0000809593 2024-03-15 2024-03-15 0000809593 abf:S000051599Member 2024-03-15 2024-03-15 0000809593 abf:S000051599Member abf:ModelAndDataProgrammingErrorRiskMember 2024-03-15 2024-03-15 0000809593 abf:S000035897Member 2024-03-15 2024-03-15 0000809593 abf:S000035897Member abf:GrowthCompaniesRiskMember 2024-03-15 2024-03-15 0000809593 abf:S000035897Member abf:ModelAndDataProgrammingErrorRiskMember 2024-03-15 2024-03-15 iso4217:USD pure false 0000809593 AMERICAN BEACON FUNDS 497 N-1A 2023-12-31 2024-03-15 2024-03-15 2024-03-15 The Fund invests in a diversified portfolio of stocks of large capitalization companies that are listed on the New York Stock Exchange, NYSE American, or Nasdaq. Under normal circumstances, the Fund invests at least 80% of its net assets (plus borrowings for investment purposes) in stocks from among those in the large-cap growth category at the time of purchase. For purposes of the Fund's investments, "large-cap stocks" are common stocks of companies whose market capitalization (stock market worth) falls within the range of the Russell 1000® Index at the time of investment. The Russell 1000 Index is an unmanaged, market value weighted index, which measures the performance of approximately 1,000 of the largest companies in the U.S. equity market. The Russell 1000 Index is reconstituted from time to time. The market capitalization range for the Russell 1000 Index was $353.3 million to $2.9 trillion as of January 31, 2024. The Fund’s sub-advisor, Numeric Investors LLC (“Numeric”), uses a proprietary model-driven quantitative approach to select large-cap growth stocks generally represented in the Russell 1000® Growth Index, plus large capitalization stocks with similar "growth" characteristics that are not represented in the Russell 1000 Growth Index (collectively, “large-cap growth” stocks). The Russell 1000 Growth Index includes those Russell 1000 companies with higher price-to-book ratios and higher forecasted growth values. Numeric selects stocks that have, in its opinion, attractive valuations, positive long-term growth characteristics, sustainable competitive advantages, relatively benign competitive environments, and favorable industry dynamics. In seeking to achieve this goal, stocks are selected from the universe using a balance of proprietary quantitative models that blend fundamental investment concepts with other uncorrelated drivers of stock returns to aid in forecasting a company’s long term business prospects. A discretionary overlay based on fundamental research supplements the quantitative models to verify data, validate assumptions, and incorporate any insights that may not be picked up by the models. The discretionary overlay is expected to operate only to exclude stocks from the portfolio that have been recommended by the models. The overlay will not identify stocks for investment outside of the models. Based on statistically driven rules in the quantitative models, securities are sold in Numeric’s discretion for various reasons, including, without limitation, when they fall into the bottom 50% of the stock selection universe, the reasons for selecting the stock are no longer valid, or when necessary to maintain the risk profile of the overall Fund. Numeric will not necessarily sell a stock if it “migrates” outside the market capitalization range of the Russell 1000 Index after purchase or if a stock begins to have characteristics of a “value” stock as opposed to a growth stock. As a result, the Fund may invest in stocks that are no longer large-cap growth stocks, including stocks of mid-capitalization companies and stocks that exhibit value characteristics. Numeric’s investment process incorporates environmental, social and/or governance (“ESG”) analysis as a consideration in the assessment of potential portfolio investments. However, as ESG information is just one investment consideration, ESG considerations are not solely determinative in any investment decision made. In addition, Numeric does not use ESG considerations to limit, restrict or otherwise exclude companies or sectors from the Fund’s investment universe. Numeric may use ESG research and/or ratings information provided by one or more third parties in performing this analysis and considering ESG risks. Although the Fund seeks investments across a number of sectors, from time to time, the Fund may have significant positions in particular sectors, including the Information Technology sector. However, as the sector composition of the Fund's portfolio changes over time, the Fund's exposure to the Information Technology sector may be lower at a future date, and the Fund's exposure to other market sectors may be higher. The Fund may invest cash balances in a government money market fund advised by the Manager, with respect to which the Manager receives a management fee. The Fund also may purchase and sell equity index futures contracts to gain market exposure on cash balances or reduce market exposure in anticipation of liquidity needs. The Fund may seek