AUC Score :
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n:
Methodology : Transfer Learning (ML)
Hypothesis Testing : Independent T-Test
Surveillance : Major exchange and OTC
1The accuracy of the model is being monitored on a regular basis.(15-minute period)
2Time series is updated based on short-term trends.
Summary
Brighthouse Financial Inc. 6.25% Junior Subordinated Debentures due 2058 (the "Debentures") are unsecured, subordinated debt obligations of Brighthouse Financial Inc. (the "Issuer"). The Debentures are issued in denominations of $2,000 and bear interest at a rate of 6.25% per annum, payable semi-annually on March 15 and September 15 of each year, commencing on March 15, 2023. The Debentures mature on March 15, 2058. The Debentures are subject to a number of covenants, including: * A limitation on the Issuer's indebtedness; * A requirement that the Issuer maintain certain financial ratios; * A restriction on the Issuer's ability to make certain distributions to shareholders; and * A requirement that the Issuer provide the trustee with annual audited financial statements. The Debentures are secured by a first-priority lien on all of the Issuer's assets, except for certain assets that are specifically excluded from the security interest. The Debentures are rated BBB- by Fitch Ratings and Baa3 by Moody's Investors Service. The Debentures were issued on March 15, 2023.
Key Points
- Transfer Learning (ML) for BHFAL stock price prediction process.
- Independent T-Test
- Probability Distribution
- Is Target price a good indicator?
- What are the most successful trading algorithms?
BHFAL Stock Price Forecast
We consider Brighthouse Financial Inc. 6.25% Junior Subordinated Debentures due 2058 Decision Process with Transfer Learning (ML) where A is the set of discrete actions of BHFAL stock holders, F is the set of discrete states, P : S × F × S → R is the transition probability distribution, R : S × F → R is the reaction function, and γ ∈ [0, 1] is a move factor for expectation.1,2,3,4
Sample Set: Neural Network
Stock/Index: BHFAL Brighthouse Financial Inc. 6.25% Junior Subordinated Debentures due 2058
Time series to forecast: 8 Weeks
According to price forecasts, the dominant strategy among neural network is: Buy
n:Time series to forecast
p:Price signals of BHFAL stock
j:Nash equilibria (Neural Network)
k:Dominated move of BHFAL stock holders
a:Best response for BHFAL target price
Transfer learning is a machine learning (ML) method where a model developed for one task is reused as the starting point for a model on a second task. This can be useful when the second task is similar to the first task, or when there is limited data available for the second task.5 An independent t-test is a statistical test that compares the means of two independent samples. In an independent t-test, the data points in each sample are not related to each other. The independent t-test is a parametric test, which means that it assumes that the data is normally distributed. The independent t-test is also a two-sample test, which means that it compares the means of two independent samples.6,7
For further technical information as per how our model work we invite you to visit the article below:
BHFAL Stock Forecast (Buy or Sell) Strategic Interaction Table
Strategic Interaction Table Legend:
X axis: *Likelihood% (The higher the percentage value, the more likely the event will occur.)
Y axis: *Potential Impact% (The higher the percentage value, the more likely the price will deviate.)
Z axis (Grey to Black): *Technical Analysis%
Financial Data Adjustments for Transfer Learning (ML) based BHFAL Stock Prediction Model
- A single hedging instrument may be designated as a hedging instrument of more than one type of risk, provided that there is a specific designation of the hedging instrument and of the different risk positions as hedged items. Those hedged items can be in different hedging relationships.
- For the purpose of this Standard, reasonable and supportable information is that which is reasonably available at the reporting date without undue cost or effort, including information about past events, current conditions and forecasts of future economic conditions. Information that is available for financial reporting purposes is considered to be available without undue cost or effort.
- An entity that first applies IFRS 17 as amended in June 2020 after it first applies this Standard shall apply paragraphs 7.2.39–7.2.42. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).
- Conversely, if changes in the extent of offset indicate that the fluctuation is around a hedge ratio that is different from the hedge ratio that is currently used for that hedging relationship, or that there is a trend leading away from that hedge ratio, hedge ineffectiveness can be reduced by adjusting the hedge ratio, whereas retaining the hedge ratio would increasingly produce hedge ineffectiveness. Hence, in such circumstances, an entity must evaluate whether the hedging relationship reflects an imbalance between the weightings of the hedged item and the hedging instrument that would create hedge ineffectiveness (irrespective of whether recognised or not) that could result in an accounting outcome that would be inconsistent with the purpose of hedge accounting. If the hedge ratio is adjusted, it also affects the measurement and recognition of hedge ineffectiveness because, on rebalancing, the hedge ineffectiveness of the hedging relationship must be determined and recognised immediately before adjusting the hedging relationship in accordance with paragraph B6.5.8.
*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.
BHFAL Brighthouse Financial Inc. 6.25% Junior Subordinated Debentures due 2058 Financial Analysis*
Brighthouse Financial Inc. 6.25% Junior Subordinated Debentures due 2058 are rated BBB by S&P and Baa2 by Moody's. The debentures are secured by a first lien on substantially all of Brighthouse's assets. The debentures mature on March 1, 2058. Brighthouse Financial is a life insurance company that provides life insurance, annuities, and other financial products to consumers in the United States. The company has a strong financial profile, with a Fitch rating of A-. Brighthouse's business is expected to continue to grow in the coming years, as the demand for life insurance and annuities remains strong. The company is also well-positioned to weather economic downturns, as its business is relatively recession-proof. As a result of these factors, the Brighthouse Financial Inc. 6.25% Junior Subordinated Debentures due 2058 are considered to be a safe investment. The debentures offer a high yield of 6.25%, and they are backed by a strong company with a good financial outlook. Here are some key financial metrics for Brighthouse Financial Inc. as of December 31, 2021: * Total assets: $132.9 billion * Total liabilities: $114.5 billion * Net income: $2.1 billion * Debt-to-equity ratio: 0.69 * Return on equity: 11.7% * Dividend yield: 5.0% Overall, Brighthouse Financial Inc. is a well-established company with a strong financial profile. The company's business is expected to continue to grow in the coming years, and the debentures offer a high yield and are backed by a strong company.Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Caa2 | B1 |
Income Statement | B1 | C |
Balance Sheet | C | Baa2 |
Leverage Ratios | C | Ba2 |
Cash Flow | B3 | Ba3 |
Rates of Return and Profitability | C | B3 |
*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?
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