PAAS Stock: Soars on Positive Economic Data

Outlook: Pan American Silver Corp. Common Stock is assigned short-term B2 & long-term B3 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 : Independent 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

Pan American Silver Corp. Common Stock prediction model is evaluated with Multi-Task Learning (ML) and Independent T-Test^1,2,3,4 and it is concluded that the PAAS 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. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Buy

Key Points

1. Understanding Buy, Sell, and Hold Ratings
2. Fundemental Analysis with Algorithmic Trading
3. What is prediction in deep learning?

PAAS Target Price Prediction Modeling Methodology

We consider Pan American Silver Corp. Common Stock Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of PAAS 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= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Multi-Task Learning (ML)) X S(n):→ 6 Month $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of PAAS stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Multi-Task Learning (ML)

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.

Independent T-Test

An independent t-test is a statistical test that compares the means of two independent samples. In an independent t-test, the data points in each sample are not related to each other. The independent t-test is a parametric test, which means that it assumes that the data is normally distributed. The independent t-test is also a two-sample test, which means that it compares the means of two independent samples.

 

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?

PAAS Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: PAAS Pan American Silver Corp. Common Stock
Time series to forecast: 6 Month

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

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 PAAS Stock Prediction Model

1. There is a rebuttable presumption that unless inflation risk is contractually specified, it is not separately identifiable and reliably measurable and hence cannot be designated as a risk component of a financial instrument. However, in limited cases, it is possible to identify a risk component for inflation risk that is separately identifiable and reliably measurable because of the particular circumstances of the inflation environment and the relevant debt market
2. 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.
3. 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.
4. An alternative benchmark rate designated as a non-contractually specified risk component that is not separately identifiable (see paragraphs 6.3.7(a) and B6.3.8) at the date it is designated shall be deemed to have met that requirement at that date, if, and only if, the entity reasonably expects the alternative benchmark rate will be separately identifiable within 24 months. The 24-month period applies to each alternative benchmark rate separately and starts from the date the entity designates the alternative benchmark rate as a non-contractually specified risk component for the first time (ie the 24- month period applies on a rate-by-rate basis).

*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.

PAAS Pan American Silver Corp. Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B2	B3
Income Statement	B3	Caa2
Balance Sheet	C	C
Leverage Ratios	Baa2	C
Cash Flow	B3	B3
Rates of Return and Profitability	B2	Caa2

*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?

Conclusions

Pan American Silver Corp. Common Stock is assigned short-term B2 & long-term B3 estimated rating. Pan American Silver Corp. Common Stock prediction model is evaluated with Multi-Task Learning (ML) and Independent T-Test^1,2,3,4 and it is concluded that the PAAS stock is predictable in the short/long term. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Buy

Prediction Confidence Score

Trust metric by Neural Network: 82 out of 100 with 875 signals.

References

1. Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
2. M. Benaim, J. Hofbauer, and S. Sorin. Stochastic approximations and differential inclusions, Part II: Appli- cations. Mathematics of Operations Research, 31(4):673–695, 2006
3. Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
4. Burgess, D. F. (1975), "Duality theory and pitfalls in the specification of technologies," Journal of Econometrics, 3, 105–121.
5. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. MRNA: The Next Big Thing in mRNA Vaccines. AC Investment Research Journal, 220(44).
6. J. Spall. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control, 37(3):332–341, 1992.
7. Belloni A, Chernozhukov V, Hansen C. 2014. High-dimensional methods and inference on structural and treatment effects. J. Econ. Perspect. 28:29–50

Frequently Asked Questions

Q: What is the prediction methodology for PAAS stock?
A: PAAS stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Independent T-Test
Q: Is PAAS stock a buy or sell?
A: The dominant strategy among neural network is to Buy PAAS Stock.
Q: Is Pan American Silver Corp. Common Stock stock a good investment?
A: The consensus rating for Pan American Silver Corp. Common Stock is Buy and is assigned short-term B2 & long-term B3 estimated rating.
Q: What is the consensus rating of PAAS stock?
A: The consensus rating for PAAS is Buy.
Q: What is the prediction period for PAAS stock?
A: The prediction period for PAAS is 6 Month

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