@article {Davis39, author = {Richard C. Davis}, title = {{\textquotedblleft}Big Data{\textquotedblright} Meets {\textquotedblleft}Smart Beta{\textquotedblright}}, volume = {6}, number = {1}, pages = {39--50}, year = {2015}, doi = {10.3905/jii.2015.6.1.039}, publisher = {Institutional Investor Journals Umbrella}, abstract = {There is business intelligence in {\textquotedblleft}big data{\textquotedblright} that can be utilized to improve performance in both actively and passively managed portfolios. But extracting that business intelligence from big data has a number of challenges, including the processing scale implied in the name itself. This article is intended to be a primer for investment professionals seeking to learn more about how to meaningfully utilize the brand-name citation metrics that are available from big data. It shows how to use those metrics as either a new form of fundamental data for tactically or quantitatively managed active portfolios, or as alternate selection and weighting strategies for tracking tolerant {\textquotedblleft}smart beta{\textquotedblright} applications.TOPICS: Big data/machine learning, portfolio construction, passive strategies}, issn = {2154-7238}, URL = {https://jii.pm-research.com/content/6/1/39}, eprint = {https://jii.pm-research.com/content/6/1/39.full.pdf}, journal = {The Journal of Beta Investment Strategies} }