AI is coming to financial traders

A more accessible AI is coming to financial traders

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Well-informed traders take both charts and high-impact news into account. Artificial intelligence (AI) offers an unprecedented capacity for not only crunching numbers, but also for processing news. As the technology spreads, it becomes less of a privilege reserved for large hedge funds and banks and more accessible to individual traders who’d like to harness the benefits too.

A widely-used application of AI is machine learning. With this technology, an algorithm explores vast data sets and “learns” their structure by detecting patterns. Once the training is complete, the insights from the model can be adapted to make predictions about other data sets. For example, based on historical market data, an algorithm can project upcoming price changes. Thereby, machine learning can facilitate the technical analysis of trading data.

However, traders don’t solely rely on mathematical analysis. Watching financial and other major news is critical when announcements or even gossip have the power to move prices. There is an application of AI which can be used to process the news circulating on the internet. The technique is called natural language processing and deals with the computational management of speech and text data. This means that sentiments, news articles as well as opinion pieces are easy to gather together and digest with the same software. What would be a daunting job for humans, is no problem for natural language processing algorithms. They can extract themes and expressions from more than a thousand articles at the same time. With such aggregation, it becomes easier to assess how likely a trade deal negotiation is to succeed according to other people.

A type of machine learning called deep learning is the closest we have gotten to real AI. This is the only kind of AI whose performance does not plateau but keeps getting better and better as more data is plugged in. Deep learning operates on so-called artificial neural networks because the networks simulate the working of human brain cells. They can propagate information from cell to cell but also feed back if something goes wrong.

This allows the algorithm to adapt to changing circumstances and refine its output, learning from every observation. Deep learning has the capability of bringing technical analysis and fundamentals together. For instance, a framework containing price analyses can be enriched with news stories appearing on social media. This way different parameters can be linked with each other and the influence of one source on the other can be assessed.

Overall, AI can be used to optimize trading strategies by training algorithms on an endless supply of data and then inventing new strategies based on the output. Other uses of AI, such as authenticating humans through voice and recording vocal commands may also come handy for traders. Initiating transactions via speech could accelerate the trading process, granting a speed advantage compared to other traders.

In short, artificial intelligence can be implemented to max out performance in narrowly defined tasks but human intelligence is what makes someone good at trading.

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