@article {Davis1, author = {Richard C. Davis}, editor = {Picchi, Aimee}, title = {Practical Applications of {\textquotedblleft}Big Data{\textquotedblright} Meets {\textquotedblleft}Smart Beta{\textquotedblright}}, volume = {3}, number = {SB}, pages = {1--4}, year = {2015}, doi = {10.3905/pa.2015.3.sb.004}, publisher = {Institutional Investor Journals Umbrella}, abstract = {{\textquotedblleft}Big Data{\textquotedblright} Meets {\textquotedblleft}Smart Beta{\textquotedblright} Richard C Davis There{\textquoteright}s more to {\textquotedblleft}big data{\textquotedblright} than just a buzzword. Business intelligence extracted from big data has helped active managers achieve excess returns, particularly for portfolios invested in consumer-focused industries such as retailing and specialty foods. But what happens when a smart-beta passive portfolio is constructed on information gleaned from big data? Consumer Metrics Institute and BrandLoyalties.com CEO Richard Davis wrote {\textquotedblleft}Big Data{\textquotedblright} Meets {\textquotedblleft}Smart Beta{\textquotedblright} as a primer for investment professionals about how to glean relevant insights from brand-name metrics. He discusses how such metrics can serve as 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.}, issn = {2329-0196}, URL = {https://pa.pm-research.com/content/3/SB/1.4}, eprint = {https://pa.pm-research.com/content/3/SB/1.4.full.pdf}, journal = {Practical Applications} }