Modelling A.I. in Economics

ABBV AbbVie Inc. Common Stock (Forecast)

Outlook: AbbVie Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 18 Apr 2023 for (n+3 month)
Methodology : Statistical Inference (ML)

Abstract

AbbVie Inc. Common Stock prediction model is evaluated with Statistical Inference (ML) and Wilcoxon Sign-Rank Test1,2,3,4 and it is concluded that the ABBV stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

Key Points

  1. Reaction Function
  2. Operational Risk
  3. Probability Distribution

ABBV Target Price Prediction Modeling Methodology

We consider AbbVie Inc. Common Stock Decision Process with Statistical Inference (ML) where A is the set of discrete actions of ABBV 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(Wilcoxon Sign-Rank Test)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Statistical Inference (ML)) X S(n):→ (n+3 month) S = s 1 s 2 s 3

n:Time series to forecast

p:Price signals of ABBV 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?

ABBV Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: ABBV AbbVie Inc. Common Stock
Time series to forecast n: 18 Apr 2023 for (n+3 month)

According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

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 AbbVie Inc. Common Stock

  1. At the date of initial application, an entity shall assess whether a financial asset meets the condition in paragraphs 4.1.2(a) or 4.1.2A(a) on the basis of the facts and circumstances that exist at that date. The resulting classification shall be applied retrospectively irrespective of the entity's business model in prior reporting periods.
  2. For example, Entity A, whose functional currency is its local currency, has a firm commitment to pay FC150,000 for advertising expenses in nine months' time and a firm commitment to sell finished goods for FC150,000 in 15 months' time. Entity A enters into a foreign currency derivative that settles in nine months' time under which it receives FC100 and pays CU70. Entity A has no other exposures to FC. Entity A does not manage foreign currency risk on a net basis. Hence, Entity A cannot apply hedge accounting for a hedging relationship between the foreign currency derivative and a net position of FC100 (consisting of FC150,000 of the firm purchase commitment—ie advertising services—and FC149,900 (of the FC150,000) of the firm sale commitment) for a nine-month period.
  3. If there are changes in circumstances that affect hedge effectiveness, an entity may have to change the method for assessing whether a hedging relationship meets the hedge effectiveness requirements in order to ensure that the relevant characteristics of the hedging relationship, including the sources of hedge ineffectiveness, are still captured.
  4. The methods used to determine whether credit risk has increased significantly on a financial instrument since initial recognition should consider the characteristics of the financial instrument (or group of financial instruments) and the default patterns in the past for comparable financial instruments. Despite the requirement in paragraph 5.5.9, for financial instruments for which default patterns are not concentrated at a specific point during the expected life of the financial instrument, changes in the risk of a default occurring over the next 12 months may be a reasonable approximation of the changes in the lifetime risk of a default occurring. In such cases, an entity may use changes in the risk of a default occurring over the next 12 months to determine whether credit risk has increased significantly since initial recognition, unless circumstances indicate that a lifetime assessment is necessary

*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

AbbVie Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. AbbVie Inc. Common Stock prediction model is evaluated with Statistical Inference (ML) and Wilcoxon Sign-Rank Test1,2,3,4 and it is concluded that the ABBV stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Hold

ABBV AbbVie Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB1Caa2
Balance SheetCaa2B1
Leverage RatiosB1C
Cash FlowCaa2B2
Rates of Return and ProfitabilityBaa2B2

*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: 72 out of 100 with 865 signals.

References

  1. Schapire RE, Freund Y. 2012. Boosting: Foundations and Algorithms. Cambridge, MA: MIT Press
  2. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
  3. Künzel S, Sekhon J, Bickel P, Yu B. 2017. Meta-learners for estimating heterogeneous treatment effects using machine learning. arXiv:1706.03461 [math.ST]
  4. Thompson WR. 1933. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25:285–94
  5. Belloni A, Chernozhukov V, Hansen C. 2014. High-dimensional methods and inference on structural and treatment effects. J. Econ. Perspect. 28:29–50
  6. 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
  7. Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
Frequently Asked QuestionsQ: What is the prediction methodology for ABBV stock?
A: ABBV stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Wilcoxon Sign-Rank Test
Q: Is ABBV stock a buy or sell?
A: The dominant strategy among neural network is to Hold ABBV Stock.
Q: Is AbbVie Inc. Common Stock stock a good investment?
A: The consensus rating for AbbVie Inc. Common Stock is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of ABBV stock?
A: The consensus rating for ABBV is Hold.
Q: What is the prediction period for ABBV stock?
A: The prediction period for ABBV is (n+3 month)

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