Cementos Pacasmayo S.A.A. American Depositary Shares (Each representing five Common Shares) is assigned short-term B1 & long-term Ba1 estimated  rating.

Jorgenson, Dale W.; Weitzman, Martin L.; ZXhang, Yoshua X; Haxo, Yann M; Mat , Ying X

Outlook: Cementos Pacasmayo S.A.A. American Depositary Shares (Each representing five Common Shares) is assigned short-term B1 & long-term Ba1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Buy
Time series to forecast n: for Weeks²
Methodology : Multi-Task Learning (ML)
Hypothesis Testing : Paired T-Test
Surveillance : Major exchange and OTC

¹The accuracy of the model is being monitored on a regular basis.(15-minute period)

²Time series is updated based on short-term trends.

Summary

Cementos Pacasmayo S.A.A. American Depositary Shares (Each representing five Common Shares) prediction model is evaluated with Multi-Task Learning (ML) and Paired T-Test^1,2,3,4 and it is concluded that the CPAC stock is predictable in the short/long term. Multi-task learning (MTL) is a machine learning (ML) method in which multiple related tasks are learned simultaneously. This can be done by sharing features and weights between the tasks. MTL has been shown to improve the performance of each task, compared to learning each task independently.⁵ According to price forecasts for 1 Year period, the dominant strategy among neural network is: Buy

Key Points

Multi-Task Learning (ML) for CPAC stock price prediction process.
Paired T-Test
Decision Making
Nash Equilibria
What is Markov decision process in reinforcement learning?

CPAC Stock Price Forecast

We consider Cementos Pacasmayo S.A.A. American Depositary Shares (Each representing five Common Shares) Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of CPAC 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

Sample Set: Neural Network
Stock/Index: CPAC Cementos Pacasmayo S.A.A. American Depositary Shares (Each representing five Common Shares)
Time series to forecast: 1 Year

According to price forecasts, the dominant strategy among neural network is: Buy

F(Paired T-Test)^6,7=

\begin{matrix} p_{a 1} & p_{a 2} & \dots & p_{1 n} \\ ⋮ \\ p_{j 1} & p_{j 2} & \dots & p_{j n} \\ ⋮ \\ p_{k 1} & p_{k 2} & \dots & p_{k n} \\ ⋮ \\ p_{n 1} & p_{n 2} & \dots & p_{n n} \end{matrix}

X R(Multi-Task Learning (ML)) X S(n):→ 1 Year

\vec{S} = (s_{1}, s_{2}, s_{3})

n:Time series to forecast

p:Price signals of CPAC stock

j:Nash equilibria (Neural Network)

k:Dominated move of CPAC stock holders

a:Best response for CPAC target price

Multi-task learning (MTL) is a machine learning (ML) method in which multiple related tasks are learned simultaneously. This can be done by sharing features and weights between the tasks. MTL has been shown to improve the performance of each task, compared to learning each task independently.⁵ A paired t-test is a statistical test that compares the means of two paired samples. In a paired t-test, each data point in one sample is paired with a data point in the other sample. The pairs are typically related in some way, such as before and after measurements, or measurements from the same subject under different conditions. The paired t-test is a parametric test, which means that it assumes that the data is normally distributed. The paired t-test is also a dependent samples test, which means that the data points in each pair are correlated.^6,7

For further technical information as per how our model work we invite you to visit the article below:

How do Predictive A.I. algorithms actually work?

CPAC Stock Forecast (Buy or Sell) Strategic Interaction Table

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Multi-Task Learning (ML) based CPAC Stock Prediction Model

When assessing a modified time value of money element, an entity must consider factors that could affect future contractual cash flows. For example, if an entity is assessing a bond with a five-year term and the variable interest rate is reset every six months to a five-year rate, the entity cannot conclude that the contractual cash flows are solely payments of principal and interest on the principal amount outstanding simply because the interest rate curve at the time of the assessment is such that the difference between a five-year interest rate and a six-month interest rate is not significant. Instead, the entity must also consider whether the relationship between the five-year interest rate and the six-month interest rate could change over the life of the instrument such that the contractual (undiscounted) cash flows over the life of the instrument could be significantly different from the (undiscounted) benchmark cash flows. However, an entity must consider only reasonably possible scenarios instead of every possible scenario. If an entity concludes that the contractual (undiscounted) cash flows could be significantly different from the (undiscounted) benchmark cash flows, the financial asset does not meet the condition in paragraphs 4.1.2(b) and 4.1.2A(b) and therefore cannot be measured at amortised cost or fair value through other comprehensive income.
When using historical credit loss experience in estimating expected credit losses, it is important that information about historical credit loss rates is applied to groups that are defined in a manner that is consistent with the groups for which the historical credit loss rates were observed. Consequently, the method used shall enable each group of financial assets to be associated with information about past credit loss experience in groups of financial assets with similar risk characteristics and with relevant observable data that reflects current conditions.
If such a mismatch would be created or enlarged, the entity is required to present all changes in fair value (including the effects of changes in the credit risk of the liability) in profit or loss. If such a mismatch would not be created or enlarged, the entity is required to present the effects of changes in the liability's credit risk in other comprehensive income.
When measuring a loss allowance for a lease receivable, the cash flows used for determining the expected credit losses should be consistent with the cash flows used in measuring the lease receivable in accordance with IFRS 16 Leases.

*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.

CPAC Cementos Pacasmayo S.A.A. American Depositary Shares (Each representing five Common Shares) Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B1	Ba1
Income Statement	Baa2	Baa2
Balance Sheet	Ba3	Baa2
Leverage Ratios	Caa2	Baa2
Cash Flow	B3	C
Rates of Return and Profitability	B3	Ba2

*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?

References

Andrews, D. W. K. W. Ploberger (1994), "Optimal tests when a nuisance parameter is present only under the alternative," Econometrica, 62, 1383–1414.
Abadie A, Cattaneo MD. 2018. Econometric methods for program evaluation. Annu. Rev. Econ. 10:465–503
Farrell MH, Liang T, Misra S. 2018. Deep neural networks for estimation and inference: application to causal effects and other semiparametric estimands. arXiv:1809.09953 [econ.EM]
Breiman L. 1993. Better subset selection using the non-negative garotte. Tech. Rep., Univ. Calif., Berkeley
P. Milgrom and I. Segal. Envelope theorems for arbitrary choice sets. Econometrica, 70(2):583–601, 2002
Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276
Thompson WR. 1933. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25:285–94

Frequently Asked Questions

Q: Is CPAC stock expected to rise?
A: CPAC stock prediction model is evaluated with Multi-Task Learning (ML) and Paired T-Test and it is concluded that dominant strategy for CPAC stock is Buy
Q: Is CPAC stock a buy or sell?
A: The dominant strategy among neural network is to Buy CPAC Stock.
Q: Is Cementos Pacasmayo S.A.A. American Depositary Shares (Each representing five Common Shares) stock a good investment?
A: The consensus rating for Cementos Pacasmayo S.A.A. American Depositary Shares (Each representing five Common Shares) is Buy and is assigned short-term B1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of CPAC stock?
A: The consensus rating for CPAC is Buy.
Q: What is the forecast for CPAC stock?
A: CPAC target price forecast: Buy

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Cementos Pacasmayo S.A.A. American Depositary Shares (Each representing five Common Shares) is assigned short-term B1 & long-term Ba1 estimated rating.