## Summary

The categorization of high dimensional data present a fascinating challenge to machine learning models as frequent number of highly correlated dimensions or attributes can affect the accuracy of classification model. In this paper, the problem of high dimensionality of stock exchange is investigated to predict the market trends by applying the principal component analysis (PCA) with linear regression. PCA can help to improve the predictive performance of machine learning methods while reducing the redundancy among the data.** We evaluate CORO ENERGY PLC prediction models with Modular Neural Network (Market Direction Analysis) and Logistic Regression ^{1,2,3,4} and conclude that the LON:CORO stock is predictable in the short/long term. **

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold LON:CORO stock.**

## Key Points

- Prediction Modeling
- Operational Risk
- Why do we need predictive models?

## LON:CORO Target Price Prediction Modeling Methodology

We consider CORO ENERGY PLC Stock Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of LON:CORO 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 Î³ ∈ [0, 1] is a move factor for expectation.^{1,2,3,4}

F(Logistic 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 (Market Direction Analysis)) X S(n):→ (n+16 weeks) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of LON:CORO 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?

## LON:CORO Stock Forecast (Buy or Sell) for (n+16 weeks)

**Sample Set:**Neural Network

**Stock/Index:**LON:CORO CORO ENERGY PLC

**Time series to forecast n: 21 Nov 2022**for (n+16 weeks)

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold LON:CORO 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 CORO ENERGY PLC

- The fair value of a financial instrument at initial recognition is normally the transaction price (ie the fair value of the consideration given or received, see also paragraph B5.1.2A and IFRS 13). However, if part of the consideration given or received is for something other than the financial instrument, an entity shall measure the fair value of the financial instrument. For example, the fair value of a long-term loan or receivable that carries no interest can be measured as the present value of all future cash receipts discounted using the prevailing market rate(s) of interest for a similar instrument (similar as to currency, term, type of interest rate and other factors) with a similar credit rating. Any additional amount lent is an expense or a reduction of income unless it qualifies for recognition as some other type of asset.
- The definition of a derivative in this Standard includes contracts that are settled gross by delivery of the underlying item (eg a forward contract to purchase a fixed rate debt instrument). An entity may have a contract to buy or sell a non-financial item that can be settled net in cash or another financial instrument or by exchanging financial instruments (eg a contract to buy or sell a commodity at a fixed price at a future date). Such a contract is within the scope of this Standard unless it was entered into and continues to be held for the purpose of delivery of a non-financial item in accordance with the entity's expected purchase, sale or usage requirements. However, this Standard applies to such contracts for an entity's expected purchase, sale or usage requirements if the entity makes a designation in accordance with paragraph 2.5 (see paragraphs 2.4–2.7).
- To be eligible for designation as a hedged item, a risk component must be a separately identifiable component of the financial or the non-financial item, and the changes in the cash flows or the fair value of the item attributable to changes in that risk component must be reliably measurable.
- An entity shall apply Annual Improvements to IFRS Standards 2018–2020 to financial liabilities that are modified or exchanged on or after the beginning of the annual reporting period in which the entity first applies the amendment.

*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

CORO ENERGY PLC assigned short-term Ba3 & long-term B1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Logistic Regression ^{1,2,3,4} and conclude that the LON:CORO stock is predictable in the short/long term.**

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold LON:CORO stock.**

### Financial State Forecast for LON:CORO CORO ENERGY PLC Stock Options & Futures

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

Outlook* | Ba3 | B1 |

Operational Risk | 40 | 38 |

Market Risk | 60 | 43 |

Technical Analysis | 69 | 46 |

Fundamental Analysis | 87 | 76 |

Risk Unsystematic | 81 | 85 |

### Prediction Confidence Score

## References

- Athey S, Bayati M, Imbens G, Zhaonan Q. 2019. Ensemble methods for causal effects in panel data settings. NBER Work. Pap. 25675
- M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
- C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
- L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
- Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
- J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
- Bell RM, Koren Y. 2007. Lessons from the Netflix prize challenge. ACM SIGKDD Explor. Newsl. 9:75–79

## Frequently Asked Questions

Q: What is the prediction methodology for LON:CORO stock?A: LON:CORO stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Logistic Regression

Q: Is LON:CORO stock a buy or sell?

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

Q: Is CORO ENERGY PLC stock a good investment?

A: The consensus rating for CORO ENERGY PLC is Hold and assigned short-term Ba3 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of LON:CORO stock?

A: The consensus rating for LON:CORO is Hold.

Q: What is the prediction period for LON:CORO stock?

A: The prediction period for LON:CORO is (n+16 weeks)