Outlook: RPM AUTOMOTIVE GROUP LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.
Time series to forecast n: 02 Apr 2023 for (n+1 year)
Methodology : Reinforcement Machine Learning (ML)

## Abstract

RPM AUTOMOTIVE GROUP LIMITED prediction model is evaluated with Reinforcement Machine Learning (ML) and ElasticNet Regression1,2,3,4 and it is concluded that the RPM stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy

## Key Points

1. What are buy sell or hold recommendations?
2. How do you pick a stock?
3. Stock Rating

## RPM Target Price Prediction Modeling Methodology

We consider RPM AUTOMOTIVE GROUP LIMITED Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of RPM 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= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Reinforcement Machine Learning (ML)) X S(n):→ (n+1 year) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of RPM 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?

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

Sample Set: Neural Network
Stock/Index: RPM RPM AUTOMOTIVE GROUP LIMITED
Time series to forecast n: 02 Apr 2023 for (n+1 year)

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

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 RPM AUTOMOTIVE GROUP LIMITED

1. Paragraph 5.5.4 requires that lifetime expected credit losses are recognised on all financial instruments for which there has been significant increases in credit risk since initial recognition. In order to meet this objective, if an entity is not able to group financial instruments for which the credit risk is considered to have increased significantly since initial recognition based on shared credit risk characteristics, the entity should recognise lifetime expected credit losses on a portion of the financial assets for which credit risk is deemed to have increased significantly. The aggregation of financial instruments to assess whether there are changes in credit risk on a collective basis may change over time as new information becomes available on groups of, or individual, financial instruments.
2. 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.
3. In some cases, the qualitative and non-statistical quantitative information available may be sufficient to determine that a financial instrument has met the criterion for the recognition of a loss allowance at an amount equal to lifetime expected credit losses. That is, the information does not need to flow through a statistical model or credit ratings process in order to determine whether there has been a significant increase in the credit risk of the financial instrument. In other cases, an entity may need to consider other information, including information from its statistical models or credit ratings processes.
4. The purpose of estimating expected credit losses is neither to estimate a worstcase scenario nor to estimate the best-case scenario. Instead, an estimate of expected credit losses shall always reflect the possibility that a credit loss occurs and the possibility that no credit loss occurs even if the most likely outcome is no credit loss.

*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

RPM AUTOMOTIVE GROUP LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. RPM AUTOMOTIVE GROUP LIMITED prediction model is evaluated with Reinforcement Machine Learning (ML) and ElasticNet Regression1,2,3,4 and it is concluded that the RPM stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy

### RPM RPM AUTOMOTIVE GROUP LIMITED Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB3Baa2
Balance SheetBaa2C
Leverage RatiosBaa2Caa2
Cash FlowBa3Baa2
Rates of Return and ProfitabilityCaa2Caa2

*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

Trust metric by Neural Network: 89 out of 100 with 521 signals.

## References

1. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., When to Sell and When to Hold FTNT Stock. AC Investment Research Journal, 101(3).
2. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
3. Artis, M. J. W. Zhang (1990), "BVAR forecasts for the G-7," International Journal of Forecasting, 6, 349–362.
4. Athey S, Imbens GW. 2017a. The econometrics of randomized experiments. In Handbook of Economic Field Experiments, Vol. 1, ed. E Duflo, A Banerjee, pp. 73–140. Amsterdam: Elsevier
5. Barrett, C. B. (1997), "Heteroscedastic price forecasting for food security management in developing countries," Oxford Development Studies, 25, 225–236.
6. Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276
7. M. Petrik and D. Subramanian. An approximate solution method for large risk-averse Markov decision processes. In Proceedings of the 28th International Conference on Uncertainty in Artificial Intelligence, 2012.
Frequently Asked QuestionsQ: What is the prediction methodology for RPM stock?
A: RPM stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and ElasticNet Regression
Q: Is RPM stock a buy or sell?
A: The dominant strategy among neural network is to Buy RPM Stock.
Q: Is RPM AUTOMOTIVE GROUP LIMITED stock a good investment?
A: The consensus rating for RPM AUTOMOTIVE GROUP LIMITED is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of RPM stock?
A: The consensus rating for RPM is Buy.
Q: What is the prediction period for RPM stock?
A: The prediction period for RPM is (n+1 year)