Portfolio optimization and corporate networks: Extending the Black Litterman model

Germán Creamer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 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 with knowledge of market behavior. In this paper I propose a method where investors’ 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.

Original languageEnglish
Title of host publicationComplex Sciences - 2nd International Conference, COMPLEX 2012, Revised Selected Papers
EditorsKristin Glass, Richard Colbaugh, Jeffrey Tsao, Paul Ormerod
Pages83-94
Number of pages12
DOIs
StatePublished - 2013
Event2nd International Conference on Complex Sciences, COMPLEX 2012 - Santa Fe, United States
Duration: 5 Dec 20127 Dec 2012

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume126 LNICST
ISSN (Print)1867-8211

Conference

Conference2nd International Conference on Complex Sciences, COMPLEX 2012
Country/TerritoryUnited States
CitySanta Fe
Period5/12/127/12/12

Keywords

  • Black Litterman model
  • Boosting
  • Computational finance
  • Link mining
  • Machine learning
  • Portfolio optimization
  • Social network

Fingerprint

Dive into the research topics of 'Portfolio optimization and corporate networks: Extending the Black Litterman model'. Together they form a unique fingerprint.

Cite this