@article {Guerard81, author = {John B. Guerard, Jr and Eli Krauklis and Manish Kumar}, title = {Further Analysis of Efficient Portfolios with the USER Data}, volume = {21}, number = {1}, pages = {81--88}, year = {2012}, doi = {10.3905/joi.2012.21.1.081}, publisher = {Institutional Investor Journals Umbrella}, abstract = {In this study, we show that earnings forecasting and price momentum strategies complement fundamental stock selection strategies such that a composite model can be effectively implemented using both enhanced index-tracking portfolios and traditional mean{\textendash}variance portfolios. The mean{\textendash}variance optimization model produces statistically significant asset selection portfolios that dominate less-aggressive enhanced index-tracking portfolio construction models. We show that portfolios that use tracking error in risk optimization techniques produce a superior risk{\textendash}return trade-off than traditional mean{\textendash}variance optimization techniques. A portfolio manager should use a data mining corrections test to minimize the probability that the models selected resulted from a near-random process.TOPICS: VAR and use of alternative risk measures of trading risk, big data/machine learning, portfolio construction}, issn = {1068-0896}, URL = {https://joi.pm-research.com/content/21/1/81}, eprint = {https://joi.pm-research.com/content/21/1/81.full.pdf}, journal = {The Journal of Investing} }