Strategy. The Fund seeks to track the performance, before fees and expenses, of the Index. The Index, developed by Wilshire Indexes (the Index Provider) in partnership with the Adviser, is composed of equity securities of issuers incorporated, headquartered in or with primary listings in one of twenty-four designated emerging market countries (the Eligible Countries), which include Brazil, Chile, China, Colombia, Czech Republic, Egypt, Greece, Hungary, India, Indonesia, Kuwait, Malaysia, Mexico, Peru, Philippines, Poland, Qatar, Saudi Arabia, South Africa, South Korea, Taiwan, Thailand, Turkey, and United Arab Emirates. Chinese issuers included in the Index may be incorporated outside of mainland China in jurisdictions such as Hong Kong or in certain offshore locations (the Benefit Countries), which include Bermuda, British Virgin Islands, Cayman … Show more… The Fund seeks to track the performance, before fees and expenses, of the Index. The Index, developed by Wilshire Indexes (the Index Provider) in partnership with the Adviser, is composed of equity securities of issuers incorporated, headquartered in or with primary listings in one of twenty-four designated emerging market countries (the Eligible Countries), which include Brazil, Chile, China, Colombia, Czech Republic, Egypt, Greece, Hungary, India, Indonesia, Kuwait, Malaysia, Mexico, Peru, Philippines, Poland, Qatar, Saudi Arabia, South Africa, South Korea, Taiwan, Thailand, Turkey, and United Arab Emirates. Chinese issuers included in the Index may be incorporated outside of mainland China in jurisdictions such as Hong Kong or in certain offshore locations (the Benefit Countries), which include Bermuda, British Virgin Islands, Cayman Islands, Gibraltar, Guernsey, Isle of Man, Jersey, and Marshall Islands. Such issuers may list on exchanges in Hong Kong, New York (N-shares), or Singapore (S-Chips). Taiwanese issuers may similarly maintain operational headquarters in mainland China or be incorporated in a Benefit Country. The Index includes listed equity securities such as common shares, ordinary shares, and preferred shares. With respect to Chinese issuers, the Index may also include A Shares of companies incorporated in China (China A Shares) that trade on the Shanghai Stock Exchange and the Shenzhen Stock Exchange through the Shanghai Hong Kong and Shenzhen Hong Kong Stock Connect programs (Stock Connect), B-shares, H-shares, Red Chips, P-Chips, S-Chips, and N-shares. Securities must be exchange-listed to qualify for inclusion. Securities trading solely over-the-counter and issuers that are subject to a U.S. sanctions program are excluded. For each Eligible Country, an index universe is established that consists of all eligible securities assigned to that country, which is then divided into large and small cap segments and screened for investability. The large cap segments are then aggregated to form the FT Wilshire Emerging Large Cap Index (the Underlying Benchmark), from which the Index is constructed. As of September 30, 2025, the companies included in the Index had a market capitalization ranging from $1.01 billion to $1.11 trillion. The Index Provider designs, maintains, and calculates the Index using a transparent, ruled-based methodology. This methodology incorporates return forecasts from quantitative machine learning models developed by the Adviser, guiding stock selection and weighting within the Index. The Index construction process begins with the universe of companies that are current members of the Underlying Benchmark. The Underlying Benchmark captures large-cap representation across all 24 emerging market countries. With 1,383 constituents as of June 30, 2025, the Underlying Benchmark covers approximately 80% of the investable market capitalization in emerging markets. The construction of the Index is then divided into three steps: (1) risk-adjusted returns estimation via machine learning; (2) covariance matrix estimation and (3) mean-tracking error optimization, as described in greater detail below. 1. Risk-Adjusted Returns Estimation via Machine Learning The first step of the Index construction process involves forecasting the expected risk-adjusted return of each component of the Underlying Benchmark using machine learning models. These models analyze over 100 stock-level market and fundamental characteristics from well-established academic research, drawn from 12 different categories such as default risk, growth, momentum, productivity, profitability, size and value. The models are based on historical data and aim to identify patterns that help predict which stocks that comprise the Underlying Benchmark are likely to outperform. 2. Covariance Matrix Estimation The second step of the Index construction process utilizes a covariance matrix to estimate risk and correlations between stocks of the Underlying Benchmark. The covariance matrix uses a statistical factor model to identify how the daily returns of stocks comprising the Underlying Benchmark move in relation to each other, and allows the models to understand how combining different stocks will affect the total risk of the portfolio. 3. Mean-Tracking Error Optimization In the final step of the Index construction process, a mean-tracking error optimization is performed using the expected returns determined in Step 1 above and the covariance matrix estimated in Step 2. This mathematical process selects stock weights that aim to maximize return while minimizing tracking error from the Underlying Benchmark in terms of risk and exposure. The optimization imposes certain constraints to ensure that the Index remains aligned with the Underlying Benchmark, including industry and country exposure limits and individual stock weight caps. Stocks with trivial target weights, as defined in the Index methodology, are removed from the Index. The optimization process is repeated periodically to adapt to changing market conditions. The Index is reconstituted on a quarterly basis. A constituent will be removed from the Index if it is removed from the Underlying Benchmark. The Fund uses a passive management (or indexing) approach in seeking to achieve its investment objective. Under normal circumstances, the Fund invests at least 80% of its net assets, plus any borrowings for investment purposes, in component securities of the Index. This investment policy may be changed by the Fund upon 60 days prior written notice to shareholders. The Fund generally uses a replication strategy to achieve its investment objective, meaning that it will invest in all of the securities included in the Index. The Fund may, however, use a representative sampling approach to achieve its investment objective when the Adviser believes it is in the best interest of the Fund. For example, among other reasons, the Fund may use a representative sampling approach when there are practical difficulties or substantial costs involved in replicating the Index or when an Index constituent becomes temporarily illiquid, unavailable or less liquid. When the Fund uses a representative sampling approach, the Fund may invest in a subset, or sample, of the securities included in the Index and whose risk, return and performance characteristics generally match the risk, return and performance characteristics of the Index as a whole. The Fund may also invest in total return swaps and participatory notes (P-Notes) that are not components of the Index that the Adviser believes will help the Fund track the Index. The Fund may concentrate its investments (i.e., invest more than 25% of its total assets) in a particular industry or group of industries to approximately the same extent that the Index concentrates in an industry or group of industries. As of September 30, 2025, the Index was not concentrated in any one industry. In addition, in replicating the Index, the Fund may from time to time invest a significant portion of its assets in the securities of companies in one or more sectors. As of September 30, 2025, a significant portion of the Index consisted of companies in the Financials and Technology sectors, as each such sector is defined by the Wilshire Global Assets Taxonomy System (GATS), as set forth in the Global Assets Taxonomy System Principles and Methodology (June 2025) published by Wilshire Indexes. The sectors in which the Index components, and thus the Funds investments, may be focused will vary as the composition of the Index changes over time. Show less