Outlook: Procter & Gamble Company (The) Common Stock assigned short-term Ba3 & long-term B3 forecasted stock rating.
Dominant Strategy : Sell
Time series to forecast n: 12 Dec 2022 for (n+1 year)
Methodology : Active Learning (ML)

## Abstract

Stock prediction is a very hot topic in our life. However, in the early time, because of some reasons and the limitation of the device, only a few people had the access to the study. Thanks to the rapid development of science and technology, in recent years more and more people are devoted to the study of the prediction and it becomes easier and easier for us to make stock prediction by using different ways now, including machine learning, deep learning and so on. (Kompella, S. and Chakravarthy Chilukuri, K.C.C., 2020. Stock market prediction using machine learning methods. International Journal of Computer Engineering and Technology, 10(3), p.2019.) We evaluate Procter & Gamble Company (The) Common Stock prediction models with Active Learning (ML) and Logistic Regression1,2,3,4 and conclude that the PG stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

## Key Points

1. Is now good time to invest?
2. Can we predict stock market using machine learning?
3. What is statistical models in machine learning?

## PG Target Price Prediction Modeling Methodology

We consider Procter & Gamble Company (The) Common Stock Decision Process with Active Learning (ML) where A is the set of discrete actions of PG 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(Logistic Regression)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(Active Learning (ML)) X S(n):→ (n+1 year) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of PG 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?

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

Sample Set: Neural Network
Stock/Index: PG Procter & Gamble Company (The) Common Stock
Time series to forecast n: 12 Dec 2022 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

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%

## Adjusted IFRS* Prediction Methods for Procter & Gamble Company (The) Common Stock

1. When determining whether the recognition of lifetime expected credit losses is required, an entity shall consider reasonable and supportable information that is available without undue cost or effort and that may affect the credit risk on a financial instrument in accordance with paragraph 5.5.17(c). An entity need not undertake an exhaustive search for information when determining whether credit risk has increased significantly since initial recognition.
2. However, the fact that a financial asset is non-recourse does not in itself necessarily preclude the financial asset from meeting the condition in paragraphs 4.1.2(b) and 4.1.2A(b). In such situations, the creditor is required to assess ('look through to') the particular underlying assets or cash flows to determine whether the contractual cash flows of the financial asset being classified are payments of principal and interest on the principal amount outstanding. If the terms of the financial asset give rise to any other cash flows or limit the cash flows in a manner inconsistent with payments representing principal and interest, the financial asset does not meet the condition in paragraphs 4.1.2(b) and 4.1.2A(b). Whether the underlying assets are financial assets or non-financial assets does not in itself affect this assessment.
3. Lifetime expected credit losses are generally expected to be recognised before a financial instrument becomes past due. Typically, credit risk increases significantly before a financial instrument becomes past due or other lagging borrower-specific factors (for example, a modification or restructuring) are observed. Consequently when reasonable and supportable information that is more forward-looking than past due information is available without undue cost or effort, it must be used to assess changes in credit risk.
4. In addition to those hedging relationships specified in paragraph 6.9.1, an entity shall apply the requirements in paragraphs 6.9.11 and 6.9.12 to new hedging relationships in which an alternative benchmark rate is designated as a non-contractually specified risk component (see paragraphs 6.3.7(a) and B6.3.8) when, because of interest rate benchmark reform, that risk component is not separately identifiable at the date it is designated.

*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

Procter & Gamble Company (The) Common Stock assigned short-term Ba3 & long-term B3 forecasted stock rating. We evaluate the prediction models Active Learning (ML) with Logistic Regression1,2,3,4 and conclude that the PG stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

### Financial State Forecast for PG Procter & Gamble Company (The) Common Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3B3
Operational Risk 4432
Market Risk7765
Technical Analysis6749
Fundamental Analysis5731
Risk Unsystematic8534

### Prediction Confidence Score

Trust metric by Neural Network: 86 out of 100 with 766 signals.

## References

1. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Is TPL a Buy?. AC Investment Research Journal, 101(3).
2. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2018a. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21:C1–68
3. Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]
4. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
5. Breiman L. 2001a. Random forests. Mach. Learn. 45:5–32
6. Pennington J, Socher R, Manning CD. 2014. GloVe: global vectors for word representation. In Proceedings of the 2014 Conference on Empirical Methods on Natural Language Processing, pp. 1532–43. New York: Assoc. Comput. Linguist.
7. S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
Frequently Asked QuestionsQ: What is the prediction methodology for PG stock?
A: PG stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Logistic Regression
Q: Is PG stock a buy or sell?
A: The dominant strategy among neural network is to Sell PG Stock.
Q: Is Procter & Gamble Company (The) Common Stock stock a good investment?
A: The consensus rating for Procter & Gamble Company (The) Common Stock is Sell and assigned short-term Ba3 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of PG stock?
A: The consensus rating for PG is Sell.
Q: What is the prediction period for PG stock?
A: The prediction period for PG is (n+1 year)