Numerals in Financial Narratives

Numerals are more common in financial narratives than in documents from other domains, which makes understanding numerals very important when analyzing financial documents. In this chapter, we summarize our work on numerals in financial narratives and share findings from the FinNum shared task series in the 14th and 15th NTCIR Conferences. In Sect. 5.1, we discuss how to understand the meaning of a given numeral, and in Sect. 5.2, we discuss numeral attachment, where we link numerals and named entities. In Sect. 5.3, we show experimental results from downstream tasks that demonstrate the importance of numeral understanding in financial narratives. We conclude by proposing future research directions in Sect. 5.4.

FinTech Applications

The Financial Stability Board defines financial technology (FinTech) as “technology-enabled innovation in financial services.” At the 2015 World Economic Forum, experts proposed a taxonomy for financial services that can be classified into six major categories: payments, deposits and lending, market provisioning, capital raising, insurance, and investment management. Because financial opinion mining can be applied to many listed services, we survey various cases in this chapter and show that financial opinion mining is useful and crucial in many financial application scenarios.

Introduction

Financial opinion mining is a branch of traditional opinion mining and sentiment analysis which shares the basic notions of traditional approaches and adds its own domain-specific characteristics. In Sect. 1.1, we start with a common definition of general opinion mining after which we briefly overview traditional research directions.

Perspectives and Conclusion

In this book, we started by describing the components of financial opinions as well as opinion sources in the financial domain. Then, we surveyed options for modeling financial opinions, and discussed in detail one fundamental characteristic of financial narratives: numerals. We also listed numerous applications and research directions. We have thus described financial opinion mining and have provided essential examples to illustrate various concepts. In this final chapter, we organize future directions and summarize the ideas in the book.

Sources and Corpora

In this chapter, we focus on the sources of financial opinions; we group these sources by the opinion holders: insiders (Sect. 3.1), professionals (Sect. 3.2), social media users (Sect. 3.3), and journalists (Sect. 3.4). Each opinion holder may have his/her own goals when expressing opinions, resulting in different opinions from unique viewpoints.

Organizing Financial Opinions

In Chap. 10.1007/978-981-16-2881-8_2, we discuss what we need to extract and understand when analyzing financial opinions. In Chap. 10.1007/978-981-16-2881-8_3, we discuss where to find financial opinions. This chapter concerns how to extract and understand the financial opinions in these sources.

Modeling Financial Opinions

In this chapter we lay out the primary background of a financial opinion and the relation between opinions and financial instruments. Together, these constitute an overall picture of opinion-based market interaction. Following this discussion we propose several research issues. First, in Sect. 2.1, we discuss the components in a financial opinion one by one, as well as potential research directions; we also explain why we need to extract components and estimate their quality (or influence).