v3.26.3
Investment Strategy
Oct. 31, 2026
Intelligent Alpha Atlas ETF  
Prospectus [Line Items]  
Strategy [Heading] PRINCIPAL INVESTMENT STRATEGIES
Strategy Narrative [Text Block]
The Fund is an actively-managed exchange-traded fund (“ETF”) that invests in a portfolio of U.S.-listed stocks and depositary receipts of foreign companies based on a proprietary artificial intelligence-powered stock selection strategy developed by Intelligent Alpha, LLC, the Fund’s investment sub-adviser (the “Sub-Adviser”). The Fund typically invests in 60–90 companies, each with a market capitalization greater than US$1 billion at the time the company is added to the Fund’s portfolio. The Sub-Adviser’s process relies on large language models, which are a type of artificial intelligence (“AI”) algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate, and predict new content.
The Sub-Adviser begins by prompting three separate models to each identify the six trading themes in the current market that the model believes will offer the strongest performance over the next 12 months. Examples of these themes include AI infrastructure, global defense and rearmament, and small-cap strength. Themes may be based on industry developments, macroeconomic trends, company fundamentals, technical indicators, broad-based exposures, or any other common factor identified by the models. While uncommon, the models may also suggest a theme that reflects having short exposure to a group of securities (i.e., anticipating that the value of the securities will decline).
As part of the Sub-Adviser’s prompting of the AI models, the Sub-Adviser provides the models with examples of well-known investment managers (e.g., large private fund managers) for which ample information about their holdings, strategies, techniques, and commentary on markets is publicly available. The models may identify themes based on the activities of those managers or identify themes based on information unrelated to those managers. In identifying themes for the Fund, the AI models will analyze numerous information sources (e.g., 13F filings, public statements, and interviews), as well as general news, publicly available investment, economic, or other data, websites, and other information accessible to the models. Form 13F is a quarterly report filed by institutional investment managers to disclose their U.S. equity holdings to the SEC.
Once each model has selected its themes, the Sub-Adviser provides the models with access to fundamental data about all companies in the Fund’s investment universe and prompts the models to return the top five stocks or depositary receipts for each investment theme based on the model’s expectations for performance over the next 12 months. The data set includes information from one or more third-party data providers (e.g., FactSet) and is used to ensure the models have access to reliable information about each company’s fundamentals (e.g., revenue, earnings, or free cash flow) in addition to the other information to which the models may have access. The models are not required to use the data set provided and may choose to use other information to which they have access instead. For certain data points, the models may rely on third-party information (e.g., consensus earnings estimates) or calculate their own estimates of future activity (e.g., earnings) based on the information available to them. The models may select their securities directly from an analysis of individual companies or may identify other ETFs with a strategy tied to a particular theme and use the holdings of that ETF as a narrower universe from which to select stocks.
Each model is then asked to compile a portfolio of up to 30 selected stocks (i.e., five stocks from each of six themes), with each stock weighted based on the model’s conviction with respect to each theme, subject to a 30% cap on the weight for any single company for a particular theme. The model may select the same stock for more than one theme. Each proposed portfolio is then subject to review by a human analyst at the Sub-Adviser. The analyst reviews the portfolio to ensure that each stock selected is an eligible holding for the Fund. The Sub-Adviser ultimately compiles the portfolio for the Fund such that one-third of the Fund’s portfolio is allocated based on the selections by each model and no single security comprises more than 10% of the Fund’s portfolio. If a single security would exceed 10%, the excess weight is redistributed to other securities in the same theme.
The Sub-Adviser expects that the Fund will predominantly hold equity securities (e.g., common stock) of U.S.-listed companies and depositary receipts of foreign companies. Depositary receipts represent shares in a foreign company that are traded on a local stock exchange. The Fund may also hold other ETFs, including leveraged, inverse, or inverse-leveraged ETFs, when a model determines that an ETF is a top investment holding for a particular theme or when an analyst determines that an ETF best represents a theme for which individual instruments are not eligible to be held by the Fund (e.g., the Fund may use a gold ETF if a model selects gold as a theme). If a model selects a theme of having short exposure to certain securities, the Fund may use an inverse ETF for such exposure.
