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

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  • Germ�n G. Creamer

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.

Suggested Citation

  • Germ�n G. Creamer, 2015. "Can a corporate network and news sentiment improve portfolio optimization using the Black-Litterman model?," Quantitative Finance, Taylor & Francis Journals, vol. 15(8), pages 1405-1416, August.
    • Handle: RePEc:taf:quantf:v:15:y:2015:i:8:p:1405-1416
    DOI: 10.1080/14697688.2015.1039865
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    Cited by:

    1. Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
    2. Barua, Ronil & Sharma, Anil K., 2023. "Using fear, greed and machine learning for optimizing global portfolios: A Black-Litterman approach," Finance Research Letters, Elsevier, vol. 58(PC).
    3. S., Glogger & S., Heiden & D., Schneller, 2019. "Bearing the bear: Sentiment-based disagreement in multi-criteria portfolio optimization," Finance Research Letters, Elsevier, vol. 31(C), pages 47-53.

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