About this Research Topic
Datasets have been created that contain about 10 variables in three stock universes for analysis data and portfolio construction for the 1999 -2016 time period. Three questions can be addressed and answered: (1) which statistical techniques are best at modeling data plagued with outliers and multicollinearity; (2) what portfolio optimization techniques are best used to create efficient frontiers and portfolios; and (3) do fundamental or statistical risk models produce the highest geometric means, Sharpe Ratios, and Information Ratios? The modeling universes will include: (1) global stocks with two analysts’ earnings forecasts; (2) non-U.S. stocks with two analysts’ forecasts; and (3) emerging markets stocks with two analysts’ earnings forecasts. We expect portfolio construction techniques will include expected tail lose and down-side risk measures.
This Research Topic aims to gather the direct output of the horse race. Once these are published, we encourage spontaneous submissions in the form of General Commentaries on the Original Research articles.
Keywords: Optimized portfolios, I/B/E/S Forecasts, Investments, Risk Models, Robust Regression
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.