The frequency and timing of a portfolio review is at the discretion of the Sub-Adviser but generally will be conducted at least quarterly. The resulting portfolio at the end of the process will replace the existing portfolio at the time of the review.
The Fund is expected to have high portfolio turnover based on its investment strategy.
Intelligent Omaha ETF  
Prospectus [Line Items]  
Strategy [Heading] PRINCIPAL INVESTMENT STRATEGIES
Strategy Narrative [Text Block]
The Fund uses Intelligent Alpha, LLC’s (the “Sub-Adviser”) proprietary artificial intelligence-powered stock selection strategy to create an intelligent custom-weighted portfolio of global large cap stocks with over $10 billion in market capitalization (the “Investment Universe”). The strategy generally focuses on high-quality companies, defined both qualitatively and quantitatively, and value. The securities held in the portfolio will be a byproduct of the themes identified by artificial intelligence (“AI”), as described in more detail below. This is collectively referred to herein as the “Intended Strategy.”
The Sub-Adviser’s AI-powered stock selection process uses three steps:
Step 1: Human initiation. A human analyst (the “Analyst”) establishes the intended strategy for the underlying portfolio including the target investment universe, the portfolio size, the intended concentration level (e.g., maximum security weighting), and any specific factors or themes to be highlighted in the portfolio (e.g. dividends, quality). The Analyst then uses a template to collect historical data and forward estimates of certain data such as revenue, earnings, free cash flow, etc. from a third-party data source (e.g., Factset). The Analyst may add certain additional data that is relevant to the intended strategy (e.g., data on revenue or earning growth for a growth-oriented strategy). This information is to be used in quantitative analysis by AI that is relevant to stocks in the Investment Universe. Finally, the Analyst defines a philosophy for the AI to use for qualitative analysis of stocks in the Investment Universe given the Intended Strategy.
The Analyst has defined the Fund’s Investment Universe as global equity securities with a market capitalization of over $10 billion at the time of the AI’s review. Global equity securities are common stocks, including American Depositary Receipts (“ADRs”), European Depositary Receipts (“EDRs”) and Global Depositary Receipts (“GDRs”) of companies that are located throughout the world and that are listed on a regulated stock exchange. The number of stocks in the portfolio is expected to be between 25-30 stocks. Given that universe, a selection set of companies in the Investment Universe with sufficient data about revenue growth, earnings, free cash flow, price to earnings ratio, beta and other financial metrics are collected by the Analyst. Sufficient data is generally considered to be 50% of the data entries in the overall dataset that is sought by the AI model.
The Analyst has also defined the Fund’s philosophy, which is built on the ideas of the world’s greatest investors with an emphasis on returns on invested capital, enduring business models with the ability to serve customers for long periods of time, and long-term business ownership (the “Philosophy”). The Analyst will define the list of the world’s greatest investors for the AI. The Analyst focuses on investors with a strong view toward quality and value investments with the potential for multi-year investment duration. The AI will analyze numerous information sources (such as 13F filings, public statements, and interviews) related to the identified investors to determine the kinds of stocks that fit the Philosophy. Form 13F is a quarterly report filed by institutional investment managers to disclose their U.S. equity holdings to the SEC. The Philosophy is part of the instruction set that is provided by the Analyst to the AI as described in subsequent steps.
Step 2: AI portfolio creation. The Analyst gathers the details, information and Philosophy set forth in Step 1 and translates it into an instruction set to be submitted to three large language models, which is a type of AI algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content (the “AI Models”) for portfolio creation. Each AI Model is similarly instructed to review the data and instructions to create a portfolio of up to 10 stocks each. The AI Models are instructed to limit the maximum weight of any one holding to 10%. Each AI Model has its own discretion in creating its portfolio, which is reviewed by the Analyst in Step 3. The AI Models represent the Fund’s AI investment committee, whereby the AI Models provide their independently created portfolios based on each AI Model’s independent evaluation of the instructions provided to it.
