# Applying Artificial Intelligence in Cryptocurrency Markets: A Survey
## 4 Discussion and Potential Future Research
### Integration within Cryptocurrencies or with Other Financial Assets  
Recent fundamental changes in cryptocurrency markets indicate that they are increasingly integrated with other traditional financial and economic systems. For instance, Coinbase, one of the most popular cryptocurrency exchanges, went public on the NASDAQ exchange, and there are an increasing number of ways in which cryptocurrencies can be used to pay for services and products. This evidence strongly indicates the acceptance of cryptocurrencies by existing financial bodies as well as the general public. Since financial and economic systems continuously and dynamically evolve, investigating the integration of cryptocurrency markets with other financial assets can be of significant benefit. Internationally, it is important to study the financial impacts of the price of traditional assets and commodities on the price of cryptocurrencies, and vice versa. In a similar fashion, the question of whether or not the prices of cryptocurrencies can be predicted based on changes in the prices of other financial assets (e.g., oil and the US dollar). Investigating the influence of financial markets and political sentiments on the price of cryptocurrencies and whether or not cryptocurrencies can influence traditional assets such as oil prices, is of significant interest.  
In addition, the influence of different cryptocurrencies on each other warrants further attention and investigation. In particular, the emergence of government-based cryptocurrencies, governmental restrictions on trading and using cryptocurrencies in some countries (e.g., China), and preferences regarding certain coins based on their liquidity ease, may create an influence from one coin to another. Furthermore, creating a profitable portfolio of different cryptocurrencies needs a better understanding of the interactions and influences between the coins. The necessity of attending to these gaps is evident in the recent changes in the cryptocurrency markets. For example, the market capitalisation of altcoins has increased substantially in the last three years, where it has surged from 500 million dollars in January 2019 to 1.5 trillion dollars in December 2021 (www.coinmarketcap.com). Therefore, the question of whether leading cryptocurrencies such as Bitcoin and Ethereum influence the prices of other altcoins needs to be studied. Modelling approaches such as Bayesian networks [103] can be used to gain insights by modelling causal relationships between cryptocurrencies and other financial systems, and among cryptocurrencies themselves.  
Although studies have been undertaken to investigate integrating cryptocurrencies within other markets, they are mainly based on financial and economic models, such as a gold standard model applied in [1] to study the price of Bitcoin, or in another study GARCH models (statistical models) are widely used in the financial sector. Moreover, there are other gaps in the literature that need further attention. One impending issue is that of dealing with big data, where a sound approach from AI can be of great benefit. Additionally, statistical models used to date place a strong emphasis on explainability rather than accuracy. Therefore, selecting an appropriate AI framework that is accurate and explainable considering feature engineering, fitting, resampling, and testing is crucial. Furthermore, designing trustable AI tools that are capable of predicting market movements, price changes, and profitable trade strategies is vitally important. In particular, such a tool should be able to take as input different types of data including price histories, information from social media, news items from international political interactions, governmental decisions from economically influential countries, and expert opinion.