Outlook: Bausch Health Companies Inc. is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 10 Jan 2023 for (n+3 month)
Methodology : Deductive Inference (ML)

Abstract

Bausch Health Companies Inc. prediction model is evaluated with Deductive Inference (ML) and Lasso Regression1,2,3,4 and it is concluded that the BHC:TSX stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

Key Points

1. Prediction Modeling
2. What statistical methods are used to analyze data?
3. Game Theory

BHC:TSX Target Price Prediction Modeling Methodology

We consider Bausch Health Companies Inc. Decision Process with Deductive Inference (ML) where A is the set of discrete actions of BHC: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(Lasso Regression)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Deductive Inference (ML)) X S(n):→ (n+3 month) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of BHC: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?

BHC:TSX Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: BHC:TSX Bausch Health Companies Inc.
Time series to forecast n: 10 Jan 2023 for (n+3 month)

According to price forecasts for (n+3 month) 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 Bausch Health Companies Inc.

1. IFRS 15, issued in May 2014, amended paragraphs 3.1.1, 4.2.1, 5.1.1, 5.2.1, 5.7.6, B3.2.13, B5.7.1, C5 and C42 and deleted paragraph C16 and its related heading. Paragraphs 5.1.3 and 5.7.1A, and a definition to Appendix A, were added. An entity shall apply those amendments when it applies IFRS 15.
2. 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.
3. In addition to those hedging relationships specified in paragraph 6.9.1, an entity shall apply the requirements in paragraphs 6.9.11 and 6.9.12 to new hedging relationships in which an alternative benchmark rate is designated as a non-contractually specified risk component (see paragraphs 6.3.7(a) and B6.3.8) when, because of interest rate benchmark reform, that risk component is not separately identifiable at the date it is designated.
4. An entity applies IAS 21 to financial assets and financial liabilities that are monetary items in accordance with IAS 21 and denominated in a foreign currency. IAS 21 requires any foreign exchange gains and losses on monetary assets and monetary liabilities to be recognised in profit or loss. An exception is a monetary item that is designated as a hedging instrument in a cash flow hedge (see paragraph 6.5.11), a hedge of a net investment (see paragraph 6.5.13) or a fair value hedge of an equity instrument for which an entity has elected to present changes in fair value in other comprehensive income in accordance with paragraph 5.7.5 (see paragraph 6.5.8).

*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.

Conclusions

Bausch Health Companies Inc. is assigned short-term Ba1 & long-term Ba1 estimated rating. Bausch Health Companies Inc. prediction model is evaluated with Deductive Inference (ML) and Lasso Regression1,2,3,4 and it is concluded that the BHC:TSX stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

BHC:TSX Bausch Health Companies Inc. Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2B3
Balance SheetBaa2Caa2
Leverage RatiosB1Baa2
Cash FlowCaa2C
Rates of Return and ProfitabilityBaa2C

*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: 83 out of 100 with 707 signals.

References

1. V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.
2. Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
3. K. Tuyls and G. Weiss. Multiagent learning: Basics, challenges, and prospects. AI Magazine, 33(3): 41–52, 2012
4. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., How do you know when a stock will go up or down?(STJ Stock Forecast). AC Investment Research Journal, 101(3).
5. Kallus N. 2017. Balanced policy evaluation and learning. arXiv:1705.07384 [stat.ML]
6. Imbens GW, Rubin DB. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge, UK: Cambridge Univ. Press
7. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
Frequently Asked QuestionsQ: What is the prediction methodology for BHC:TSX stock?
A: BHC:TSX stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Lasso Regression
Q: Is BHC:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Sell BHC:TSX Stock.
Q: Is Bausch Health Companies Inc. stock a good investment?
A: The consensus rating for Bausch Health Companies Inc. is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BHC:TSX stock?
A: The consensus rating for BHC:TSX is Sell.
Q: What is the prediction period for BHC:TSX stock?
A: The prediction period for BHC:TSX is (n+3 month)