The submission of the data and Philosophy initiates the process for each AI Model to review the instruction set and create the portfolio. The Analyst works with each AI Model to create a portfolio of up to 10 stocks each.
Step 3: Analyst portfolio review. After the three AI Models create their respective portfolios, the Analyst reviews each portfolio to ensure it adheres to the Intended Strategy and any applicable regulatory requirements. Any stocks that are included in the AI Models but do not fit the Investment Universe or Intended Strategy are excluded by the Analyst with the weight of any removed stocks redistributed pro rata across the particular AI portfolio. Overlapping stock selections among the AI Model portfolios are eliminated. Determination of whether stocks fit the Fund’s Intended Strategy and Philosophy is at the final discretion of the Analyst.
In constructing the Fund’s portfolio, the Analyst aggregates the three AI-powered portfolios into a single portfolio of up to 30 stocks, which is then submitted to each AI investment committee member to assign weights based on the AI’s confidence in the stock’s potential to outperform a broader universe of large cap global equities (e.g., the MSCI All-World Index) and fit for the strategy. The Analyst then aggregates the three weighted AI-powered portfolios into a single portfolio where each of the individual portfolios created by the AI Models make up one-third of the overall portfolio.
A portfolio review, including the list of great investors, is initiated by the Analyst via the same process described above. The frequency and timing of portfolio review is at the discretion of the Analyst but generally a portfolio review will be conducted on a quarterly basis. The new resultant portfolio at the end of the process will replace the existing portfolio at the time of the review.
The Fund typically rebalances quarterly in February, May, August, and November; however, the Analyst has discretion to review the portfolio more or less frequently.
The Fund is expected to have high portfolio turnover based on historical testing of the Fund’s investment strategy. During the portfolio review process the AI may remove or add stocks to the portfolio or change the weight of stocks already in the portfolio.
The Fund will be considered to be non-diversified, which means that it may invest more of its assets in the securities of a single issuer or a smaller number of issuers than if it were a diversified fund.
Intelligent Equal Select ETF  
Prospectus [Line Items]  
Strategy [Heading] PRINCIPAL INVESTMENT STRATEGIES
Strategy Narrative [Text Block]
The Intelligent Equal Select ETF uses Intelligent Alpha, LLC’s (the “Sub-Adviser”) proprietary artificial intelligence-powered stock selection strategy to create an intelligent equal weight portfolio of U.S. large cap stocks with over $10 billion in market capitalization (the “Investment Universe”). The securities held in the portfolio will be a byproduct of the themes identified by artificial intelligence (“AI”), as described in more detail below. This is collectively referred to herein as the “Intended Strategy.”
The Sub-Adviser’s AI-powered stock selection process uses three steps:
Step 1: Human initiation. A human analyst (the “Analyst”) establishes the intended strategy for the underlying portfolio including the target investment universe, the portfolio size, the intended concentration level (e.g., maximum security weighting), and any specific factors or themes to be highlighted in the portfolio (e.g. dividends, quality). The Analyst then defines and collects data from a third-party data source (e.g., Factset) to be used in quantitative analysis by AI that is relevant to stocks in the universe given the intended strategy. Finally, the Analyst defines a philosophy for the AI to use for qualitative analysis of stocks in the universe given the intended strategy.
Given the Investment Universe, which is initially submitted to the AI at $15 billion in market capitalization, a selection set of companies in the Investment Universe with sufficient data about revenue growth, earnings, free cash flow, and other financial metrics are collected by the Analyst. Sufficient data is generally considered to be 50% of the data entries in the overall dataset that is sought by the AI. The Analyst has also defined the Fund’s philosophy, which is designed for a long-term oriented investor aiming to generate returns greater than the overall universe of large cap equity securities (the “Philosophy”). Returns are benchmarked by the Analyst against a broad-based equal-weighted U.S. large cap benchmark. The Philosophy is part of the instruction set that is provided by Analyst to the AI as described in subsequent steps.
