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

被引:12
作者
Creamer, German G. [1 ]
机构
[1] Stevens Inst Technol, Howe Sch, Hoboken, NJ 07030 USA
关键词
Link mining; Social network; Machine learning; Boosting; Text analysis; Portfolio optimization; Black-Litterman model;
D O I
10.1080/14697688.2015.1039865
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
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.
引用
收藏
页码:1405 / 1416
页数:12
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