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 : Hold
Time series to forecast n: 20 Feb 2023 for (n+16 weeks)
Methodology : Modular Neural Network (Social Media Sentiment Analysis)

Abstract

Santacruz Silver Mining Ltd. prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Polynomial 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+16 weeks) period, the dominant strategy among neural network is: Hold

Key Points

  1. What are the most successful trading algorithms?
  2. Understanding Buy, Sell, and Hold Ratings
  3. Stock Forecast Based On a Predictive Algorithm

SCZ:TSXV Target Price Prediction Modeling Methodology

We consider Santacruz Silver Mining Ltd. Decision Process with Modular Neural Network (Social Media Sentiment Analysis) 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(Polynomial 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(Modular Neural Network (Social Media Sentiment Analysis)) X S(n):→ (n+16 weeks) i = 1 n r 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+16 weeks)

Sample Set: Neural Network
Stock/Index: SCZ:TSXV Santacruz Silver Mining Ltd.
Time series to forecast n: 20 Feb 2023 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Hold

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. If, at the date of initial application, it is impracticable (as defined in IAS 8) for an entity to assess whether the fair value of a prepayment feature was insignificant in accordance with paragraph B4.1.12(c) on the basis of the facts and circumstances that existed at the initial recognition of the financial asset, an entity shall assess the contractual cash flow characteristics of that financial asset on the basis of the facts and circumstances that existed at the initial recognition of the financial asset without taking into account the exception for prepayment features in paragraph B4.1.12. (See also paragraph 42S of IFRS 7.)
  2. 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.
  3. An entity shall assess separately whether each subgroup meets the requirements in paragraph 6.6.1 to be an eligible hedged item. If any subgroup fails to meet the requirements in paragraph 6.6.1, the entity shall discontinue hedge accounting prospectively for the hedging relationship in its entirety. An entity also shall apply the requirements in paragraphs 6.5.8 and 6.5.11 to account for ineffectiveness related to the hedging relationship in its entirety.
  4. As with all fair value measurements, an entity's measurement method for determining the portion of the change in the liability's fair value that is attributable to changes in its credit risk must make maximum use of relevant observable inputs and minimum use of unobservable inputs.

*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 Modular Neural Network (Social Media Sentiment Analysis) and Polynomial 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+16 weeks) period, the dominant strategy among neural network is: Hold

SCZ:TSXV Santacruz Silver Mining Ltd. Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCB3
Balance SheetBaa2B1
Leverage RatiosB1Ba1
Cash FlowBaa2Baa2
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 527 signals.

References

  1. Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
  2. Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36
  3. Rosenbaum PR, Rubin DB. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70:41–55
  4. Bengio Y, Schwenk H, Senécal JS, Morin F, Gauvain JL. 2006. Neural probabilistic language models. In Innovations in Machine Learning: Theory and Applications, ed. DE Holmes, pp. 137–86. Berlin: Springer
  5. Abadie A, Cattaneo MD. 2018. Econometric methods for program evaluation. Annu. Rev. Econ. 10:465–503
  6. Batchelor, R. P. Dua (1993), "Survey vs ARCH measures of inflation uncertainty," Oxford Bulletin of Economics Statistics, 55, 341–353.
  7. Wager S, Athey S. 2017. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. 113:1228–42
Frequently Asked QuestionsQ: What is the prediction methodology for SCZ:TSXV stock?
A: SCZ:TSXV stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Polynomial Regression
Q: Is SCZ:TSXV stock a buy or sell?
A: The dominant strategy among neural network is to Hold SCZ:TSXV Stock.
Q: Is Santacruz Silver Mining Ltd. stock a good investment?
A: The consensus rating for Santacruz Silver Mining Ltd. is Hold 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 Hold.
Q: What is the prediction period for SCZ:TSXV stock?
A: The prediction period for SCZ:TSXV is (n+16 weeks)



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