Optimal portfolio construction using qualitative and quantitative signals

Ronen Feldman, Suresh Govindaraj, Sangsang Liu, Joshua Livnat

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

Finance and accounting research has recently focused on extracting the tone or sentiment of a document (such as an earnings press release, cover story about a company, or management's presentations to analysts) by using positive or negative words/phrases in the document. This chapter shows that signals based on tone or sentiment (extracted from qualitative data) can achieve abnormal returns, and in some studies, incremental abnormal returns beyond quantitative signals. In this chapter, the authors exploit the information content of qualitative data in addition to quantitative signals in selecting optimal portfolios. Using optimization techniques developed by Brandt, Santa-Clara, and Valkanov (2009), and later extended by Hand and Green (2011), the authors show that significantly higher returns can be obtained by combining quantitative and qualitative data obtained from firms' Management Discussion and Analysis (MD&A) sections of their Form 10-Q (10-K) SEC filings than using quantitative signals.

Original languageEnglish (US)
Title of host publicationCommunication and Language Analysis in the Corporate World
PublisherIGI Global
Pages140-161
Number of pages22
ISBN (Electronic)9781466650008
ISBN (Print)1466649992, 9781466649996
DOIs
StatePublished - Jan 31 2014
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)

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