Dominant Strategy : Hold
Time series to forecast n: 06 Jun 2023 for (n+1 year)
Methodology : Reinforcement Machine Learning (ML)
Abstract
UnitedHealth Group Incorporated Common Stock (DE) prediction model is evaluated with Reinforcement Machine Learning (ML) and ElasticNet Regression1,2,3,4 and it is concluded that the UNH stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: HoldKey Points
- Decision Making
- Reaction Function
- Reaction Function
UNH Target Price Prediction Modeling Methodology
We consider UnitedHealth Group Incorporated Common Stock (DE) Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of UNH 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(ElasticNet Regression)5,6,7= X R(Reinforcement Machine Learning (ML)) X S(n):→ (n+1 year)
n:Time series to forecast
p:Price signals of UNH 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?
UNH Stock Forecast (Buy or Sell) for (n+1 year)
Sample Set: Neural NetworkStock/Index: UNH UnitedHealth Group Incorporated Common Stock (DE)
Time series to forecast n: 06 Jun 2023 for (n+1 year)
According to price forecasts for (n+1 year) 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 UnitedHealth Group Incorporated Common Stock (DE)
- An entity shall apply Prepayment Features with Negative Compensation (Amendments to IFRS 9) retrospectively in accordance with IAS 8, except as specified in paragraphs 7.2.30–7.2.34
- In cases such as those described in the preceding paragraph, to designate, at initial recognition, the financial assets and financial liabilities not otherwise so measured as at fair value through profit or loss may eliminate or significantly reduce the measurement or recognition inconsistency and produce more relevant information. For practical purposes, the entity need not enter into all of the assets and liabilities giving rise to the measurement or recognition inconsistency at exactly the same time. A reasonable delay is permitted provided that each transaction is designated as at fair value through profit or loss at its initial recognition and, at that time, any remaining transactions are expected to occur.
- In cases such as those described in the preceding paragraph, to designate, at initial recognition, the financial assets and financial liabilities not otherwise so measured as at fair value through profit or loss may eliminate or significantly reduce the measurement or recognition inconsistency and produce more relevant information. For practical purposes, the entity need not enter into all of the assets and liabilities giving rise to the measurement or recognition inconsistency at exactly the same time. A reasonable delay is permitted provided that each transaction is designated as at fair value through profit or loss at its initial recognition and, at that time, any remaining transactions are expected to occur.
- 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
UnitedHealth Group Incorporated Common Stock (DE) is assigned short-term Ba1 & long-term Ba1 estimated rating. UnitedHealth Group Incorporated Common Stock (DE) prediction model is evaluated with Reinforcement Machine Learning (ML) and ElasticNet Regression1,2,3,4 and it is concluded that the UNH stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold
UNH UnitedHealth Group Incorporated Common Stock (DE) Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | C | Ba3 |
Balance Sheet | Caa2 | C |
Leverage Ratios | Baa2 | Caa2 |
Cash Flow | B3 | B1 |
Rates of Return and Profitability | Ba3 | 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

References
- Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
- Holland PW. 1986. Statistics and causal inference. J. Am. Stat. Assoc. 81:945–60
- E. Collins. Using Markov decision processes to optimize a nonlinear functional of the final distribution, with manufacturing applications. In Stochastic Modelling in Innovative Manufacturing, pages 30–45. Springer, 1997
- G. J. Laurent, L. Matignon, and N. L. Fort-Piat. The world of independent learners is not Markovian. Int. J. Know.-Based Intell. Eng. Syst., 15(1):55–64, 2011
- V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016
- Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
- Bessler, D. A. T. Covey (1991), "Cointegration: Some results on U.S. cattle prices," Journal of Futures Markets, 11, 461–474.
Frequently Asked Questions
Q: What is the prediction methodology for UNH stock?A: UNH stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and ElasticNet Regression
Q: Is UNH stock a buy or sell?
A: The dominant strategy among neural network is to Hold UNH Stock.
Q: Is UnitedHealth Group Incorporated Common Stock (DE) stock a good investment?
A: The consensus rating for UnitedHealth Group Incorporated Common Stock (DE) is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of UNH stock?
A: The consensus rating for UNH is Hold.
Q: What is the prediction period for UNH stock?
A: The prediction period for UNH is (n+1 year)