**Outlook:**CZR RESOURCES LTD is assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Hold

**Time series to forecast n: 27 May 2023**for (n+4 weeks)

**Methodology :**Modular Neural Network (DNN Layer)

## Abstract

CZR RESOURCES LTD prediction model is evaluated with Modular Neural Network (DNN Layer) and Multiple Regression^{1,2,3,4}and it is concluded that the CZR stock is predictable in the short/long term.

**According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Hold**

## Key Points

- Should I buy stocks now or wait amid such uncertainty?
- What are the most successful trading algorithms?
- Game Theory

## CZR Target Price Prediction Modeling Methodology

We consider CZR RESOURCES LTD Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of CZR 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}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (DNN Layer)) X S(n):→ (n+4 weeks) $\sum _{i=1}^{n}\left({a}_{i}\right)$

n:Time series to forecast

p:Price signals of CZR 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?

## CZR Stock Forecast (Buy or Sell) for (n+4 weeks)

**Sample Set:**Neural Network

**Stock/Index:**CZR CZR RESOURCES LTD

**Time series to forecast n: 27 May 2023**for (n+4 weeks)

**According to price forecasts for (n+4 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 CZR RESOURCES LTD

- Adjusting the hedge ratio by decreasing the volume of the hedging instrument does not affect how the changes in the value of the hedged item are measured. The measurement of the changes in the fair value of the hedging instrument related to the volume that continues to be designated also remains unaffected. However, from the date of rebalancing, the volume by which the hedging instrument was decreased is no longer part of the hedging relationship. For example, if an entity originally hedged the price risk of a commodity using a derivative volume of 100 tonnes as the hedging instrument and reduces that volume by 10 tonnes on rebalancing, a nominal amount of 90 tonnes of the hedging instrument volume would remain (see paragraph B6.5.16 for the consequences for the derivative volume (ie the 10 tonnes) that is no longer a part of the hedging relationship).
- An entity shall apply this Standard for annual periods beginning on or after 1 January 2018. Earlier application is permitted. If an entity elects to apply this Standard early, it must disclose that fact and apply all of the requirements in this Standard at the same time (but see also paragraphs 7.1.2, 7.2.21 and 7.3.2). It shall also, at the same time, apply the amendments in Appendix C.
- For purchased or originated credit-impaired financial assets, expected credit losses shall be discounted using the credit-adjusted effective interest rate determined at initial recognition.
- 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.

## Conclusions

CZR RESOURCES LTD is assigned short-term Ba1 & long-term Ba1 estimated rating. CZR RESOURCES LTD prediction model is evaluated with Modular Neural Network (DNN Layer) and Multiple Regression^{1,2,3,4} and it is concluded that the CZR stock is predictable in the short/long term. ** According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Hold**

### CZR CZR RESOURCES LTD Financial Analysis*

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | Ba1 | Ba1 |

Income Statement | Caa2 | C |

Balance Sheet | C | Caa2 |

Leverage Ratios | C | C |

Cash Flow | C | Caa2 |

Rates of Return and Profitability | Ba3 | Baa2 |

*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

## References

- Dudik M, Erhan D, Langford J, Li L. 2014. Doubly robust policy evaluation and optimization. Stat. Sci. 29:485–511
- Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
- Hastie T, Tibshirani R, Friedman J. 2009. The Elements of Statistical Learning. Berlin: Springer
- R. Rockafellar and S. Uryasev. Conditional value-at-risk for general loss distributions. Journal of Banking and Finance, 26(7):1443 – 1471, 2002
- M. Sobel. The variance of discounted Markov decision processes. Applied Probability, pages 794–802, 1982
- Burgess, D. F. (1975), "Duality theory and pitfalls in the specification of technologies," Journal of Econometrics, 3, 105–121.
- D. White. Mean, variance, and probabilistic criteria in finite Markov decision processes: A review. Journal of Optimization Theory and Applications, 56(1):1–29, 1988.

## Frequently Asked Questions

Q: What is the prediction methodology for CZR stock?A: CZR stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Multiple Regression

Q: Is CZR stock a buy or sell?

A: The dominant strategy among neural network is to Hold CZR Stock.

Q: Is CZR RESOURCES LTD stock a good investment?

A: The consensus rating for CZR RESOURCES LTD is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.

Q: What is the consensus rating of CZR stock?

A: The consensus rating for CZR is Hold.

Q: What is the prediction period for CZR stock?

A: The prediction period for CZR is (n+4 weeks)

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