Exploring the Challenges and Prospects of Artificial Intelligence in Automated Cryptocurrency Trading
We should start from acknowledging the differences between general AI and expert AI systems. While the former is still decades away according to many specialist and computer scientists, the latter is already here and disrupts many industries as you are reading this article. Expert AI systems are highly specialized algorithms that can perform extremely well in certain fields and very narrow domains.
For example, an AI crypto trading system trained on the data about the history of the market and asked to identify the best strategies, given that the circumstances do not change, will provide a way better assessment and analysis to give you a very good solution. The problem is that such crypto artificial intelligence traders will most likely produce many false positives and hallucinations.
Finding the right balance between blindly believing the outputs of such expert systems and relying on your own instinct will be one of the most important qualities of a successful retail trader using AI crypto trading systems. Let’s talk which issues concern developers and potential users right now.
- Selecting data sets. It is hugely important for an Artificial Intelligence crypto trading system to learn using the best data with all the nuances that must be incorporated in the training data set. It will be hard to get the right type of data, relevant additional information, and compile it into something that can be fed to an expert system.
- Hallucinations. One of the biggest problems with machine learning in crypto trading, or any other field for that matter, is that AI can produce weird outputs as a result of still unknown internal processes. Any machine learning system can simply make up something out of thin air. While it is a fun thing to observe for something like ChatGPT, it cannot be tolerated when it comes to finances.
- Emergence. One last thing that should be accounted for is emergence which is a property of a system that was never intended to be obtained by a system during the training process. Again, it can be quite exciting to see for a developer working with AI systems, but it can be detrimental for financiers who will suddenly see their systems performing audits of their finances instead of analyzing the market.
These are general issues that are currently bugging researchers, but there can be industry-specific issues that we cannot foresee. The implementation of AI systems in contemporary financial analysis can be quite challenging. We simply don’t know everything about machine learning systems and how they arrive at certain points of their evolution.
Understanding the Role of Artificial Intelligence in Automated Cryptocurrency Trading
With the rapid advancement of expert AI systems and industries caving in to make room for the new technology, it is inevitable that the crypto domain will succumb to artificial intelligence cryptocurrency trading products very soon. It is not a question of “why”, but a question of “when”.
Algorithmic trading systems (ATS) have been used by large financial institutions from the 1980s. Automation as a tool became available to individual retail traders with relatively small portfolios just two decades ago with the expansion of the Forex market. The last five years were quite a journey for people interested in using automation in financial markets.
Contemporary automation crypto trading is not as sophisticated as future AI-driven systems. An automated trading system still relies heavily on a wide range of factors and human inputs. Let’s look at what an ATS looks like for an individual retail trader today:
1. A trader must come up with a technical analysis strategy that can be deployed on a widely accessible analytical platform like TradingView.
2. A trader must choose a good automation vendor and set up a bot (script) that will receive signals from the analytical platform and perform actions as written in its instructions.
3. The bot will connect to a centralized exchange and, on your behalf, place orders with the addition of take-profit and stop-loss commands.
As you see, a human is involved in each step. You need to decide how the system trades, where it gets signals from, and where it places orders. A trader must make decisions about every single aspect of the system which means that automation is still just a very limited tool. It is an impressive instrument and should be used by people who want to achieve success in the crypto industry, but it is still an instrument incapable of making any decisions.
When it comes to machine learning, crypto trading starts looking a little bit different and slightly scary. It is possible that expert AI systems will take over the decision-making process which means that those retail traders who use the best software and best data sets will always be one step ahead of their competitors.
It is quite easy to foresee a future where AI crypto trading turns into an economic war between various expert AI systems. Whatever we do from now on, we cannot stop the evolution of these systems. It is imperative for all users to carefully observe the industry and jump on the first opportunity to use the latest systems before they become mainstream.
How AI can Help Optimize Cryptocurrency Trading and Improve Performance
The competition between these trading systems will be ferocious and brutal. Up until now, algorithmic crypto trading was still just a way for smart retail traders who know how to build great technical analysis systems to trade efficiently. With the development of artificial intelligence focused on financial markets, it is possible to train systems that will easily outperform even the best analysts.
Here are several important areas where the influence of AI for crypto trading will be most noticeable:
- Analytics. The commonly adopted approach for building an ATS is to find a good technical analysis strategy that can identify good moments to enter the market and execute an order instantly. It means that you need to find a TA algorithm and use it on short time frames to utilize the power of automation to its fullest potential. Imagine a world where a system can simply start using the data at hand and producing thousands of micro signals. Computers will react instantly and the market will turn into a nightmare for humans to navigate with millions of orders open at once.
- Portfolio optimization. One of the aspects of contemporary trading that can be automated fairly easily with expert AI systems is portfolio management, especially when it comes to sophisticated multi-faceted systems like statistical arbitrage. A well-trained AI expert system will quickly identify weak spots in the portfolio and create hedging orders while liquidating risky assets before they become a liability. Such automated cryptocurrency trading strategies will be absolutely necessary in a rapidly changing crypto market.
