The objective of the PoC was to assess whether analysis with AI would contribute to increased
\naccuracy of portfolio managers\u2019 investment decision-making. Portfolio managers at asset
\nmanagement firms usually have to process and analyze a large amount of information which
\nincludes not only analyst reports, but also a flood of various news sources, industry blogs and
\nsocial media, such as Twitter\u00ae, to make forecasts and determine the impact on stock prices.<\/p>\n
NAM and NRI worked jointly using AI technology to analyze all the information a portfolio
\nmanager would consume and score them into two groups; either positive (indicating that
\ncompany performance or corporate value is likely to rise) or negative (indicating these factors
\nare likely not to rise). This PoC is one of the first full-scale efforts made by a Japanese asset
\nmanager to analyze and score analyst reports using AI.<\/p>\n
To run this PoC, NRI\u2019s experience in developing AI solutions and natural language analysis was
\nused. NRI first conducted a natural language analysis on analyst reports which highlighted the
\nshifts of investment decisions (For example, a shift from neutral to overweight or from neutral to
\nunderweight). The language patterns for \u201cpositive\u201d and \u201cnegative\u201d were then identified and used
\nas training data for AI. Finally, the AI calculated the similarities between the training data and
\nthe targeted materials, scoring whether each piece of information is \u201cpositive\u201d or \u201cnegative\u201d.
\nThe result of the PoC highlighted that analysis of analyst reports using AI enabled the
\nquantitative assessment of information which portfolio managers usually see as qualitative. <\/p>\n
In
\naddition, even text information from news websites and blogs could be quantitatively scored and
\nused to enhance the ability of portfolio managers to make investment decisions. In the future, it
\nis expected that more information that could not have been captured by humans qualitatively,
\nwill be available as quantitative information and utilized for investment decision-making.
\nThe PoC was conducted in 2016 and 2017. NAM and NRI plan to continue to work with clients
\nto create PoCs and to explore cases where AI can help to move the industry forward. <\/p>\n","protected":false},"excerpt":{"rendered":"
Nomura Asset Management Co., Ltd. (NAM) and Nomura Research Institute, Ltd. (NRI), today announced that they have conducted a proof of
\nconcept (PoC) study to examine natural language processing utilizing Artificial Intelligence (AI).<\/p>\n","protected":false},"author":20,"featured_media":64026,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1470],"tags":[1655,1658,1437,2007,2068,1787],"_links":{"self":[{"href":"http:\/\/beta.next-finance.net\/en\/wp-json\/wp\/v2\/posts\/64028"}],"collection":[{"href":"http:\/\/beta.next-finance.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/beta.next-finance.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/beta.next-finance.net\/en\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"http:\/\/beta.next-finance.net\/en\/wp-json\/wp\/v2\/comments?post=64028"}],"version-history":[{"count":0,"href":"http:\/\/beta.next-finance.net\/en\/wp-json\/wp\/v2\/posts\/64028\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/beta.next-finance.net\/en\/wp-json\/wp\/v2\/media\/64026"}],"wp:attachment":[{"href":"http:\/\/beta.next-finance.net\/en\/wp-json\/wp\/v2\/media?parent=64028"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/beta.next-finance.net\/en\/wp-json\/wp\/v2\/categories?post=64028"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/beta.next-finance.net\/en\/wp-json\/wp\/v2\/tags?post=64028"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}