SPB Spectrum Brands Holdings Inc. Common Stock

Outlook: Spectrum Brands Holdings Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 02 Jun 2023 for (n+8 weeks)
Methodology : Supervised Machine Learning (ML)

Abstract

Spectrum Brands Holdings Inc. Common Stock prediction model is evaluated with Supervised Machine Learning (ML) and Logistic Regression^1,2,3,4 and it is concluded that the SPB stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell

Key Points

1. Can machine learning predict?
2. What is Markov decision process in reinforcement learning?
3. Is it better to buy and sell or hold?

SPB Target Price Prediction Modeling Methodology

We consider Spectrum Brands Holdings Inc. Common Stock Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of SPB 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

F(Logistic Regression)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Supervised Machine Learning (ML)) X S(n):→ (n+8 weeks) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of SPB stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

 

For further technical information as per how our model work we invite you to visit the article below: 

How do AC Investment Research machine learning (predictive) algorithms actually work?

SPB Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: SPB Spectrum Brands Holdings Inc. Common Stock
Time series to forecast n: 02 Jun 2023 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell

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%

IFRS Reconciliation Adjustments for Spectrum Brands Holdings Inc. Common Stock

1. An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods only if it is possible to do so without the use of hindsight. If an entity restates prior periods, the restated financial statements must reflect all the requirements in this Standard for the affected financial instruments. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.
2. There are two types of components of nominal amounts that can be designated as the hedged item in a hedging relationship: a component that is a proportion of an entire item or a layer component. The type of component changes the accounting outcome. An entity shall designate the component for accounting purposes consistently with its risk management objective.
3. Annual Improvements to IFRSs 2010–2012 Cycle, issued in December 2013, amended paragraphs 4.2.1 and 5.7.5 as a consequential amendment derived from the amendment to IFRS 3. An entity shall apply that amendment prospectively to business combinations to which the amendment to IFRS 3 applies.
4. Rebalancing does not apply if the risk management objective for a hedging relationship has changed. Instead, hedge accounting for that hedging relationship shall be discontinued (despite that an entity might designate a new hedging relationship that involves the hedging instrument or hedged item of the previous hedging relationship as described in paragraph B6.5.28).

*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.

Conclusions

Spectrum Brands Holdings Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Spectrum Brands Holdings Inc. Common Stock prediction model is evaluated with Supervised Machine Learning (ML) and Logistic Regression^1,2,3,4 and it is concluded that the SPB stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell

SPB Spectrum Brands Holdings Inc. Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B1	Baa2
Balance Sheet	Caa2	B2
Leverage Ratios	Baa2	Baa2
Cash Flow	B1	B2
Rates of Return and Profitability	Baa2	B1

*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?

Prediction Confidence Score

Trust metric by Neural Network: 90 out of 100 with 754 signals.

References

1. Y. Le Tallec. Robust, risk-sensitive, and data-driven control of Markov decision processes. PhD thesis, Massachusetts Institute of Technology, 2007.
2. Andrews, D. W. K. W. Ploberger (1994), "Optimal tests when a nuisance parameter is present only under the alternative," Econometrica, 62, 1383–1414.
3. Blei DM, Lafferty JD. 2009. Topic models. In Text Mining: Classification, Clustering, and Applications, ed. A Srivastava, M Sahami, pp. 101–24. Boca Raton, FL: CRC Press
4. Jacobs B, Donkers B, Fok D. 2014. Product Recommendations Based on Latent Purchase Motivations. Rotterdam, Neth.: ERIM
5. Miller A. 2002. Subset Selection in Regression. New York: CRC Press
6. S. Proper and K. Tumer. Modeling difference rewards for multiagent learning (extended abstract). In Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, June 2012
7. Kallus N. 2017. Balanced policy evaluation and learning. arXiv:1705.07384 [stat.ML]

Frequently Asked Questions

Q: What is the prediction methodology for SPB stock?
A: SPB stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Logistic Regression
Q: Is SPB stock a buy or sell?
A: The dominant strategy among neural network is to Sell SPB Stock.
Q: Is Spectrum Brands Holdings Inc. Common Stock stock a good investment?
A: The consensus rating for Spectrum Brands Holdings Inc. Common Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of SPB stock?
A: The consensus rating for SPB is Sell.
Q: What is the prediction period for SPB stock?
A: The prediction period for SPB is (n+8 weeks)

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