WPP plc American Depositary Shares Research Report

## Summary

The research reported in the paper focuses on the stock market prediction problem, the main aim being the development of a methodology to forecast the stock closing price. The methodology is based on some novel variable selection methods and an analysis of neural network and support vector machines based prediction models. Also, a hybrid approach which combines the use of the variables derived from technical and fundamental analysis of stock market indicators in order to improve prediction results of the proposed approaches is reported in this paper. We evaluate WPP plc American Depositary Shares prediction models with Modular Neural Network (DNN Layer) and Independent T-Test1,2,3,4 and conclude that the WPP 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 Buy WPP stock.

## Key Points

1. Is Target price a good indicator?
3. Can statistics predict the future?

## WPP Target Price Prediction Modeling Methodology

We consider WPP plc American Depositary Shares Stock Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of WPP 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(Independent T-Test)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(Modular Neural Network (DNN Layer)) X S(n):→ (n+16 weeks) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of WPP 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?

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

Sample Set: Neural Network
Stock/Index: WPP WPP plc American Depositary Shares
Time series to forecast n: 22 Nov 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy WPP 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 WPP plc American Depositary Shares

1. An entity is not required to restate prior periods to reflect the application of these amendments. The entity may restate prior periods if, and only if, it is possible without the use of hindsight. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.
2. A contractual cash flow characteristic does not affect the classification of the financial asset if it could have only a de minimis effect on the contractual cash flows of the financial asset. To make this determination, an entity must consider the possible effect of the contractual cash flow characteristic in each reporting period and cumulatively over the life of the financial instrument. In addition, if a contractual cash flow characteristic could have an effect on the contractual cash flows that is more than de minimis (either in a single reporting period or cumulatively) but that cash flow characteristic is not genuine, it does not affect the classification of a financial asset. A cash flow characteristic is not genuine if it affects the instrument's contractual cash flows only on the occurrence of an event that is extremely rare, highly abnormal and very unlikely to occur.
3. Hedge effectiveness is the extent to which changes in the fair value or the cash flows of the hedging instrument offset changes in the fair value or the cash flows of the hedged item (for example, when the hedged item is a risk component, the relevant change in fair value or cash flows of an item is the one that is attributable to the hedged risk). Hedge ineffectiveness is the extent to which the changes in the fair value or the cash flows of the hedging instrument are greater or less than those on the hedged item.
4. An entity's estimate of expected credit losses on loan commitments shall be consistent with its expectations of drawdowns on that loan commitment, ie it shall consider the expected portion of the loan commitment that will be drawn down within 12 months of the reporting date when estimating 12-month expected credit losses, and the expected portion of the loan commitment that will be drawn down over the expected life of the loan commitment when estimating lifetime expected credit losses.

*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

WPP plc American Depositary Shares assigned short-term B3 & long-term Ba2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (DNN Layer) with Independent T-Test1,2,3,4 and conclude that the WPP 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 Buy WPP stock.

### Financial State Forecast for WPP WPP plc American Depositary Shares Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B3Ba2
Operational Risk 4087
Market Risk4353
Technical Analysis6239
Fundamental Analysis6289
Risk Unsystematic4271

### Prediction Confidence Score

Trust metric by Neural Network: 93 out of 100 with 755 signals.

## References

1. C. Szepesvári. Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2010
2. L. Busoniu, R. Babuska, and B. D. Schutter. A comprehensive survey of multiagent reinforcement learning. IEEE Transactions of Systems, Man, and Cybernetics Part C: Applications and Reviews, 38(2), 2008.
3. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
4. Mullainathan S, Spiess J. 2017. Machine learning: an applied econometric approach. J. Econ. Perspect. 31:87–106
5. Burgess, D. F. (1975), "Duality theory and pitfalls in the specification of technologies," Journal of Econometrics, 3, 105–121.
6. L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
7. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
Frequently Asked QuestionsQ: What is the prediction methodology for WPP stock?
A: WPP stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Independent T-Test
Q: Is WPP stock a buy or sell?
A: The dominant strategy among neural network is to Buy WPP Stock.
Q: Is WPP plc American Depositary Shares stock a good investment?
A: The consensus rating for WPP plc American Depositary Shares is Buy and assigned short-term B3 & long-term Ba2 forecasted stock rating.
Q: What is the consensus rating of WPP stock?
A: The consensus rating for WPP is Buy.
Q: What is the prediction period for WPP stock?
A: The prediction period for WPP is (n+16 weeks)