AG Stock: The Wild Ride Continues

Outlook: First Majestic Silver Corp. Ordinary Shares (Canada) is assigned short-term Baa2 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised :
Dominant Strategy : Speculative Trend
Time series to forecast n: for 6 Month
Methodology : Deductive Inference (ML)
Hypothesis Testing : Multiple Regression
Surveillance : Major exchange and OTC

Summary

First Majestic Silver Corp. Ordinary Shares (Canada) prediction model is evaluated with Deductive Inference (ML) and Multiple Regression^1,2,3,4 and it is concluded that the AG stock is predictable in the short/long term. Deductive inference is a type of reasoning in which a conclusion is drawn based on a set of premises that are assumed to be true. In machine learning (ML), deductive inference can be used to create models that can make predictions about new data based on a set of known rules. Deductive inference is a supervised learning algorithm, which means that it requires labeled data to train. The labeled data is used to train the model to make predictions about new data. There are many different types of deductive inference algorithms, including decision trees, rule-based systems, and expert systems. Each type of algorithm has its own strengths and weaknesses. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Speculative Trend

Key Points

1. Probability Distribution
2. Can we predict stock market using machine learning?
3. How do predictive algorithms actually work?

AG Target Price Prediction Modeling Methodology

We consider First Majestic Silver Corp. Ordinary Shares (Canada) Decision Process with Deductive Inference (ML) where A is the set of discrete actions of AG 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(Multiple Regression)^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(Deductive Inference (ML)) X S(n):→ 6 Month $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of AG stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Deductive Inference (ML)

Deductive inference is a type of reasoning in which a conclusion is drawn based on a set of premises that are assumed to be true. In machine learning (ML), deductive inference can be used to create models that can make predictions about new data based on a set of known rules. Deductive inference is a supervised learning algorithm, which means that it requires labeled data to train. The labeled data is used to train the model to make predictions about new data. There are many different types of deductive inference algorithms, including decision trees, rule-based systems, and expert systems. Each type of algorithm has its own strengths and weaknesses.

Multiple Regression

Multiple regression is a statistical method that analyzes the relationship between a dependent variable and multiple independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Multiple regression is a more complex statistical method than simple linear regression, which only analyzes the relationship between a dependent variable and one independent variable. Multiple regression can be used to analyze more complex relationships between variables, and it can also be used to control for confounding variables. A confounding variable is a variable that is correlated with both the dependent variable and one or more of the independent variables. Confounding variables can distort the relationship between the dependent variable and the independent variables. Multiple regression can be used to control for confounding variables by including them in the model.

 

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?

AG Stock Forecast (Buy or Sell) for 6 Month

Sample Set: Neural Network
Stock/Index: AG First Majestic Silver Corp. Ordinary Shares (Canada)
Time series to forecast: 6 Month

According to price forecasts for 6 Month period, the dominant strategy among neural network is: Speculative Trend

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 First Majestic Silver Corp. Ordinary Shares (Canada)

1. IFRS 16, issued in January 2016, amended paragraphs 2.1, 5.5.15, B4.3.8, B5.5.34 and B5.5.46. An entity shall apply those amendments when it applies IFRS 16.
2. If there are changes in circumstances that affect hedge effectiveness, an entity may have to change the method for assessing whether a hedging relationship meets the hedge effectiveness requirements in order to ensure that the relevant characteristics of the hedging relationship, including the sources of hedge ineffectiveness, are still captured.
3. A regular way purchase or sale gives rise to a fixed price commitment between trade date and settlement date that meets the definition of a derivative. However, because of the short duration of the commitment it is not recognised as a derivative financial instrument. Instead, this Standard provides for special accounting for such regular way contracts (see paragraphs 3.1.2 and B3.1.3–B3.1.6).
4. For the purpose of determining whether a forecast transaction (or a component thereof) is highly probable as required by paragraph 6.3.3, an entity shall assume that the interest rate benchmark on which the hedged cash flows (contractually or non-contractually specified) are based is not altered as a result of interest rate benchmark reform.

*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

First Majestic Silver Corp. Ordinary Shares (Canada) is assigned short-term Baa2 & long-term B1 estimated rating. First Majestic Silver Corp. Ordinary Shares (Canada) prediction model is evaluated with Deductive Inference (ML) and Multiple Regression^1,2,3,4 and it is concluded that the AG stock is predictable in the short/long term. According to price forecasts for 6 Month period, the dominant strategy among neural network is: Speculative Trend

AG First Majestic Silver Corp. Ordinary Shares (Canada) Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Baa2	B1
Income Statement	Baa2	Caa2
Balance Sheet	B1	B2
Leverage Ratios	Baa2	B1
Cash Flow	Baa2	B2
Rates of Return and Profitability	Baa2	Ba3

*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: 83 out of 100 with 757 signals.

References

1. Akgiray, V. (1989), "Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts," Journal of Business, 62, 55–80.
2. E. Altman. Constrained Markov decision processes, volume 7. CRC Press, 1999
3. Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]
4. S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
5. Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
6. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market? (No. Stock Analysis). AC Investment Research.
7. M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016

Frequently Asked Questions

Q: What is the prediction methodology for AG stock?
A: AG stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Multiple Regression
Q: Is AG stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend AG Stock.
Q: Is First Majestic Silver Corp. Ordinary Shares (Canada) stock a good investment?
A: The consensus rating for First Majestic Silver Corp. Ordinary Shares (Canada) is Speculative Trend and is assigned short-term Baa2 & long-term B1 estimated rating.
Q: What is the consensus rating of AG stock?
A: The consensus rating for AG is Speculative Trend.
Q: What is the prediction period for AG stock?
A: The prediction period for AG is 6 Month

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