Modelling A.I. in Economics

Buy or Sell: WH Stock

Investors raise profit from stock market by maximising gains and minimising loses. The profit is difficult to raise because of the volatile nature of stock market prices. Predictive modelling allows investors to make informed decisions. We evaluate Wyndham Hotels & Resorts prediction models with Reinforcement Machine Learning (ML) and Spearman Correlation1,2,3,4 and conclude that the WH stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold WH stock.


Keywords: WH, Wyndham Hotels & Resorts, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. How do you know when a stock will go up or down?
  2. Probability Distribution
  3. What is the use of Markov decision process?

WH Target Price Prediction Modeling Methodology

Prediction of stock market is a long-time attractive topic to researchers from different fields. In particular, numerous studies have been conducted to predict the movement of stock market using machine learning algorithms such as support vector machine (SVM) and reinforcement learning. In this project, we propose a new prediction algorithm that exploits the temporal correlation among global stock markets and various financial products to predict the next-day stock trend. We consider Wyndham Hotels & Resorts Stock Decision Process with Spearman Correlation where A is the set of discrete actions of WH 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(Spearman Correlation)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(Reinforcement Machine Learning (ML)) X S(n):→ (n+16 weeks) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of WH stock

j:Nash equilibria

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?

WH Stock Forecast (Buy or Sell) for (n+16 weeks)


Sample Set: Neural Network
Stock/Index: WH Wyndham Hotels & Resorts
Time series to forecast n: 10 Nov 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold WH stock.

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 (Yellow to Green): *Technical Analysis%

Adjusted IFRS* Prediction Methods for Wyndham Hotels & Resorts

  1. An entity's risk management is the main source of information to perform the assessment of whether a hedging relationship meets the hedge effectiveness requirements. This means that the management information (or analysis) used for decision-making purposes can be used as a basis for assessing whether a hedging relationship meets the hedge effectiveness requirements.
  2. 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
  3. An entity that first applies these amendments after it first applies this Standard shall apply paragraphs 7.2.32–7.2.34. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).
  4. 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.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Wyndham Hotels & Resorts assigned short-term B1 & long-term B1 forecasted stock rating. We evaluate the prediction models Reinforcement Machine Learning (ML) with Spearman Correlation1,2,3,4 and conclude that the WH stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold WH stock.

Financial State Forecast for WH Wyndham Hotels & Resorts Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1B1
Operational Risk 3942
Market Risk7278
Technical Analysis8664
Fundamental Analysis7854
Risk Unsystematic3551

Prediction Confidence Score

Trust metric by Neural Network: 74 out of 100 with 624 signals.

References

  1. Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
  2. Harris ZS. 1954. Distributional structure. Word 10:146–62
  3. Friedman JH. 2002. Stochastic gradient boosting. Comput. Stat. Data Anal. 38:367–78
  4. Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press
  5. Li L, Chu W, Langford J, Moon T, Wang X. 2012. An unbiased offline evaluation of contextual bandit algo- rithms with generalized linear models. In Proceedings of 4th ACM International Conference on Web Search and Data Mining, pp. 297–306. New York: ACM
  6. Bottomley, P. R. Fildes (1998), "The role of prices in models of innovation diffusion," Journal of Forecasting, 17, 539–555.
  7. Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]
Frequently Asked QuestionsQ: What is the prediction methodology for WH stock?
A: WH stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Spearman Correlation
Q: Is WH stock a buy or sell?
A: The dominant strategy among neural network is to Hold WH Stock.
Q: Is Wyndham Hotels & Resorts stock a good investment?
A: The consensus rating for Wyndham Hotels & Resorts is Hold and assigned short-term B1 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of WH stock?
A: The consensus rating for WH is Hold.
Q: What is the prediction period for WH stock?
A: The prediction period for WH is (n+16 weeks)



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