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Appendix Disclosure (continued) Data Frequency & Updates Aperio updates its ESG data for the menu periodically on a preset schedule. Data elements are updated during the year as our data providers receive new data from either the company or publicly available sources. Aperio updates all exclusions and scoring profiles annually at the beginning of each calendar year. As accounts are rebalanced, the updated data will be incorporated. NOTE: Because the data sets are not updated in real time, there may be a lag between a change at the company and when the change flows into the data set, and again when it flows into the portfolio during a rebalance. Aperio handles all updates consistently and does not override the approved data sets. Index Definition The MSCI ACWI is an equity benchmark for global stock performance. It is a capitalization-weighted index covering large and midsize companies. The index includes approximately 2,800 stocks from 23 developed-market countries and 24 emerging-market countries. Optimizer The optimization process used in tax-loss harvesting by Aperio relies upon an optimization model built and designed by MSCI Barra. The model utilizes a mathematical objective function that seeks to minimize the combination of active risk (i.e., forecast tracking error) and the tax liability on realized gains, all while also meeting the conditions presented by a series of simultaneous equations, the values of which are, in part, populated by data based upon the securities being analyzed. With respect to measuring potential equity risk in the process of tax-loss harvesting and portfolio analysis, Aperio also uses and relies upon MSCI Barra risk models. You should note that such use and reliance of the MSCI Barra models in the optimization and equity risk analysis presents model risk, which is defined as the potential for adverse consequences from decisions based on incorrect or misused model outputs and reports. Model risk can lead to financial loss. The model may have fundamental errors and may produce inaccurate outputs when viewed against the design objective and intended business uses. The mathematical calculation and quantification exercise underlying any model generally involves application of theory, choice of sample design and numerical routines, selection of inputs and estimation, and implementation in information systems. Errors can occur at any point from design through implementation. In addition, shortcuts, simplifications, or approximations used to manage complicated problems could compromise the integrity and reliability of outputs from those calculations. Finally, the quality of model outputs depends on the quality of input data and assumptions, and errors in inputs or incorrect assumptions will lead to inaccurate outputs. The model may be used incorrectly or inappropriately. Even a fundamentally sound model producing accurate outputs consistent with the design objective of the model may exhibit high model risk if it is misapplied or misused. Models by their nature are simplifications of reality, and real-world events may prove those simplifications inappropriate. aperio For Professional Investor Use Only 16

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