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Providing services for the new SMACOM information distribution platform


In March 2021, Nikkei Financial Technology Research Institute (hereinafter "Nikkei FTRI") began providing services for the new SMACOM information distribution platform, which provides corporate analysis information. SMACOM makes valuable information available in order to support the decision-making process employed by leading financial market professionals. It evaluates more than 40,000 companies in 51 major economies using the sophisticated technologies and unique analytical skills of Nikkei FTRI. A wide range of data is used by SMACOM to evaluate companies, including financial statements, Nikkei News, and disclosed information. The platform leverages analyzed data and applies to it the advanced techniques and modeling expertise that Nikkei FTRI has developed over two decades. Another key feature of SMACOM is the use of exclusive information, including data from Nikkei newspapers and QUICK news, which it can access because of our status as a member of the Nikkei Group.

SMACOM delivers eight characteristic scores. There are five scores that evaluate the intrinsic value of companies: the News Sentiment Score (based on an analysis of news articles), the SR Sentiment Score (based on a securities report analysis), the FS Forecast Score (based on a future financial statement forecast), the Fundamental Score (based on a financial statement analysis), and the Total Score (a combination of these four scores). In addition, there are three scores related to a company's risks and credits: the Credit Score (which predicts default), the Accrual Score (which evaluates financial reporting quality and credibility), and the Rating Change Score (analyzing the risk of rating fluctuations). For example, the News Sentiment Score is derived from news information that could impact a company's future value. This score is calculated from Nikkei and QUICK news using the Natural Language Processing technique and based on know-how accumulated over many years by Nikkei FTRI. We plan to develop new types of scores in the future. In addition to the scores, various forms of detailed information, such as timely disclosure information and information on the sources of calculation, are also distributed.

SMACOM can provide these scores and information through a user-friendly browser-based interface, enabling users to make customized portfolios and easily check the quality and characteristics of their portfolio status, anywhere and at any time. SMACOM users can develop original in-house models utilizing our information and data, as has been done in the past by many prestigious hedge funds.

Among the various scores distributed by SMACOM, the performance of the Total Score can be evaluated using historical time-series data, as shown below. As can be seen from the graph, the Total Score (blue line) has outperformed TOPIX (orange line) over the long term.


We create five portfolios in order of increasing Total Score. Portfolio 1, where the highest Total Score (over 70 points) is long, and Portfolio 5, where the lowest Total Score (under 30 points) is short. We have used back data from March 2018 to March 2021.

The performance of the News Sentiment Score from 2011 to 2021 has been measured in the same way as above. We have found that the News Sentiment Score (blue line) has outperformed TOPIX (orange line) over the term as well as over a five-day holding period.


Although the above are past results, it is highly possible that better performance can be secured using SMACOM scores. The situation in the past, when stock selection was conducted mainly based on qualitative information, has changed to one in which stock selection takes place using quantitative information, mainly based on data analysis. Nowadays, one of the best options is to implement SMACOM, which provides easy access to scores resulting from stringent data analysis.

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Nikkei FTRI

Nikkei FTRI is a member of the Nikkei Group that works with data analysis technology. We are recognized for the high quality of our analytical and modeling techniques, which utilize both traditional and alternative varieties of data.

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