Human stock pickers have upper hand over AI when it comes to longer time horizons

Maria Nikolova

In investments of five years or longer, humans have the upper hand over AI, according to the Nomura Research Institute.

Robots are taking over more and more roles in the financial services world, including trading and investment strategies but human strategists still do better in some tasks than automated solutions, according to Nomura Research Institute Ltd (TYO:4307).

A report by the Japanese Nikkei refers to data from the Nomura Research Institute concerning a comparison of human stock pickers and artificial intelligence (AI) solutions trying to do the same.

Nomura Securities now uses AI solutions to forecast where share prices will be in five minutes. Based on the information given, the system detects correlations that humans cannot find, says Satoshi Kashihara, head of electronic trading services. Computers are increasingly taking over investments of a month to a year and are now doing better for investments spanning two to three years, where human-devised strategies used to have an edge.

The last hope for human staff seems to be the time horizon of five years or longer. According to the Nomura Research Institute, humans have an upper hand when recognizing a particularly competent management team, or brand strategy, early on. The future task for human investors will be to develop an ability to discern what cannot be detected by computers.

The trends outlined by Nomura are supported by the latest developments at UBS AG (SWX:UBSN), which may take robots to trading floors. The company has shown how two AI solutions can help traders to improve their performance.

The first program, developed in co-operation with Deloitte, deals with clients’ post-trade allocation requests. The solution scans for clients’ emails describing how they would like to allocate large block trades among funds. The system then processes the data and executes the transfers. According to UBS, the AI system performs a task that would usually take a person about 45 minutes in only about two minutes.

The second of the new solutions uses machine learning to develop new strategies for trading volatility on behalf of clients. It scans vast amounts of trading data and creates a strategy based on learning from market patterns. The strategy, however, still has to be approved by human employees.

Early this year, Marty Chavez, Goldman Sachs’s deputy chief financial officer and former chief information officer, said that automated trading programs had assumed most of the work performed by human traders at the company’s US cash equities trading desk in New York. He added that there were only 2 equity traders working at this desk, compared to 600 traders in 2000. Mr Chavez also forecast that currency trading and certain parts of investment banking will follow suit.

Goldman Sachs has already started to automate currency trading. Four traders can be replaced by one computer engineer, according to Mr Chavez. At present, about a third of Goldman Sachs’s staff are computer engineers.

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