Step 2: AI portfolio creation. The Analyst gathers the details, information and Philosophy set forth in Step 1 and translates it into an instruction set to be submitted to three large language models, which is a type of AI algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content (the “AI Models”) for
portfolio creation. Each AI Model is similarly instructed to review the data and instructions to create a portfolio. The portfolio will generally hold 150-250 stocks with no single security exceeding 3% of the portfolio. Each AI Model has its own discretion in creating its portfolio, which is reviewed by the Analyst in Step 3. The AI Models represent the Fund’s AI investment committee, whereby the AI Models provide their independently created portfolios based on each AI Model’s independent evaluation of the instructions provided to it.
The submission of the data and Philosophy initiates the process for each AI Model to review the instruction set and create a portfolio. The Analyst works with each AI Model to create a portfolio of up to 100 stocks per AI Model.
Step 3: Analyst portfolio review. After the three AI Models create their respective portfolios, the Analyst reviews each portfolio to ensure that it adheres to the Intended Strategy and any applicable regulatory requirements. Any stocks that are included in the AI Model portfolios that do not fit the Intended Strategy are excluded with the weight of removed stocks redistributed pro rata across the particular AI portfolio. Determination of whether stocks fit the Fund’s Intended Strategy and Philosophy is at the final discretion of the Analyst.
The market capitalization limitation of the Investment Universe of $15 billion is then adjusted to $10 billion for Analyst review to allow the AI Models some flexibility in individual stock selection.
The Analyst then aggregates the three AI-powered portfolios into a single portfolio where the base weight of each stock is one divided by the number of total stocks in all three portfolios including duplicates. Stocks that appear in multiple portfolios, which are represented as duplicates in the aggregated portfolio, will get the base weight times the number of times the stock appears across the individual AI-powered portfolios. For example, if AAPL were to appear in all three portfolios created by the AI investment committee members, AAPL’s weight would be three times the base weight of the overall portfolio.
A portfolio review is initiated generally on a quarterly basis by the Analyst via the same process described above. The new resultant portfolio at the end of the process will replace the existing portfolio at the time of the review.
The Fund is expected to have high portfolio turnover based on historical testing of the Fund’s investment strategy. During the portfolio review process the AI may remove or add stocks to the portfolio or change the weight of stocks already in the portfolio.
The Fund typically rebalances quarterly in February, May, August, and November; however, the Analyst has discretion to review more or less frequently.
Intelligent Tech Focus ETF  
Prospectus [Line Items]  
Strategy [Heading] PRINCIPAL INVESTMENT STRATEGIES
Strategy Narrative [Text Block]
The Fund uses Intelligent Alpha, LLC’s (the “Sub-Adviser”) proprietary artificial intelligence-powered stock selection strategy to create an intelligent custom-weighted portfolio of U.S. large cap tech stocks (the “Intended Strategy”).
The Sub-Adviser’s artificial intelligence-powered stock selection process uses three steps:
Step 1: Human initiation. A human analyst (the “Analyst”) establishes the Intended strategy for the underlying portfolio including the target investment universe, the portfolio size, the intended concentration level (e.g., maximum security weighting), and any specific factors or themes to be highlighted in the portfolio (e.g. dividends, quality). The Analyst then defines and collects data from a third-party data source (e.g., Factset) to be used in quantitative analysis by artificial intelligence (“AI”) that is relevant to stocks in the universe given the Intended strategy. Finally, the Analyst defines a philosophy for the AI to use for qualitative analysis of stocks in the universe given the Intended strategy.
The Analyst has defined the Fund’s investment universe as US-listed equity securities of technology companies with a market capitalization of over $15 billion at the time of the AI’s review (the “Investment Universe”). The number of stocks in the portfolio is expected to be between 25-30 stocks with no single security exceeding 10% of the portfolio. Given that Investment Universe, a selection set of companies in the Investment Universe with sufficient data about revenue growth, earnings, free cash flow and other financial metrics are collected by the Analyst. Sufficient data is generally considered to be 50% of the data entries in the overall dataset that is sought by the AI. The Analyst has also defined the Fund’s philosophy, which is designed for a long-term, growth-focused investor aiming to generate returns greater than the overall universe of large cap equity securities of technology companies (the “Philosophy”). Returns are benchmarked against a broad-based information technology sector index. The Philosophy is part of the instruction set that is provided by Analyst to the AI as described in subsequent steps.
