Modelling A.I. in Economics

SCZ:TSXV Santacruz Silver Mining Ltd.

Outlook: Santacruz Silver Mining Ltd. is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 21 May 2023 for (n+1 year)
Methodology : Deductive Inference (ML)

Abstract

Santacruz Silver Mining Ltd. prediction model is evaluated with Deductive Inference (ML) and Stepwise Regression1,2,3,4 and it is concluded that the SCZ:TSXV stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Key Points

  1. How do you know when a stock will go up or down?
  2. Game Theory
  3. Game Theory

SCZ:TSXV Target Price Prediction Modeling Methodology

We consider Santacruz Silver Mining Ltd. Decision Process with Deductive Inference (ML) where A is the set of discrete actions of SCZ:TSXV 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(Stepwise Regression)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Deductive Inference (ML)) X S(n):→ (n+1 year) i = 1 n s i

n:Time series to forecast

p:Price signals of SCZ:TSXV 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?

SCZ:TSXV Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: SCZ:TSXV Santacruz Silver Mining Ltd.
Time series to forecast n: 21 May 2023 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

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 Santacruz Silver Mining Ltd.

  1. An entity can rebut this presumption. However, it can do so only when it has reasonable and supportable information available that demonstrates that even if contractual payments become more than 30 days past due, this does not represent a significant increase in the credit risk of a financial instrument. For example when non-payment was an administrative oversight, instead of resulting from financial difficulty of the borrower, or the entity has access to historical evidence that demonstrates that there is no correlation between significant increases in the risk of a default occurring and financial assets on which payments are more than 30 days past due, but that evidence does identify such a correlation when payments are more than 60 days past due.
  2. Rebalancing is accounted for as a continuation of the hedging relationship in accordance with paragraphs B6.5.9–B6.5.21. On rebalancing, the hedge ineffectiveness of the hedging relationship is determined and recognised immediately before adjusting the hedging relationship.
  3. For the purposes of applying the requirement in paragraph 5.7.7(a), credit risk is different from asset-specific performance risk. Asset-specific performance risk is not related to the risk that an entity will fail to discharge a particular obligation but instead it is related to the risk that a single asset or a group of assets will perform poorly (or not at all).
  4. Although the objective of an entity's business model may be to hold financial assets in order to collect contractual cash flows, the entity need not hold all of those instruments until maturity. Thus an entity's business model can be to hold financial assets to collect contractual cash flows even when sales of financial assets occur or are expected to occur in the future.

*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

Santacruz Silver Mining Ltd. is assigned short-term Ba1 & long-term Ba1 estimated rating. Santacruz Silver Mining Ltd. prediction model is evaluated with Deductive Inference (ML) and Stepwise Regression1,2,3,4 and it is concluded that the SCZ:TSXV stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

SCZ:TSXV Santacruz Silver Mining Ltd. Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCCaa2
Balance SheetCBaa2
Leverage RatiosCaa2Baa2
Cash FlowCaa2Caa2
Rates of Return and ProfitabilityCBaa2

*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: 78 out of 100 with 582 signals.

References

  1. Harris ZS. 1954. Distributional structure. Word 10:146–62
  2. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market? (No. Stock Analysis). AC Investment Research.
  3. Bickel P, Klaassen C, Ritov Y, Wellner J. 1998. Efficient and Adaptive Estimation for Semiparametric Models. Berlin: Springer
  4. Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
  5. Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]
  6. Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
  7. 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
Frequently Asked QuestionsQ: What is the prediction methodology for SCZ:TSXV stock?
A: SCZ:TSXV stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Stepwise Regression
Q: Is SCZ:TSXV stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes SCZ:TSXV Stock.
Q: Is Santacruz Silver Mining Ltd. stock a good investment?
A: The consensus rating for Santacruz Silver Mining Ltd. is Wait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of SCZ:TSXV stock?
A: The consensus rating for SCZ:TSXV is Wait until speculative trend diminishes.
Q: What is the prediction period for SCZ:TSXV stock?
A: The prediction period for SCZ:TSXV is (n+1 year)

Premium

  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

Login
This project is licensed under the license; additional terms may apply.