@inproceedings{8ede20ba6d154f83b29bb1d4f70c15f4,
title = "Portfolio optimization and corporate networks: Extending the Black Litterman model",
abstract = "The Black Litterman (BL) model for portfolio optimization combines investors{\textquoteright} expectations with the Markowitz framework. The BL model is designed for investors with private information or with knowledge of market behavior. In this paper I propose a method where investors{\textquoteright} expectations are based on accounting variables, recommendations of financial analysts, and social network indicators of financial analysts and corporate directors. The results show promise when compared to those of an investor that only uses market price information. I also provide recommendations about trading strategies using the results of my model.",
keywords = "Black Litterman model, Boosting, Computational finance, Link mining, Machine learning, Portfolio optimization, Social network",
author = "Germ{\'a}n Creamer",
note = "Publisher Copyright: {\textcopyright} Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2013.; 2nd International Conference on Complex Sciences, COMPLEX 2012 ; Conference date: 05-12-2012 Through 07-12-2012",
year = "2013",
doi = "10.1007/978-3-319-03473-7\_8",
language = "English",
isbn = "9783319034720",
series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",
pages = "83--94",
editor = "Kristin Glass and Richard Colbaugh and Jeffrey Tsao and Paul Ormerod",
booktitle = "Complex Sciences - 2nd International Conference, COMPLEX 2012, Revised Selected Papers",
}