Machine Learning Is Better Than Humans In Predicting Stock Market Behavior, Report

According to a report from the Bank of England, machine learning is better than humans regarding predicting upcoming economic meltdowns.

The report was made public on the Bank Underground blog with the title “Wir Sind die Roboter: Can We Predict Financial Crises?”

The researchers use machine learning to analyze data of the last 40 years from 17 nations. The system is proven to work in complicated situations. For example, it predicted the 1991’s small bank crisis in the UK and the 2008-2009 global financial crisis.

The lead researcher Kristina Bluwstein wrote in the blog post that the advantages of knowing what was coming were huge and humans weren’t very good at predicting such an event. They said even people like Isaac Newton lost a fortune when crises happened.

According to the research, around 75% of GPD is the average cost of such a crisis. The loss is avoidable if macroprudential tools – or preventative actions are taken early.

As stated by the authors, the most important predictors for machine learning were the yield-curve slope and credit growth. While there will be unforeseeable events, identifying the financial system that can be amplified into a fully-fledged financial crisis is important.

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