Lately, neural networks have been attracting attention in the trading community. With the availability of fast computing ability and plenty of bandwidth, neural networks can help trading systems learn and evolve in real time. Here’s a brief overview.
What is a neural network?
Stated simply, a neural network is a computational model which mimics the human brain by processing a large number of inputs in order to predict a likely outcome. Technically, networks used for trading are data-analysis protocols that contain a large number of processing modules related together through weighted probabilities.
The model is capable of both pattern recognition and “machine learning” which is adaptive in nature. When operated properly, the network “learns” by assessing the outcomes from its previous actions.
How neural networks are used in forex
Unlike traditional trading system development scenarios, neural networks use multiple data streams to produce a single output result. Any data that can be quantified can be added to the input used to make a prediction. These networks are used in a range of market-prediction forex software. They can be trained to recognize patterns, interpret data, and draw appropriate conclusions about future outcomes.
Before they make forex predictions, the networks must be “trained” to recognize patterns that become visible between input and output, and adjust the trading system’s actions accordingly. The only drawback in using neural networks is the time and effort required to train and test them. Still, the potential for gains may justify those efforts.
The idea is that when the system is presented with samples of input data and resulting outcomes, the network will learn the dependencies between input and output data sets. Going forward, the network compares its own results to see how closely they met the predicted values.
As with many testing scenarios, a neural network system must be operated using two separate sets of data – in this case a testing set and a training set. Then, it adjusts the weighting among the various dependencies until it exactly calculates the correct result. That’s how the network changes its behavior to improve the results.
Benefits of forex neural networks
The main benefit of neural-network trading systems is the fact that they continue to learn and improve their performance with continuing data input. These networks are also efficient in combining together both fundamental and technical data. They can find patterns not discovered during traditional system development, and apply those patterns to generate accurate predictions.
The more comprehensive the input, the better the output. The system can usually find tradeable correlations among the data input, as long as there’s plenty of it. In fact, networks can build patterns from disparate types of data, even when other analysis methods don’t work.
Another benefit of neural network-based forex trading systems is their ability to use intelligence without being influenced by emotion. This can be very helpful for human traders in volatile markets. Nevertheless, the network always requires human oversight of some kind, since it has no easy way to assign emotional weights to input factors.
The trading system learns your strategy, and improves it
There are numerous forex trading systems that incorporate features of neural networks in order to learn your trading strategy. The best artificial intelligence systems go a step further by evolving your trading rules and strategy based on real-time trading results, so the system learns and improves its performance over time.
How “intelligent” is your own trading system?
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