- Bridging the gap between platforms. Right now, you need to perform multiple tasks on different technological platforms to create a fully automated crypto trading system. For example, you need to write a strategy on TradingView, create new scripts on something like WunderTrading, and set up an API connection with a centralized exchange. Imagine an automated Bitcoin trader that can do everything on a single platform. The battle between service providers will be legendary in scope.
The Challenges to Implementing AI Automated Crypto Trading Systems
The implementation of an expert system in a trading strategy will be quite challenging for many reasons. Let’s explore several:
- The transitioning period. Many retail traders understand how to use contemporary systems which are widely different from what an AI system will look like. Since the vast majority of serious investors are older than 40, it means that they will have even harder times adjusting to a new technology. The learning curve won’t be as steep as studying new coding languages after decades of using an analog phone, but it will confuse many veterans.
- Issues with integration. One of the challenges of an AI-based cryptocurrency trading system will be the integration in an already existing infrastructure established in the world of finances. While API functionality of many CEX platforms looks sufficient right now, it will need to adapt to larger volumes of connections and requests from users. Automation platforms like WunderTrading will surely offer their own solutions, but they will also need to work with external services that may also use AI.
- Unforeseen algo-trading risks. We all understand the risks associated with using automation. Retail traders use hedging mechanisms, diversify into different branches of automation, limit the amount of funds available to their systems, and more. However, new risks like the sudden failure of an AI system or emergence of new properties may pose a greater danger to retail traders and institutional investors as they will have less control over the actions of their trading systems.
In the future, a cryptotrader bot review will be a very useful source of data. However, these reviews will have to be performed by actually trained AI specialists. Laymen and financiers may not understand the reasons of failures and underperformance.
Exploring the Prospects of AI-Based Automated Crypto Trading Solutions
In 2012, Morgan Stanley published their report showing that over 84% of all stock trades in the US are performed by ATS. Humans are responsible for just 16% of all trades. Multiple studies performed throughout the last decade indicate that an AI expert system is capable of making correct predictions about the market (using back-testing against the market history) if it has access to a wide range of data types. Just feeding it information about the stock is not sufficient.
There is a very simple conclusion from these two facts about the contemporary financial market: system will overtake humans in every aspect of trading if it has enough data to analyze.
So far, the automated cryptocurrency traders performance analysis shows that final results depend heavily on the proficiency of human operators running automated systems. It means that people who already can trade well use automation to enhance their performance while those who do not understand how to use technical analysis systems usually fall behind or do not enjoy the same level of improvement.
While it is a good idea to hope that future blockchain-powered algorithmic pricing services will give you a good idea about what to buy and when, we can only hope that traditional methods will perform as intended when the market is decided by AI expert systems skewing the usual behavior of human traders.
Here are three very important takeaways about the future of an average crypto trading bot system:
1. AI crypto trading will be overwhelmingly popular with over 80% of all trades performed by ATS. The share of trades performed by automated systems will likely increase.
2. We will need sufficiently rich data sets to train machines on. It is possible that the information will become increasingly harder to obtain in the nearest future.
3. Machine learning in crypto trading will become an absolute necessity by 2030 (maybe, even sooner) with the advancement of the AI industry in general.
What are the Best Practices for Developing and Implementing an AI-Powered Crypto Trader?
Many experts are talking about blockchain intelligence systems that can be potentially more powerful than traditional AI systems ran on individually owned servers or in clouds. However, the keyword here is “potentially”. Blockchain networks do not provide any significant benefits to AI systems and may even hinder their expansion and learning capabilities.
We also have very good blockchain-adjacent solutions for the AI industry. For example, some decentralized platforms already provide cloud-based GPU renting services to people and companies interested in training their own AI models. Since these decentralized platforms offer their hardware to all types of users, it is possible for an individual retail trader to train an excellent AI expert system capable of outperforming everything else on the market.
We foresee several ways of implementing AI-powered crypto traders in the future:
1. Use AI-powered trading tools on a subscription model (software-as-a-service) just like we do it today using platforms like WunderTrading.
2. Train your personal models and run them from your servers. This route requires some technical knowhow, but can be uniquely advantageous.
3. Simply purchased ready-to-run solutions from the market as they become available. It is possible that these products will have additional features such as machine learning packages to expand their functionality.
Identifying the best practices of implementing AI systems in your trading strategy is quite hard right now. Many artificial intelligence systems are still months away and we don’t have anything substantial to talk about. However, the three methods outlined above will be most commonly used in the crypto industry where many individuals are already educated computer scientists or simply love the technology.
The main takeaway
Denying the fact that AI expert systems will completely overwhelm the crypto industry is like refusing to see a cliff right in front of your car. Machine learning scientists are already looking into ways to apply their findings to the world of financial markets. The transition to the new crypto trading environment will be tough on many individuals, but it will happen whether you want it or not.