their luck on the stock market has found out, markets behave in mysterious ways. Even expert traders with years of experience are frequently taken by surprise and suffer unexpected losses. This is specifically true for cryptocurrency markets and similar assets, such as ICO investments.
This increased unpredictability is not just explained by the smaller size and the short-lived history of the market. High technological risk and regulatory uncertainty are factors to be taken into account. Furthermore, cryptocurrency investments are highly influenced by social sentiment, news, and rumors.
In short, traditional methods, such as mathematical trend analysis does not work anymore. In addition, the number of factors involved is too large and varied for humans to make accurate decisions. For this reason, WatermelonBlock employs Artificial Intelligence for accurate crypto market predictions.
Patterns and trends in market behavior may not be easily identifiable for human observers, but AI can make a difference. Recent advances in data processing capacity and machine learning algorithms have made trading and investment advice one of the fields in which AI can provide a significant advantage over human expertise.
The field of AI is made up of many domains and techniques. Some techniques are more suitable for trading than others, especially in the realm of cryptocurrency investment.
Since the early days of AI, historical data has been used to gain statistical insights in order to forecast future events. In terms of trading, there are patterns that repeat themselves. Some of these patterns are obvious, for example, the Christmas build-up having a favorable impact on the stocks of retail companies. However, many other patterns depend on a large number of parameters which are not obvious to human experts. Linear Regressions and more sophisticated neural networks can be trained by large sets of data to adjust weights on the importance of input parameters, in order to make fairly accurate decisions.
Natural Language Processing and Sentiment Analysis
As we have mentioned before, markets are irrational and greatly influenced by psychology. This is especially the case in cryptocurrency investment. Rumors, social media sentiment, and real or fake news are often more important than statistical trends or economic analysis.
To take into account all these factors, artificial intelligence has to process many sources of data in a variety of formats. Moreover, this data is not written in machine processable form. Facebook posts, for example, are meant for human readers and need to be interpreted in such a way.
In order for a machine to detect whether an asset is being talked about positively or negatively, it first has to understand human language. This is covered by the AI field of natural language processing, which deals with interpreting spoken and written language. Sentiment analysis, at the next level, classifies language according to its sentiment towards a certain subject. This makes it possible for social networks and other data sources to be mined for references according to certain assets, and the resulting analysis to be used for informed investment decisions. Artificial intelligence can even consider the reputation and historic accuracy of data feeds.
Deep Learning is a recent evolution of neural network-based machine learning that makes all of the above possible. Interconnected neural networks are arranged in layered architectures providing input for each other, modeling closely the functioning of the human brain.
The results of deep learning even often surprises machine learning experts and make it possible for WatermelonBlock to provide reliable AI-generated investment recommendations.