Developing an Risk Signal Detection System Based on Opinion Mining for Financial Decision Support

Companies have long sought to detect financial risks and prevent crises in their business activities. Investors also have a great need to identify risks and utilize them for investment. Thus, several studies have attempted to detect financial risk. However, these studies had limitations in that various data were not exploited and diverse perspectives of the firm were not reflected. This can lead to wrong choices for investment. Thus, the purpose of this study was to propose risk signal prediction models based on firm data and opinion mining, reflecting both the perspectives of firms and investors. Furthermore, we developed a process to obtain real time firm related data and convenience visualization. To develop this process, a credit event was defined as an event that led to a critical risk of the firm. In the next step, the firm risk score was calculated for a firm having a possible credit event. This score was calculated by combining the firm activity score and opinion mining score. The firm activity score was calculated based on a financial statement and disclosure data indicator, while the opinion mining score was calculated based on a sentiment analysis of news and social data. As a result, the total firm risk grade was derived, and the risk level was proposed. These processes were developed into a system and illustrated by real firm data. The results of this study demonstrate that it is possible to derive risk signals through integrated monitoring indicators and provide useful information to users. This study can help users make decisions. It also provides users an opportunity to identify new investment momentums.

Declining Dynamism, Allocative Efficiency, and the Productivity Slowdown

A large literature documents declining measures of business dynamism including high-growth young firm activity and job reallocation. A distinct literature describes a slowdown in the pace of aggregate labor productivity growth. We relate these patterns by studying changes in productivity growth from the late 1990s to the mid 2000s using firm-level data. We find that diminished allocative efficiency gains can account for the productivity slowdown in a manner that interacts with the within-firm productivity growth distribution. The evidence suggests that the decline in dynamism is reason for concern and sheds light on debates about the causes of slowing productivity growth.

Declining Business Dynamism: What We Know and the Way Forward

A growing body of evidence indicates that the U.S. economy has become less dynamic in recent years. This trend is evident in declining rates of gross job and worker flows as well as declining rates of entrepreneurship and young firm activity, and the trend is pervasive across industries, regions, and firm size classes. We describe the evidence on these changes in the U.S. economy by reviewing existing research. We then describe new empirical facts about the relationship between establishment-level productivity and employment growth, framing our results in terms of canonical models of firm dynamics and suggesting empirically testable potential explanations.