to earn additional income by lending its securities to certain qualified broker-dealers and institutions. Model and Data/Programming Error Risk The success of the sub-advisor’s investment strategy depends largely on the effectiveness of its quantitative research models and investment programs. Models (including quantitative models), data, and investment programs are used to screen potential investments for the Fund. When models or data prove to be incorrect or incomplete, any decisions made in reliance thereon expose the Fund to potential risks and programs may not react as expected to market events, resulting in losses for the Fund. Some of the models used by the sub-advisor are predictive in nature. The use of predictive models has inherent risks. Because predictive models are usually constructed based on historical data supplied by third parties, the success of relying on such models may depend heavily on the accuracy and reliability of the supplied historical data. There is no assurance that the models are complete or accurate, or representative of future market cycles, nor will they always be beneficial to the Fund if they are accurate. Additionally, programs may become outdated or experience malfunctions which may not be identified by the sub-advisor and therefore may also result in losses to the Fund. These models and programs may negatively affect Fund performance for various other reasons, including human judgment, inaccuracy of historical data and non-quantitative factors (such as market or trading system dysfunctions, investor fear or overreaction). Models and data are known to have errors, omissions, imperfections, and malfunctions (collectively, “System Events”). The sub-advisor seeks to reduce the incidence and impact of System Events, to the extent feasible, through a combination of internal testing, simulation, real-time monitoring, and use of independent safeguards in the overall portfolio management process and often in the software code itself. Despite such testing, monitoring and independent safeguards, System Events will result in, among other things, the execution of unanticipated trades, the failure to execute anticipated trades, delays in the execution of anticipated trades, the failure to properly allocate trades, the failure to properly gather and organize available data, the failure to take certain hedging or risk reducing actions and/or the taking of actions which increase certain risk(s) - all of which may have materially adverse effects on the Fund. System Events in third-party provided data are generally entirely outside the control of the sub-advisor. The Fund invests in a diversified portfolio of stocks of large capitalization companies that are listed on the New York Stock Exchange, NYSE American, or Nasdaq. Under normal market conditions, at least 80% of the Fund’s net assets (plus borrowings for investment purposes) are invested in stocks from among those in the large-cap value category at the time of purchase. For purposes of the Fund's investments, "large-cap stocks" are common stocks of companies whose market capitalization (stock market worth) falls within the range of the Russell 1000® Index at the time of investment. The Russell 1000 Index is an unmanaged, market value weighted index, which measures the performance of approximately 1,000 of the largest companies in the U.S. equity market. The Russell 1000 Index is reconstituted from time to time. The market capitalization range for the Russell 1000 Index was $353.3 million to $2.9 trillion as of January 31, 2024. The Fund’s sub-advisor, Numeric Investors LLC (“Numeric”), uses a proprietary model-driven quantitative approach to select large-cap value stocks generally represented in the Russell 1000® Value Index, plus large capitalization stocks with similar “value” characteristics that are not represented in the Russell 1000 Value Index (collectively, “large-cap value” stocks). The Russell 1000 Value Index includes those Russell 1000 companies with lower price-to-book ratios and lower forecasted growth values. Numeric selects stocks that have, in its opinion, attractive valuations, positive long-term growth characteristics, sustainable competitive advantages, relatively benign competitive environments, and favorable industry dynamics. In seeking to achieve this goal, stocks are selected from the universe using a balance of proprietary quantitative models that blend fundamental investment concepts with other uncorrelated drivers of stock returns to aid in forecasting a company’s long term business prospects. A discretionary overlay based on fundamental research supplements the quantitative models to verify data, validate assumptions, and incorporate any insights that may not be picked up by the models. The discretionary overlay is expected to operate only to exclude stocks from the portfolio that have been recommended by the models. The overlay will not identify stocks for investment outside of the models. Based on statistically driven rules in the quantitative