Dominant Strategy : Speculative Trend
Time series to forecast n: 16 Jun 2023 for 4 Weeks
Methodology : Modular Neural Network (Market News Sentiment Analysis)
Abstract
Suncor Energy Inc. prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Stepwise Regression1,2,3,4 and it is concluded that the SU:TSX stock is predictable in the short/long term. A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Speculative Trend
Key Points
- Can statistics predict the future?
- What are buy sell or hold recommendations?
- Stock Forecast Based On a Predictive Algorithm
SU:TSX Target Price Prediction Modeling Methodology
We consider Suncor Energy Inc. Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of SU:TSX 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(Stepwise Regression)5,6,7= X R(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ 4 Weeks
n:Time series to forecast
p:Price signals of SU:TSX stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Modular Neural Network (Market News Sentiment Analysis)
A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.Stepwise Regression
Stepwise regression is a method of variable selection in which variables are added or removed from a model one at a time, based on their statistical significance. There are two main types of stepwise regression: forward selection and backward elimination. In forward selection, variables are added to the model one at a time, starting with the variable with the highest F-statistic. The F-statistic is a measure of how much improvement in the model is gained by adding the variable. Variables are added to the model until no variable adds a statistically significant improvement to the model.
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?
SU:TSX Stock Forecast (Buy or Sell) for 4 Weeks
Sample Set: Neural NetworkStock/Index: SU:TSX Suncor Energy Inc.
Time series to forecast n: 16 Jun 2023 for 4 Weeks
According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Speculative Trend
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 Suncor Energy Inc.
- As with all fair value measurements, an entity's measurement method for determining the portion of the change in the liability's fair value that is attributable to changes in its credit risk must make maximum use of relevant observable inputs and minimum use of unobservable inputs.
- An entity has not retained control of a transferred asset if the transferee has the practical ability to sell the transferred asset. An entity has retained control of a transferred asset if the transferee does not have the practical ability to sell the transferred asset. A transferee has the practical ability to sell the transferred asset if it is traded in an active market because the transferee could repurchase the transferred asset in the market if it needs to return the asset to the entity. For example, a transferee may have the practical ability to sell a transferred asset if the transferred asset is subject to an option that allows the entity to repurchase it, but the transferee can readily obtain the transferred asset in the market if the option is exercised. A transferee does not have the practical ability to sell the transferred asset if the entity retains such an option and the transferee cannot readily obtain the transferred asset in the market if the entity exercises its option
- Lifetime expected credit losses are generally expected to be recognised before a financial instrument becomes past due. Typically, credit risk increases significantly before a financial instrument becomes past due or other lagging borrower-specific factors (for example, a modification or restructuring) are observed. Consequently when reasonable and supportable information that is more forward-looking than past due information is available without undue cost or effort, it must be used to assess changes in credit risk.
- In some jurisdictions, the government or a regulatory authority sets interest rates. For example, such government regulation of interest rates may be part of a broad macroeconomic policy or it may be introduced to encourage entities to invest in a particular sector of the economy. In some of these cases, the objective of the time value of money element is not to provide consideration for only the passage of time. However, despite paragraphs B4.1.9A–B4.1.9D, a regulated interest rate shall be considered a proxy for the time value of money element for the purpose of applying the condition in paragraphs 4.1.2(b) and 4.1.2A(b) if that regulated interest rate provides consideration that is broadly consistent with the passage of time and does not provide exposure to risks or volatility in the contractual cash flows that are inconsistent with a basic lending arrangement.
*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
Suncor Energy Inc. is assigned short-term Ba1 & long-term Ba1 estimated rating. Suncor Energy Inc. prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Stepwise Regression1,2,3,4 and it is concluded that the SU:TSX stock is predictable in the short/long term. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Speculative Trend
SU:TSX Suncor Energy Inc. Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Ba3 | Baa2 |
Balance Sheet | B3 | Baa2 |
Leverage Ratios | C | Ba3 |
Cash Flow | Caa2 | B1 |
Rates of Return and Profitability | Ba1 | Baa2 |
*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
References
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- Li L, Chen S, Kleban J, Gupta A. 2014. Counterfactual estimation and optimization of click metrics for search engines: a case study. In Proceedings of the 24th International Conference on the World Wide Web, pp. 929–34. New York: ACM
- Chen X. 2007. Large sample sieve estimation of semi-nonparametric models. In Handbook of Econometrics, Vol. 6B, ed. JJ Heckman, EE Learner, pp. 5549–632. Amsterdam: Elsevier
- Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Is FFBC Stock Buy or Sell?(Stock Forecast). AC Investment Research Journal, 101(3).
- Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
Frequently Asked Questions
Q: What is the prediction methodology for SU:TSX stock?A: SU:TSX stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Stepwise Regression
Q: Is SU:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend SU:TSX Stock.
Q: Is Suncor Energy Inc. stock a good investment?
A: The consensus rating for Suncor Energy Inc. is Speculative Trend and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of SU:TSX stock?
A: The consensus rating for SU:TSX is Speculative Trend.
Q: What is the prediction period for SU:TSX stock?
A: The prediction period for SU:TSX is 4 Weeks
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