CZN Options & Futures Prediction

CORAZON MINING LIMITED Research Report

Summary

The main objective of this research is to predict the market performance on day closing using different machine learning techniques. The prediction model uses different attributes as an input and predicts market as Positive & Negative. We evaluate CORAZON MINING LIMITED prediction models with Modular Neural Network (Market News Sentiment Analysis) and Independent T-Test1,2,3,4 and conclude that the CZN stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold CZN stock.

Key Points

  1. What is the best way to predict stock prices?
  2. What is Markov decision process in reinforcement learning?
  3. Market Risk

CZN Target Price Prediction Modeling Methodology

We consider CORAZON MINING LIMITED Stock Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of CZN 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= 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 (Market News Sentiment Analysis)) X S(n):→ (n+8 weeks) S = s 1 s 2 s 3

n:Time series to forecast

p:Price signals of CZN 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?

CZN Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: CZN CORAZON MINING LIMITED
Time series to forecast n: 22 Nov 2022 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold CZN stock.

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 (Yellow to Green): *Technical Analysis%

Adjusted IFRS* Prediction Methods for CORAZON MINING LIMITED

  1. Measurement of a financial asset or financial liability and classification of recognised changes in its value are determined by the item's classification and whether the item is part of a designated hedging relationship. Those requirements can create a measurement or recognition inconsistency (sometimes referred to as an 'accounting mismatch') when, for example, in the absence of designation as at fair value through profit or loss, a financial asset would be classified as subsequently measured at fair value through profit or loss and a liability the entity considers related would be subsequently measured at amortised cost (with changes in fair value not recognised). In such circumstances, an entity may conclude that its financial statements would provide more relevant information if both the asset and the liability were measured as at fair value through profit or loss.
  2. If the group of items does not have any offsetting risk positions (for example, a group of foreign currency expenses that affect different line items in the statement of profit or loss and other comprehensive income that are hedged for foreign currency risk) then the reclassified hedging instrument gains or losses shall be apportioned to the line items affected by the hedged items. This apportionment shall be done on a systematic and rational basis and shall not result in the grossing up of the net gains or losses arising from a single hedging instrument.
  3. The requirement that an economic relationship exists means that the hedging instrument and the hedged item have values that generally move in the opposite direction because of the same risk, which is the hedged risk. Hence, there must be an expectation that the value of the hedging instrument and the value of the hedged item will systematically change in response to movements in either the same underlying or underlyings that are economically related in such a way that they respond in a similar way to the risk that is being hedged (for example, Brent and WTI crude oil).
  4. IFRS 7 defines credit risk as 'the risk that one party to a financial instrument will cause a financial loss for the other party by failing to discharge an obligation'. The requirement in paragraph 5.7.7(a) relates to the risk that the issuer will fail to perform on that particular liability. It does not necessarily relate to the creditworthiness of the issuer. For example, if an entity issues a collateralised liability and a non-collateralised liability that are otherwise identical, the credit risk of those two liabilities will be different, even though they are issued by the same entity. The credit risk on the collateralised liability will be less than the credit risk of the non-collateralised liability. The credit risk for a collateralised liability may be close to zero.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

CORAZON MINING LIMITED assigned short-term B3 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) with Independent T-Test1,2,3,4 and conclude that the CZN stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold CZN stock.

Financial State Forecast for CZN CORAZON MINING LIMITED Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B3Ba3
Operational Risk 5543
Market Risk4489
Technical Analysis3641
Fundamental Analysis8378
Risk Unsystematic3475

Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 853 signals.

References

  1. Breusch, T. S. (1978), "Testing for autocorrelation in dynamic linear models," Australian Economic Papers, 17, 334–355.
  2. Breusch, T. S. A. R. Pagan (1979), "A simple test for heteroskedasticity and random coefficient variation," Econometrica, 47, 1287–1294.
  3. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2016a. Double machine learning for treatment and causal parameters. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London
  4. Challen, D. W. A. J. Hagger (1983), Macroeconomic Systems: Construction, Validation and Applications. New York: St. Martin's Press.
  5. Matzkin RL. 1994. Restrictions of economic theory in nonparametric methods. In Handbook of Econometrics, Vol. 4, ed. R Engle, D McFadden, pp. 2523–58. Amsterdam: Elsevier
  6. Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
  7. R. Sutton and A. Barto. Reinforcement Learning. The MIT Press, 1998
Frequently Asked QuestionsQ: What is the prediction methodology for CZN stock?
A: CZN stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Independent T-Test
Q: Is CZN stock a buy or sell?
A: The dominant strategy among neural network is to Hold CZN Stock.
Q: Is CORAZON MINING LIMITED stock a good investment?
A: The consensus rating for CORAZON MINING LIMITED is Hold and assigned short-term B3 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of CZN stock?
A: The consensus rating for CZN is Hold.
Q: What is the prediction period for CZN stock?
A: The prediction period for CZN is (n+8 weeks)

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