Can a corporate network and news sentiment improve portfolio optimization using the Black–Litterman model?

Germán G. Creamer

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

The Black–Litterman (BL) model for portfolio optimization combines investors’ expectations with the Markowitz framework. The BL model is designed for investors with private information or knowledge of market behaviour. In this paper, I propose a method where investors’ expectations are based on either news sentiment using high-frequency data or on a combination of accounting variables; financial analysts’ recommendations, and corporate social network indicators with quarterly data. The results show promise when compared to a market portfolio. I also provide recommendations for trading strategies using the results of this BL model.

Original languageEnglish
Pages (from-to)1405-1416
Number of pages12
JournalQuantitative Finance
Volume15
Issue number8
DOIs
StatePublished - 3 Aug 2015

Keywords

  • Black–Litterman model
  • Boosting
  • Link mining
  • Machine learning
  • Portfolio optimization
  • Social network
  • Text analysis

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