Company: AOMN
Filing Date: 2025-03-24
Form Type: 10-K
Source: 0001766478-25-000019
Chunk: 58

Company: Angel Oak Mortgage REIT, Inc.
Filing Date: 2025-03-24
Form: 10-K
Item: Item 1A
Chunk 58
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 and amount of cash flows expected to be collected, and may also be used in connection with any hedging of our investments. Many of the models are based on historical trends. These trends may not be indicative of future results. Furthermore, the assumptions underlying the models may prove to be inaccurate, causing the models to also be incorrect. In the event models and data prove to be incorrect, misleading or incomplete, any decisions made in reliance thereon expose us to potential risks. For example, by relying on incorrect models and data, especially valuation or cash flow models, we may be induced to buy certain assets at prices that are too 

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high, to sell certain other assets at prices that are too low, to overestimate or underestimate the timing or amount of cash flows expected to be collected, or to miss favorable opportunities altogether. Similarly, any hedging activities based on faulty models and data may prove to be unsuccessful.

Some of the risks of relying on analytical models and third-party data include the following:

•collateral cash flows and/or liability structures may be incorrectly modeled in all or only certain scenarios, or may be modeled based on simplifying assumptions that lead to errors;

•information about assets or the underlying collateral may be incorrect, incomplete, or misleading;

•asset, collateral, RMBS or CMBS historical performance (such as historical prepayments, defaults, cash flows, etc.) may be incorrectly reported, or subject to interpretation; and

•asset, collateral, RMBS or CMBS information may be outdated, in which case the models may contain incorrect assumptions as to what has occurred since the date information was last updated.

Some models, such as prepayment models or default models, may be predictive in nature. The use of predictive models has inherent risks. For example, such models may incorrectly forecast future behavior, leading to potential losses. In addition, the predictive models used by our Manager may differ substantially from those models used by other market participants, with the result that valuations based on these predictive models may be substantially higher or lower for certain assets than actual market prices. Furthermore, 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, and, in the case of predicting performance in scenarios with little or no historical precedent (such as extreme broad-based declines in home prices, or deep economic recessions or depressions), such models must employ greater degrees of extrapolation and are therefore more speculative and of more limited reliability.

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