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A man is reflected on the electronic board of a securities firm in Tokyo, Wednesday, Feb. 17. (Shizuo Kambayashi/AP)
A man is reflected on the electronic board of a securities firm in Tokyo, Wednesday, Feb. 17. (Shizuo Kambayashi/AP)

This Japanese robot calls the market better than a human Add to ...

On the 10th day of every month, Junsuke Senoguchi has just one thing on his mind -- the closing level of the Nikkei 225 Stock Average.

That’s because Mr. Senoguchi, an unassuming man in his late 40s, has built a machine that’s been predicting the direction of Japanese shares, and once a month he gets a progress report on its success. The model makes a simple call - whether the equity index will be higher or lower after 30 days - and over almost four years it’s been right 68 per cent of the time.

“I’m so happy” when it works, said Mr. Senoguchi, a senior equity strategist at Mitsubishi UFJ Morgan Stanley Securities Co. in Tokyo. “It’s because I feel I can predict the future.”

Algorithms have invaded global share markets, used by everyone from high-frequency traders closing bets in fractions of a second, to specialist asset managers whose strategies are determined by complex quantitative analysis. Medallion, the fund created by James Simons at quant-trading pioneer Renaissance Technologies, averaged a 71.8-per-cent annual return, before fees, from 1994 through mid-2014. There’s also the growing field known as robo-advice, which uses algorithms to suggest investments based on clients’ goals and risk tolerances.

Mr. Senoguchi has spent his career in finance, working as a banking analyst for Lehman Brothers Holdings Inc. until it collapsed and then moving to the Bank of Japan before taking his current job. But he also holds a Ph.D. in artificial intelligence.

“Because my background lies in science, I was really interested in seeing if I could use numbers to predict stock prices and the economy,” he said. “Artificial intelligence gives you much better results than conventional statistics.”

From March 2012 through Jan. 10, Mr.Senoguchi’s robo-forecaster was right 32 times out of 47, he says. While the sample size is small, the result goes beyond the 50-per-cent level expected from a coin toss. A decades-long study by Philip Tetlock published in 2005 found expert human forecasters on average do no better than chance.

“It’s hard to get over 60 percent without some ingenuity,” said Akito Sakurai, a professor specializing in artificial intelligence at Keio University in Tokyo. “You’d have to say that 68 percent is pretty high.”

Japan’s biggest institutional investors are taking note. Mr. Senoguchi visited about 40 of them recently to field inquiries about his creation.

Mr. Senoguchi’s machine operates like a chess computer, poring over past data to identify patterns. He contrasts it with statistical analysis, which he says works in terms of lines on graphs, normal distributions and deviations from the mean. For him, that’s akin to forcing square pegs into round holes. His model harnesses big data to see what happened and decide if it will again.

Creating a Deep Blue - the computer that beat chess world champion Garry Kasparov in 1997 - for the stock market is a complex task. In short, Senoguchi’s machine develops hundreds of sets of rules by combining 92 economic indicators and multiple timeframes, and then applies the best one.

It uses elimination to decide which set has been most predictive for stocks over the past 48 months. That becomes the model to forecast month 49. It then deploys a decision-tree process from artificial intelligence theory to make its guess.

Mr. Senoguchi says one strength is his model starts afresh each time. When there are big changes in the environment, such as central bank decisions, his model will compensate.

This is “definitely something extremely new,” said Keio University’s Sakurai. “As far as I know, thinking up something like this and actually using it for forecasting hasn’t happened before.”

The technique can be applied to other areas. Predicting interest-rate moves isn’t hard, while currency rates sit at the other end of the spectrum, Mr. Senoguchi said. Stocks are “fairly difficult,” but U.S. equities would be easier because of the data available and lower volatility.

Mr. Senoguchi’s model didn’t foresee Japanese shares’ worst start to a year on record. Its prediction for the period ended Jan. 10 was for the Nikkei 225 to advance. It wasn’t alone: almost half the forecasters in a Nikkei survey saw their predicted lows for 2016 breached on the first day.

Still, Mr. Senoguchi says his machine will get back on track.

“Sometimes the structure of the market changes greatly,” he said. “The ability to change the model when this happens is a big difference from previous approaches.”

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