With the emergence and growing popularity of ChatGPT, many retail investors are increasingly pondering: Can AI trading in Forex be effectively used? To these traders, the potential of artificial intelligence technology seems boundless, with the prospect of generating consistent income through its application. But is this really the case and what will Forex AI Analysis bring?
Artificial Intelligence in Forex Market
The history of neural network applications in financial markets began long before the advent of ChatGPT and its counterparts. As far back as the early 2000s, NeuroDimension offered the NeuroSolutions package, allowing for the graphical creation of sufficiently complex neural networks and their machine learning. It enabled the generation of DLL libraries and automation files that could be connected to almost any trading terminal known at the time. In the early versions, the package included the TradingSolutions application (which could be purchased separately), designed for analyzing price charts and building trading robots based on neural networks.
The solution required certain knowledge from the trader and enjoyed considerable demand. However, with the mass influx of retail investors with minimal training levels into the markets, it became less sought after. Nevertheless, the same fate befell many other software packages. The use of neural networks and machine learning remained the prerogative of professionals.
Today, they are typically used by institutional investors: hedge funds, pension funds, major banks, etc. These market participants have long appreciated the potential of artificial intelligence in solving tasks related to big data analysis and the search for implicitly expressed patterns and connections. It is worth noting that, according to some data, over 65% of the algorithms used by them in stock, futures, and Forex trading are built with the involvement of AI.
Note! Artificial intelligence used in trading on financial markets has little in common with generative systems, which have gained immense popularity thanks to ChatGPT. Large language models are not applied in it, making it more specialized. As a result, end users get a less universal but more accurate tool for making trading decisions.
With the improvement of component base and machine learning algorithms, the use of artificial intelligence in trading, including Forex, is inevitably expanding. So what can AI (let’s conditionally call it “trading AI”) do today and in the future?
Automated Forex Trading Analysis
Any trading decisions in Forex are made based on market analysis. This is where AI is best suited. It can be used for:
- Analyzing price charts and identifying characteristic patterns for entering trades and closing positions. The history of price changes for each trading instrument can be viewed as Big Data, and AI excels at finding even non-obvious patterns in such data sets.
- Technical analysis and determining optimal parameters for setting indicators. By using artificial intelligence, prospects for increasing the accuracy of both mathematical models themselves and decision-making based on indicators are opening up.
- Fundamental analysis. It is believed that a trader cannot fully apply this toolkit since they cannot consider the impact of all factors on the market. However, artificial intelligence can do this, able, for example, to find even the dependence of currency exchange rates on the average academic performance of high school students.
Today, artificial intelligence is mainly used for automating analysis tasks. In many cases, it only generates signals for market entry and trade closure, with the final decision made by the trader. According to the Refinitiv “FX Workspace Survey” in 2022, about 43% of all traders (not just professionals) believed that AI is effective in market monitoring and were willing to use such tools.
Robotic Trading in Forex
In some cases, developers of artificial intelligence algorithms for financial markets go further and build fully automated trading systems based on it. In this case, neural networks are used not only for market analysis but also for determining the probability of achieving a positive financial result from the trade. Based on this, decisions are automatically made to open or close trades.
Such trading systems are typically used by major market players who have to manage hundreds or thousands of open positions simultaneously. This measure is somewhat necessary because a trader or even a team of traders cannot handle such a workload.
Another application of fully automated trading systems is high-frequency trading (HFT). For example, when transitioning to HFT, the holding time of an open position is reduced to seconds, and in some cases, to fractions of a second. Naturally, humans cannot operate at such a speed in making trading decisions, but AI Forex trading algorithms excel at it.
However, even in regular trading conditions, the use of artificial intelligence can be beneficial. At the very least, allowing AI to make trading decisions will help reduce the number of subjective errors caused by trader psychology. In the aforementioned Refinitiv “FX Workspace Survey,” no less than 36% were willing to work with AI-based trading robots.
AI-Powered Forex Strategies
Another direction of using artificial intelligence is the creation of complete trading strategies. It should be understood that a trading strategy is by no means just a trading system. The latter is a component of the former. However, besides it, there are equally important components, such as optimal capital management and risk management.
