v3.26.1
Investment Strategy
Jun. 09, 2026
Rayliant NxtGen Multifactor US Equity ETF  
Prospectus [Line Items]  
Strategy [Heading] Principal Investment Strategies
Strategy Narrative [Text Block]

The Fund invests, under normal circumstances, at least 80% of its net assets plus any borrowings for investment purposes in equity securities of issuers located in the United States. This investment policy may be changed by the Fund upon 60 days’ prior written notice to shareholders. The Adviser considers an issuer to be located in the United States if it meets one or more of the following criteria: (i) the issuer is organized under the laws of, or has its principal office in the United States; (ii) the issuer has the primary trading markets for its securities in the United States; (iii) the issuer derives at least 50% of its revenue or profits from goods or services sold or performed, or investments made, in the United States; or (iv) the issuer has at least 50% of its assets in the United States. For clarity, the Adviser may rely on only one criterion to determine an issuer’s location even if other criteria may indicate a different location.

 

The equity securities in which the Fund invests are primarily common stocks and depositary receipts, including unsponsored depositary receipts, but may also include preferred stocks, real estate investment trusts (“REITs”), exchange-traded funds (“ETFs”), and securities of other investment companies. The Fund may invest in securities of companies with any market capitalization with a particular focus on mid- and large-capitalization securities.

 

The Fund is primarily made up of stocks of issuers located in the United States that are selected using a quantitative investment approach with

human discretion. In quantitative investment strategies, investment decisions are made using large amounts of data and computer models. However, the Adviser has the discretion to adjust trades based on news, liquidity, or additional insights from the Adviser’s portfolio management team. The Adviser’s quantitative investment models, which incorporate machine learning, allocate more weight to stocks for which the models identify the potential for higher future returns, taking into account risk (i.e., risk-adjusted returns), and less weight to stocks for which the models identify the potential for lower future risk-adjusted returns. The Adviser’s portfolio management team may adjust portfolio weights for the Fund based on their own analysis of the securities in the Fund’s investment universe in order to enhance evaluations made by the quantitative model. Due to its investment strategy, the Fund may buy and sell securities frequently.

 

The Adviser uses data from a variety of sources, including data purchased from vendors and data accessed by the Adviser from alternative sources (e.g., data collected from public websites). Such data are collected at varying frequencies (e.g., daily price data, quarterly financial statements) and considered over varying horizons, ranging from months to years, depending on the nature of the data in question. The Adviser employs a proprietary data cleaning process, whereby data obtained from vendors and other sources is inspected for errors, processed to make information obtained from different sources useful in comparing various companies, sectors, and markets, and formatted for inclusion in the Adviser’s database and for use in its models. The Adviser monitors its data and models through a combination of automated and manual checks. The Adviser pays for data used in the strategy’s models.

Rayliant NxtGen Multifactor Emerging Markets Equity ETF  
Prospectus [Line Items]  
Strategy [Heading] Principal Investment Strategies
Strategy Narrative [Text Block]

The Fund invests, under normal circumstances, at least 80% of its net assets plus any borrowings for investment purposes in equity securities of emerging market companies. This investment policy may be changed by the Fund upon 60 days’ prior written notice to shareholders. The Adviser considers a company to be an emerging market company if it is organized or maintains its principal place of business in an emerging markets country. The Adviser considers a country to be an emerging markets country if the country is represented in the MSCI Emerging Markets Index or another widely recognized emerging markets index. Emerging markets are often characterized by low to middle income but with rapid economic growth, as well as financial liberalization and institutional development. As of Dec. 31, 2025, the MSCI Emerging Markets Index consisted of the following 24 emerging markets countries: Brazil, Chile, China, Colombia, Czech Republic, Egypt, Greece, Hungary, India, Indonesia, Korea, Kuwait, Malaysia, Mexico, Peru, Philippines, Poland, Qatar, Saudi Arabia, South Africa, Taiwan, Thailand, Turkey and United Arab Emirates. In addition to excluding stocks in specific countries as a result of the Fund’s investment models, the Adviser may avoid investing in a given country for which the transaction costs of investing exceed the benefits of investing in that country.

 

The equity securities in which the Fund invests are primarily common stocks and depositary receipts, including unsponsored depositary receipts, but may also include preferred stocks, exchange-traded funds (“ETFs”), and securities of other investment companies. The Fund may

invest in securities of companies with any market capitalization with a particular focus on mid- and large-capitalization securities.

 

From time to time, the Fund may focus its investments in a particular country, such as the People’s Republic of China (“China”). The Fund may invest in A-Shares of companies based 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”). Stock Connect is a mutual stock market access program designed to, among other things, enable foreign investments in China.

 

The Fund is primarily made up of stocks in emerging market companies that are selected using a quantitative investment approach with human discretion. In quantitative investment strategies, investment decisions are made using large amounts of data and computer models. However, the Adviser has the discretion to adjust trades based on news, liquidity, or additional insights from the Adviser’s portfolio management team. The Adviser’s quantitative investment models, which incorporate machine learning, allocate more weight to stocks for which the models identify the potential for higher future returns, taking into account risk (i.e., risk-adjusted returns), and less weight to stocks for which the models identify the potential for lower future risk-adjusted returns. The Adviser’s portfolio management team may adjust portfolio weights for the Fund based on their own analysis of the securities in the Fund’s investment universe in order to enhance evaluations made by the quantitative model. In addition to excluding stocks in specific countries as a result of the Fund’s investment models, the Adviser may avoid investing in a given country for which the transaction costs of investing exceed the benefits of investing in that country. Due to its investment strategy, the Fund may buy and sell securities frequently.

 

The Adviser uses data from a variety of sources, including data purchased from vendors and data accessed by the Adviser from alternative sources (e.g., data collected from public websites). Such data are collected at varying frequencies (e.g., daily price data, quarterly financial statements) and considered over varying horizons, ranging from months to years, depending on the nature of the data in question. The Adviser employs a proprietary data cleaning process, whereby data obtained from vendors and other sources is inspected for errors, processed to make information obtained from different sources useful in comparing various companies, sectors, and markets, and formatted for inclusion in the Adviser’s database and for use in its models. The Adviser monitors its data and models through a combination of automated and manual checks. The Adviser pays for data used in the strategy’s models.