**Outlook:**CODRUS MINERALS LIMITED assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 24 Dec 2022**for (n+3 month)

**Methodology :**Statistical Inference (ML)

## Abstract

In this paper we investigate ways to use prior knowledge and neural networks to improve multivariate prediction ability. Daily stock prices are predicted as a complicated real-world problem, taking non-numerical factors such as political and international events are into account. We have studied types of prior knowledge which are difficult to insert into initial network structures or to represent in the form of error measurements. (Wang, Y., 2014. Stock price direction prediction by directly using prices data: an empirical study on the KOSPI and HSI. International Journal of Business Intelligence and Data Mining, 9(2), pp.145-160.)** We evaluate CODRUS MINERALS LIMITED prediction models with Statistical Inference (ML) and Pearson Correlation ^{1,2,3,4} and conclude that the CDR stock is predictable in the short/long term. **

**According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy**

## Key Points

- Trading Interaction
- What is statistical models in machine learning?
- Fundemental Analysis with Algorithmic Trading

## CDR Target Price Prediction Modeling Methodology

We consider CODRUS MINERALS LIMITED Decision Process with Statistical Inference (ML) where A is the set of discrete actions of CDR 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(Pearson Correlation)

^{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(Statistical Inference (ML)) X S(n):→ (n+3 month) $\sum _{i=1}^{n}\left({r}_{i}\right)$

n:Time series to forecast

p:Price signals of CDR 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?

## CDR Stock Forecast (Buy or Sell) for (n+3 month)

**Sample Set:**Neural Network

**Stock/Index:**CDR CODRUS MINERALS LIMITED

**Time series to forecast n: 24 Dec 2022**for (n+3 month)

**According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy**

**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 CODRUS MINERALS LIMITED

- Expected credit losses are a probability-weighted estimate of credit losses (ie the present value of all cash shortfalls) over the expected life of the financial instrument. A cash shortfall is the difference between the cash flows that are due to an entity in accordance with the contract and the cash flows that the entity expects to receive. Because expected credit losses consider the amount and timing of payments, a credit loss arises even if the entity expects to be paid in full but later than when contractually due.
- The credit risk on a financial instrument is considered low for the purposes of paragraph 5.5.10, if the financial instrument has a low risk of default, the borrower has a strong capacity to meet its contractual cash flow obligations in the near term and adverse changes in economic and business conditions in the longer term may, but will not necessarily, reduce the ability of the borrower to fulfil its contractual cash flow obligations. Financial instruments are not considered to have low credit risk when they are regarded as having a low risk of loss simply because of the value of collateral and the financial instrument without that collateral would not be considered low credit risk. Financial instruments are also not considered to have low credit risk simply because they have a lower risk of default than the entity's other financial instruments or relative to the credit risk of the jurisdiction within which an entity operates.
- Fluctuation around a constant hedge ratio (and hence the related hedge ineffectiveness) cannot be reduced by adjusting the hedge ratio in response to each particular outcome. Hence, in such circumstances, the change in the extent of offset is a matter of measuring and recognising hedge ineffectiveness but does not require rebalancing.
- Expected credit losses reflect an entity's own expectations of credit losses. However, when considering all reasonable and supportable information that is available without undue cost or effort in estimating expected credit losses, an entity should also consider observable market information about the credit risk of the particular financial instrument or similar financial instruments.

*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

CODRUS MINERALS LIMITED assigned short-term Ba1 & long-term Ba1 estimated rating.** We evaluate the prediction models Statistical Inference (ML) with Pearson Correlation ^{1,2,3,4} and conclude that the CDR stock is predictable in the short/long term.**

**According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy**

### CDR CODRUS MINERALS LIMITED Financial Analysis*

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

Outlook* | Ba1 | Ba1 |

Income Statement | B2 | B1 |

Balance Sheet | B2 | Caa2 |

Leverage Ratios | Baa2 | B2 |

Cash Flow | C | Baa2 |

Rates of Return and Profitability | B2 | C |

*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

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- Scott SL. 2010. A modern Bayesian look at the multi-armed bandit. Appl. Stoch. Models Bus. Ind. 26:639–58
- Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Is DOW Stock Expected to Go Up?(Stock Forecast). AC Investment Research Journal, 101(3).
- Breusch, T. S. (1978), "Testing for autocorrelation in dynamic linear models," Australian Economic Papers, 17, 334–355.
- Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
- Hill JL. 2011. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20:217–40

## Frequently Asked Questions

Q: What is the prediction methodology for CDR stock?A: CDR stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Pearson Correlation

Q: Is CDR stock a buy or sell?

A: The dominant strategy among neural network is to Buy CDR Stock.

Q: Is CODRUS MINERALS LIMITED stock a good investment?

A: The consensus rating for CODRUS MINERALS LIMITED is Buy and assigned short-term Ba1 & long-term Ba1 estimated rating.

Q: What is the consensus rating of CDR stock?

A: The consensus rating for CDR is Buy.

Q: What is the prediction period for CDR stock?

A: The prediction period for CDR is (n+3 month)