Wyndham Hotels & Resorts Research Report

## Summary

Predicting stock index with traditional time series analysis has proven to be difficult an Artificial Neural network may be suitable for the task. A Neural Network has the ability to extract useful information from large set of data. This paper presents a review of literature application of Artificial Neural Network for stock market predictions and from this literature found that Artificial Neural Network is very useful for predicting world stock markets. We evaluate Wyndham Hotels & Resorts prediction models with Reinforcement Machine Learning (ML) and Chi-Square1,2,3,4 and conclude that the WH stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Buy WH stock.

## Key Points

1. What is Markov decision process in reinforcement learning?
2. What are buy sell or hold recommendations?

## WH Target Price Prediction Modeling Methodology

We consider Wyndham Hotels & Resorts Stock Decision Process with Reinforcement Machine Learning (ML) 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 Î³ ∈ [0, 1] is a move factor for expectation.1,2,3,4

F(Chi-Square)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(Reinforcement Machine Learning (ML)) X S(n):→ (n+1 year) $∑ i = 1 n s i$

n:Time series to forecast

p:Price signals of WH 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?

## WH Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: WH Wyndham Hotels & Resorts
Time series to forecast n: 18 Nov 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Buy 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. Interest Rate Benchmark Reform, which amended IFRS 9, IAS 39 and IFRS 7, issued in September 2019, added Section 6.8 and amended paragraph 7.2.26. An entity shall apply these amendments for annual periods beginning on or after 1 January 2020. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.
2. The underlying pool must contain one or more instruments that have contractual cash flows that are solely payments of principal and interest on the principal amount outstanding
3. For the purposes of applying the requirement in paragraph 5.7.7(a), credit risk is different from asset-specific performance risk. Asset-specific performance risk is not related to the risk that an entity will fail to discharge a particular obligation but instead it is related to the risk that a single asset or a group of assets will perform poorly (or not at all).
4. It would not be acceptable to designate only some of the financial assets and financial liabilities giving rise to the inconsistency as at fair value through profit or loss if to do so would not eliminate or significantly reduce the inconsistency and would therefore not result in more relevant information. However, it would be acceptable to designate only some of a number of similar financial assets or similar financial liabilities if doing so achieves a significant reduction (and possibly a greater reduction than other allowable designations) in the inconsistency. For example, assume an entity has a number of similar financial liabilities that sum to CU100 and a number of similar financial assets that sum to CU50 but are measured on a different basis. The entity may significantly reduce the measurement inconsistency by designating at initial recognition all of the assets but only some of the liabilities (for example, individual liabilities with a combined total of CU45) as at fair value through profit or loss. However, because designation as at fair value through profit or loss can be applied only to the whole of a financial instrument, the entity in this example must designate one or more liabilities in their entirety. It could not designate either a component of a liability (eg changes in value attributable to only one risk, such as changes in a benchmark interest rate) or a proportion (ie percentage) of a liability.

*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 B3 & long-term B1 forecasted stock rating. We evaluate the prediction models Reinforcement Machine Learning (ML) with Chi-Square1,2,3,4 and conclude that the WH stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Buy WH stock.

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

Rating Short-Term Long-Term Senior
Outlook*B3B1
Operational Risk 7237
Market Risk3139
Technical Analysis5875
Fundamental Analysis4063
Risk Unsystematic5683

### Prediction Confidence Score

Trust metric by Neural Network: 77 out of 100 with 719 signals.

## References

1. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
2. Swaminathan A, Joachims T. 2015. Batch learning from logged bandit feedback through counterfactual risk minimization. J. Mach. Learn. Res. 16:1731–55
3. Akgiray, V. (1989), "Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts," Journal of Business, 62, 55–80.
4. J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
5. Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
6. Zeileis A, Hothorn T, Hornik K. 2008. Model-based recursive partitioning. J. Comput. Graph. Stat. 17:492–514 Zhou Z, Athey S, Wager S. 2018. Offline multi-action policy learning: generalization and optimization. arXiv:1810.04778 [stat.ML]
7. M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016
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 Chi-Square
Q: Is WH stock a buy or sell?
A: The dominant strategy among neural network is to Buy WH Stock.
Q: Is Wyndham Hotels & Resorts stock a good investment?
A: The consensus rating for Wyndham Hotels & Resorts is Buy and assigned short-term B3 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of WH stock?
A: The consensus rating for WH is Buy.
Q: What is the prediction period for WH stock?
A: The prediction period for WH is (n+1 year)