Step 2: AI portfolio creation. The Analyst gathers the details, information and Philosophy set forth in Step 1 and translates it into an instruction set to be submitted to three large language models, which is a type of AI algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content (the “AI Models”) for
portfolio creation. Each AI Model is similarly instructed to review the data and instructions to create a portfolio. The AI Models are instructed to limit the maximum weight of any one holding to 10%. Each AI Model has its own discretion in creating its portfolio, which is reviewed by the Analyst in Step 3. The AI Models represent the Fund’s AI investment committee, whereby the AI Models provide their independently created portfolios based on each AI Model’s independent evaluation of the instructions provided to it.
The submission of the data and Philosophy initiates the process for each AI Model to review the instruction set and create the portfolio. The Analyst works with each AI Model to create a portfolio of up 10 stocks each.
Step 3: Analyst portfolio review. After the three AI Models create their respective portfolios, the Analyst reviews each portfolio to ensure that each portfolio adheres to the Intended Strategy and any applicable regulatory requirements. Any stocks that are included in the AI Models but do not fit the Intended Strategy are excluded with the weight of removed stocks redistributed pro rata across the portfolio. Determination of whether a stock fits the Fund’s Intended Strategy and Philosophy is at the final discretion of the Analyst. Overlapping stock selections are eliminated.
The Analyst then aggregates the three AI-powered portfolios into a single portfolio of up to 30 stocks which is then submitted to each AI committee member to assign weights for each security based on the AI’s confidence in the stock’s potential to outperform the broader universe of large cap equity securities of technology companies (e.g., the Nasdaq 100 Index). The Analyst then aggregates the three weighted AI-powered portfolios into a single portfolio where each of the individual portfolios created by the AI makes up one-third of the overall portfolio.
A portfolio review is initiated by the Analyst generally on a quarterly basis via the same process described above. The frequency and timing of portfolio review is at the discretion of the Analyst. The new resultant portfolio at the end of the process will replace the existing portfolio at the time of the review.
The Fund typically rebalances quarterly in February, May, August, and November; however, the Analyst has discretion to review more or less frequently.
The Fund is expected to have high portfolio turnover based on historical testing of the Fund’s investment strategy. During the portfolio review process the AI may remove or add stocks to the portfolio or change the weight of stocks already in the portfolio.
The Fund will be considered to be non-diversified, which means that it may invest more of its assets in the securities of a single issuer or a smaller number of issuers than if it were a diversified fund.
The Fund will concentrate its investments (i.e., hold 25% or more of its total assets) in companies in the information technology sector. Under normal circumstances, at least 80% of the Fund’s net assets, plus any borrowings for investment purposes, will be invested in equity securities of technology companies. The Fund considers a company to be a technology company if it is classified in the information technology sector by a recognized industry classification system.
Rule 35d-1 Eighty Percent Investment Policy [Text Block] Under normal circumstances, at least 80% of the Fund’s net assets, plus any borrowings for investment purposes, will be invested in equity securities of technology companies. The Fund considers a company to be a technology company if it is classified in the information technology sector by a recognized industry classification system.
Strategy Portfolio Concentration [Text] The Fund will concentrate its investments (i.e., hold 25% or more of its total assets) in companies in the information technology sector.
Intelligent Small Cap Select ETF  
Prospectus [Line Items]  
Strategy [Heading] PRINCIPAL INVESTMENT STRATEGIES
Strategy Narrative [Text Block]
The Fund uses Intelligent Alpha, LLC’s (the “Sub-Adviser”) proprietary artificial intelligence-powered stock selection strategy to create a custom-weighted portfolio of U.S. small cap stocks (the “Intended Strategy”).
