TY - JOUR
T1 - Can a corporate network and news sentiment improve portfolio optimization using the Black–Litterman model?
AU - Creamer, Germán G.
N1 - Publisher Copyright:
© 2015 Taylor & Francis.
PY - 2015/8/3
Y1 - 2015/8/3
N2 - 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.
AB - 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.
KW - Black–Litterman model
KW - Boosting
KW - Link mining
KW - Machine learning
KW - Portfolio optimization
KW - Social network
KW - Text analysis
UR - http://www.scopus.com/inward/record.url?scp=84936891828&partnerID=8YFLogxK
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U2 - 10.1080/14697688.2015.1039865
DO - 10.1080/14697688.2015.1039865
M3 - Article
AN - SCOPUS:84936891828
SN - 1469-7688
VL - 15
SP - 1405
EP - 1416
JO - Quantitative Finance
JF - Quantitative Finance
IS - 8
ER -