Nomura Tests AI for Asset Management
Japanese investment manager Nomura Asset Management and Nomura Research Institute have announced that they have conducted an artificial intelligence proof of concept using natural language processing to see if using AI would sharpen the decision-making of portfolio managers.
Firms used an AI platform developed by NRI to analyze all the information a portfolio manager would consume and score that data as positive or negative, denoting that the company’s value likely would rise or fall respectively.
NRI staff first conducted a natural language analysis on analyst reports which highlighted the shifts of investment decisions (For example, a shift from neutral to overweight or from neutral to underweight). The language patterns for “positive” and “negative” were then identified and used as training data for AI. Finally, the AI calculated the similarities between the training data and the targeted materials, scoring whether each piece of information is “positive” or “negative.”
The result of the PoC highlighted that analysis of analyst reports using AI enabled the quantitative assessment of information which portfolio managers usually see as qualitative. Also, the AI could score text from news websites, and blogs quantitatively scored to enhance the ability of portfolio managers to make investment decisions.
In the future, researchers expect that more information that could not have been captured by humans qualitatively, will be available as quantitative data and utilized for investment decision-making.
Deep learning may do to HFT what HFT did to statistical arbitrage.
AIs may flag "unambiguous" rule violations in the future.
A difficult, but not impossible, task
Machines beat a conference room full of lawyers manually reviewing docs.
Next-gen advisors broaden product support and depth.