One of the latest development at Forex is the neural network. Neural network is the system of  self-learning based on the technologies of artificial intelligence. This network collects and analyzes data similar to human brain, by way of trials and errors, generalization and segregation.

What are the prospects of using this system in Forex financial markets?

 

What is neural network?

Neural network is a unique system of technical data analysis. Note that its operation process is similar to what people do when they evaluate cause-effect relationships and probabilities. What we see as important issues for making decisions, is also embodied in neural network system, which is evaluation of past experience. It can be compared with a child who keeps doing a puzzle, eventually making fewer mistakes.

See below how biological neural network operates

 

 

 

And this is operation principle of the multilayered network. They are very similar, aren’t they?

 

The network contains two main databases: a training base and a test base, improvements in their work are made through trial-and-error process, similar to what people do. One of the strong features of the neural network is the ability of permanent progress, as the system uses new data for making more accurate predictions, altering and improving conclusions.

 

At Forex market a neural network can efficiently analyze both technical and fundamental data, performing the task, which can be difficult for the mechanical systems, and even more difficult for traders.

At the same time, training of the neural network does not take a lot of time, resources or forces. It is believed that this is the way, which leads to shortening the distance and the difference between the unique abilities of human mind and capabilities of the computer systems.

 

Have these systems been already applied?

 

Search engines such as Google or Yandex have long been using neural networks to analyze and classify images, sounds, text characters and other data. Google neural network can sort out images and distinguish common and particular features, specific to the same pictures. Such neural systems easily sort out black and white and color images, and can quite easily distinguish images of say, kittens from puppies.

 

Google translator has also partially switched to the neural network interface, which has improved quality of translation. Neurocomputers are actively used by the American financial conglomerate Citigroup Inc. Chemical Bank has also developed a large software system maintained by the company Neural Data. Many large American companies, such as LBS Capital Management Inc. buy small neuro-packets and neurocomputers (up to $ 50,000) and significantly improve their trading performance on US indices - S & P and Nasdaq.

The system expands opportunities of working with any data. For example, neural network can compress data, highlight links between common parts and provide the data in the short form and in a lesser dimension. The system can also restore the original data due to associative memory of the neural network if the data was somehow damaged.

Today, researchers and developers of the neural networks have some other serious tasks to implement. They shall improve the system of self-learning and analysis, increase the speed of reaction and resolve many other problems, enabling the use of the system for some specific tasks.   

 

Can we use this system in Forex market?

Neural network can make a forecast, generalize and highlight the data. Trained network, just   like any other technical indicator, can make predictions of the future based on historical data.

 

In contrast to classical indicators, neural network can evaluate and see dependencies between some data and also make adjustments based on the previous trading experience. Of course, it will take time, require some expenses and efforts to train a network and ensure timely responses to the incoming data.

Despite obvious advantages of the neural network, the system also involves risks of making wrong forecasts. We can say that final solutions largely depend on the input data. Neural network perfectly reveals correlations between two factors.

Neural network can distinguish common places in the disaggregated data when these patterns and relationships are hardly visible by the human eye. But still, the use of intelligence without emotions can be regarded as a weak point in work at the unstable market. When a system faces some new situation, artificial neural network can fail to evaluate it.

You can find examples of application of the neural networks in the financial markets here and here. There are more and more indicators, which use neural network and you can easily find them in many systems.

 

Overall conclusion

  • Neural network is a very prospective system, which can predict market situation better than traditional advisers and indicators; at the same time, despite their potential, neural networks have not been completely developed and need to be improved and adjusted.
  • Neural networks effectively distinguish patterns and intra-trend dynamics.
  • Neural networks work perfectly well within the current trend and discover behavioral cycles. But like a human being, they still can not foresee future without analyzing the past and work slower when receive new data.  
  • Traders, who use neural network at Forex usually prefer to trade on long-term trends or Momentum. Scalpers do not often use this system.
  • Although neural networks were popular 10 and 5 years ago, the increase in their popularity today is associated with the development of “big data” technologies and cloud storage, which should also be taken into account in further development and research.

 

 

 

 

 

 

 

 

 






The content of this article reflects the author’s opinion and does not necessarily reflect the official position of LiteForex. The material published on this page is provided for informational purposes only and should not be considered as the provision of investment advice for the purposes of Directive 2004/39/EC.



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