The Sub-Adviser’s artificial intelligence-powered stock selection process uses three steps:
Step 1: Human initiation. A human analyst (the “Analyst”) establishes the Intended strategy for the underlying portfolio including the target investment universe, the portfolio size, the intended concentration level (e.g., maximum security weighting), and any specific factors or themes to be highlighted in the portfolio (e.g. dividends, quality). The Analyst then defines and collects data from a third-party data source (e.g., Factset) to be used in quantitative analysis by artificial intelligence (“AI”) that is relevant to stocks in the universe given the Intended strategy. Finally, the Analyst defines a philosophy for the AI to use for qualitative analysis of stocks in the universe given the Intended strategy.
The Analyst has defined the Fund’s investment universe as US-listed equity securities with a market capitalization of over $1 billion and below $4 billion at the time of the AI’s review (the “Investment Universe”). The number of stocks in the portfolio is expected to be between 120-250 stocks and no single portfolio holding will exceed 3%. Given that Investment Universe, a selection set of companies in the Investment Universe with sufficient data about revenue growth, earnings, free cash flow and other financial metrics are collected by the Analyst. Sufficient data is generally considered to be 50% of the data entries in the overall dataset that is sought by the AI. The Analyst has also defined the Fund’s philosophy, which is designed for a long-term oriented investor aiming to generate returns greater than the overall universe of small cap equity securities, which is described for the AI (the “Philosophy”). Returns are benchmarked by the Analyst against a broad based small cap equity benchmark. The Philosophy is part of the instruction set that is provided by Analyst to the AI as described in subsequent steps.
Step 2: AI portfolio creation. The Analyst gathers the details, information and Philosophy set forth in Step 1 and translates it into an instruction set to be submitted to three large language models, which is a type of AI algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content (the “AI Models”) for
portfolio creation. Each AI Model is similarly instructed to review the data and instructions to create a portfolio of up to 100 stocks. Each AI Model has its own discretion in creating its portfolio, which is reviewed by the Analyst in Step 3. The AI Models represent the Fund’s AI investment committee, whereby the AI Models provide their independently created portfolios based on each AI Model’s independent evaluation of the instructions provided to it.
The submission of the data and Philosophy initiates the process for each AI Model to review the instruction set and create the portfolio. The Analyst works with each AI Model to create a portfolio of up to 100 stocks. Each AI Model is then requested to assign weights to its portfolio to reflect the AI’s confidence in each selection.
Step 3: Analyst portfolio review. After the three AI Models create their respective portfolios, the Analyst reviews each portfolio to ensure that it adheres to the Intended Strategy and any applicable regulatory requirements. Any stocks that are included in the AI Models but do not fit the Intended Strategy are excluded by the Analyst with the weight of removed stocks redistributed pro rata across the portfolio. Determination of whether stocks fit the Fund’s Intended Strategy and Philosophy is at the final discretion of the Analyst.
The AI Models are provided a buffer of 20% above and below the low-end market capitalization and high-end market capitalization for stocks they may add that are not in the initial selection set.
The Analyst then aggregates the three weighted AI-powered portfolios into a single portfolio where each of the individual portfolios created by the AI make up one-third of the overall portfolio.
A portfolio review is initiated generally on a quarterly basis by the Analyst via the same process described above. The new resultant portfolio at the end of the quarterly process will replace the existing portfolio at the time of the review.
The Fund is expected to have high portfolio turnover based on historical testing of the Fund’s investment strategy. During the portfolio review process the AI may remove or add stocks to the portfolio or change the weight of stocks already in the portfolio.
The Fund typically rebalances quarterly in February, May, August, and November; however, the Analyst has discretion to review more or less frequently.
Under normal circumstances, at least 80% of the Fund’s net assets, plus borrowings for investment purposes, will be invested in small cap companies.
Rule 35d-1 Eighty Percent Investment Policy [Text Block] Under normal circumstances, at least 80% of the Fund’s net assets, plus borrowings for investment purposes, will be invested in small cap companies.