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20An ERI Scientific Beta Publication — The Dimensions of Quality Investing: High Profitability and Low Investment Smart Factor Indices — July 2015Copyright © 2015 ERI Scientific Beta. All rights reserved. Please refer to the disclaimer at the end of this document.2. Smart Factor Indices for High Profitabilityand Low Investment TiltsWe have discussed the reasoning and the evidence for the premium associated with the twofactors – high profitability and low investment. In this section we describe how ERI Scientific Betaconstructs its smart factor indices, which allow investors to gain exposure to these rewarded riskfactors. We will also discuss the historical performance of these indices.2.1. Scientific Beta Multi-Strategy Factor IndicesERI Scientific Beta uses a consistent smart beta index-design framework for the construction of itssmart factor indices known as the Smart Beta 2.0 approach. In this approach to index construction,the selection and weighting phases are clearly separated, which enables investors to choose therisks to which they do or do not wish to be exposed. A well-diversified weighting scheme providesefficient access to the risk premia associated with this factor exposure. The idea is to construct aninvestable proxy for the risk factor (beta) chosen while reducing unrewarded risks through the useof a well-diversified weighting scheme.Such an ex-ante methodological framework for constructing a portfolio is a tool for avoiding thetrap of constructing ad-hoc methodologies that only perform well in the back-test. All the availablevariations (or choices) provided within the framework are based on proven academic or appliedresearch, allowing flexibility to accommodate various investor preferences. Moreover, publishing awide range of indices that correspond to variations within a given index design framework allowsinvestors to assess the sensitivity of each index construction strategy to the model specificationchoices.Exhibit 6: Overview of Smart BetaExhibit 7 depicts the detailed phases of the Smart Beta 2.0 approach in constructing the profitabilityand investment smart factor indices. In the stock selection phase the broad stock universe, afterapplying sufficient investability filters, is divided into two halves based on the characteristic proxyvariables – Gross Profitability (Gross Profit/Total Assets) in the case of the Profitability factor andTotal Asset Growth over two years in the case of the Investment factor. Then the 50% of stockstilting towards the rewarded factor tilt are selected (High Profitability and Low Investment) in thestock selection phase. For strategic reasons and to allow more flexibility for asset managers to usethe factor indices as building blocks for their portfolios for any short-term gains, low profitabilityand high investment indices are also constructed. Once the stock selection is done, five differentweights are computed for each stock using the five diversification weighting schemes used inthe Scientific Beta framework: Maximum Deconcentration, Maximum Decorrelation, Efficient