models, securities are sold in Numeric’s discretion for various reasons, including, without limitation, when they fall into the bottom 50% of the stock selection universe, the reasons for selecting the stock are no longer valid, or when necessary to maintain the risk profile of the overall Fund. Numeric will not necessarily sell a stock if it “migrates” outside the market capitalization range of the Russell 1000 Index after purchase or if a stock begins to have characteristics of a “growth” stock as opposed to a value stock. As a result, the Fund may invest in stocks that are no longer large-cap value stocks, including stocks of mid-capitalization companies and stocks that exhibit growth characteristics. Numeric’s investment process incorporates environmental, social and/or governance (“ESG”) analysis as a consideration in the assessment of potential portfolio investments. However, as ESG information is just one investment consideration, ESG considerations are not solely determinative in any investment decision made. In addition, Numeric does not use ESG considerations to limit, restrict or otherwise exclude companies or sectors from the Fund’s investment universe. Numeric may use ESG research and/or ratings information provided by one or more third parties in performing this analysis and considering ESG risks. The Fund may invest cash balances in a government money market fund advised by the Manager, with respect to which the Manager receives a management fee. The Fund also may purchase and sell equity index futures contracts to gain market exposure on cash balances or reduce market exposure in anticipation of liquidity needs. The Fund may seek to earn additional income by lending its securities to certain qualified broker-dealers and institutions. Growth Companies Risk Growth companies are expected to increase their earnings at a certain rate. When these expectations are not met or decrease, the prices of these stocks may decline, sometimes sharply, even if earnings showed an absolute increase. The Fund’s investments in growth companies may be more sensitive to company earnings and more volatile than the market in general primarily because their stock prices are based heavily on future expectations. If an assessment of the prospects for a company’s growth is incorrect, then the price of the company’s stock may fall or not approach the value placed on it. Growth company stocks may also lack the dividend yield that can cushion stock price declines in market downturns. Model and Data/Programming Error Risk The success of the sub-advisor’s investment strategy depends largely on the effectiveness of its quantitative research models and investment programs. Models (including quantitative models), data, and investment programs are used to screen potential investments for the Fund. When models or data prove to be incorrect or incomplete, any decisions made in reliance thereon expose the Fund to potential risks and programs may not react as expected to market events, resulting in losses for the Fund. Some of the models used by the sub-advisor are predictive in nature. The use of predictive models has inherent risks. Because predictive models are usually constructed based on historical data supplied by third parties, the success of relying on such models may depend heavily on the accuracy and reliability of the supplied historical data. There is no assurance that the models are complete or accurate, or representative of future market cycles, nor will they always be beneficial to the Fund if they are accurate. Additionally, programs may become outdated or experience malfunctions which may not be identified by the sub-advisor and therefore may also result in losses to the Fund. These models and programs may negatively affect Fund performance for various other reasons, including human judgment, inaccuracy of historical data and non-quantitative factors (such as market or trading system dysfunctions, investor fear or overreaction). Models and data are known to have errors, omissions, imperfections, and malfunctions (collectively, “System Events”). The sub-advisor seeks to reduce the incidence and impact of System Events, to the extent feasible, through a combination of internal testing, simulation, real-time monitoring, and use of independent safeguards in the overall portfolio management process and often in the software code itself. Despite such testing, monitoring and independent safeguards, System Events will result in, among other things, the execution of unanticipated trades, the failure to execute anticipated trades, delays in the execution of anticipated trades, the failure to properly allocate trades, the failure to properly gather and organize available data, the failure to take certain hedging or risk reducing actions and/or the taking of actions which increase certain risk(s) - all of which may have materially adverse effects on the Fund. System Events in third-party provided data are generally entirely outside the control of the sub-advisor.