Dominant Strategy : Buy
Time series to forecast n: 22 Jan 2023 for (n+6 month)
Methodology : Modular Neural Network (DNN Layer)
Abstract
BELLUS Health Inc. prediction model is evaluated with Modular Neural Network (DNN Layer) and Beta1,2,3,4 and it is concluded that the BLU:TSX stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: BuyKey Points
- Can stock prices be predicted?
- Buy, Sell and Hold Signals
- Prediction Modeling
BLU:TSX Target Price Prediction Modeling Methodology
We consider BELLUS Health Inc. Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of BLU: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(Beta)5,6,7= X R(Modular Neural Network (DNN Layer)) X S(n):→ (n+6 month)
n:Time series to forecast
p:Price signals of BLU:TSX 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?
BLU:TSX Stock Forecast (Buy or Sell) for (n+6 month)
Sample Set: Neural NetworkStock/Index: BLU:TSX BELLUS Health Inc.
Time series to forecast n: 22 Jan 2023 for (n+6 month)
According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy
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 BELLUS Health Inc.
- 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.
- Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.
- For a financial guarantee contract, the entity is required to make payments only in the event of a default by the debtor in accordance with the terms of the instrument that is guaranteed. Accordingly, cash shortfalls are the expected payments to reimburse the holder for a credit loss that it incurs less any amounts that the entity expects to receive from the holder, the debtor or any other party. If the asset is fully guaranteed, the estimation of cash shortfalls for a financial guarantee contract would be consistent with the estimations of cash shortfalls for the asset subject to the guarantee
- The definition of a derivative in this Standard includes contracts that are settled gross by delivery of the underlying item (eg a forward contract to purchase a fixed rate debt instrument). An entity may have a contract to buy or sell a non-financial item that can be settled net in cash or another financial instrument or by exchanging financial instruments (eg a contract to buy or sell a commodity at a fixed price at a future date). Such a contract is within the scope of this Standard unless it was entered into and continues to be held for the purpose of delivery of a non-financial item in accordance with the entity's expected purchase, sale or usage requirements. However, this Standard applies to such contracts for an entity's expected purchase, sale or usage requirements if the entity makes a designation in accordance with paragraph 2.5 (see paragraphs 2.4–2.7).
*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
BELLUS Health Inc. is assigned short-term Ba1 & long-term Ba1 estimated rating. BELLUS Health Inc. prediction model is evaluated with Modular Neural Network (DNN Layer) and Beta1,2,3,4 and it is concluded that the BLU:TSX stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy
BLU:TSX BELLUS Health Inc. Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Baa2 | Baa2 |
Balance Sheet | C | Ba3 |
Leverage Ratios | Baa2 | B3 |
Cash Flow | Baa2 | Baa2 |
Rates of Return and Profitability | B3 | Caa2 |
*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
- Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
- 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
- Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
- V. Borkar. Q-learning for risk-sensitive control. Mathematics of Operations Research, 27:294–311, 2002.
- J. Peters, S. Vijayakumar, and S. Schaal. Natural actor-critic. In Proceedings of the Sixteenth European Conference on Machine Learning, pages 280–291, 2005.
- Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
- Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36
Frequently Asked Questions
Q: What is the prediction methodology for BLU:TSX stock?A: BLU:TSX stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Beta
Q: Is BLU:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Buy BLU:TSX Stock.
Q: Is BELLUS Health Inc. stock a good investment?
A: The consensus rating for BELLUS Health Inc. is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BLU:TSX stock?
A: The consensus rating for BLU:TSX is Buy.
Q: What is the prediction period for BLU:TSX stock?
A: The prediction period for BLU:TSX is (n+6 month)
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