When using complex algorithms, traders may not always adequately assess the level of risk. This is especially characteristic of highly volatile markets, such as Forex. Here, currency exchange rates can change very quickly, and predicting price reversals is not always successful, nor are the magnitudes of price movements. To calculate risks, well-founded volatility forecasts come to the forefront, compiled taking into account as many influencing factors as possible.
It is quite difficult for a trader to solve such a task. It can be delegated to AI, which uses its own algorithms to track and predict market fluctuations. Predictive analysis with monitoring of significant volumes of data is one of the promising directions of its use. According to the aforementioned study, about 40% of companies involved in currency trading have already assessed the possibilities of artificial intelligence in making such forecasts and are using neural networks for risk management.
The possibilities of applying AI in the Forex market and other financial markets are far from being exhausted by the listed applications. Data intelligence can also be used, for example, in training professional traders and analysts. However, artificial intelligence is far from being a perfect tool, at least for now. Those who work with it must also take into account certain risks.
Potential Risks of Using AI in Trading
The use of artificial intelligence offers traders numerous promising solutions. However, applying automatic and automated systems based on AI should be done with extreme caution. While tackling many tasks, it can introduce additional risks into trading, sometimes quite significant ones.
The Issue of Training on Historical Data
It’s no secret that AI systems undergo preliminary training on historical data before being applied. However, the market is volatile, and patterns identified earlier do not always work at the current moment, let alone in the future. It’s worth recalling the most common phrase in disclaimers and risk notifications: “Past performance is not indicative of future results.”
As a result, forecasts obtained using neural networks may be inaccurate and fail to account for the influence of important new factors. Since machine learning always relies on actual material (i.e., events that have already occurred and the markets’ reactions to them), the probability of a serious error is never zero. Of course, the fresher the datasets used for training, the more accurate the resulting analysis or forecast becomes. However, there is no guarantee that AI will react adequately to sudden changes in the economic or political situation.
Problem of Algorithmic Errors
Artificial intelligence is not perfect, nor is it actually intelligence at this point. The key to its success lies in the rapid processing of significant amounts of information and in finding the optimal result (answer) given a specific set of input data.
However, algorithms and machine learning programs reflect developers’ approach and their own opinion, which sometimes lack a considerable subjective component. Naturally, this leads to errors in algorithms and final results.
Furthermore, with the growing popularity of AI systems, including for trading, errors related to the speed of development are also possible. Although they are easier to rectify, they can still have a negative impact on the final results.
There is no need to harbor illusions or idealize AI systems. In trading on the markets, there have always been, are, and will be winners (making a profit) and losers (incurring losses). Even the most advanced artificial intelligence cannot change this, nor can it make everyone winners in every trade.
Pros and Cons of AI in Forex
Using artificial intelligence systems for trading on Forex has its advantages and disadvantages. Among the advantages of traders working with AI are:
- Automatic analysis of market information on a large scale.
- The ability to build trading robots that make decisions on opening and closing trades and even consider capital management and risk requirements.
- Absence of subjective components in analytics, forecasts, and trading signals (ideally).
- High speed of decision-making, enabling the use of AI systems even in HFT.
- Self-learning systems, allowing them to adapt to changes in market conditions even without human intervention.
Among the disadvantages, it is important to note:
- Training on historical data, requiring a certain amount of time to adapt to the real market situation afterward.
- Human influence on neural network models, algorithms, and machine learning programs, leading to errors influenced by subjective developer views.
- Inevitability of development errors due to the increasing interest in AI. New products are almost certain to contain a significant number of such errors.
- Significant cost of AI-based solutions, requiring high levels of expenditure on both hardware and training, as well as specialist support.
- Similarity of most AI systems in algorithms and decision-making speed, which has already led to a significant increase in market volatility and may lead to large price fluctuations in the future.
Overall, in the near future, AI systems are expected to become more accessible to traders. It is anticipated that this will increase the speed and efficiency of decision-making. However, decisions made by such systems without human control may prove to be unsuccessful. Therefore, what to expect from Forex AI analysis remains unclear for now.
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