Investors raise profit from stock market by maximising gains and minimising loses. The profit is difficult to raise because of the volatile nature of stock market prices. Predictive modelling allows investors to make informed decisions. ** We evaluate Endeavour Mining prediction models with Modular Neural Network (CNN Layer) and Spearman Correlation ^{1,2,3,4} and conclude that the EDV 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 EDV stock.**

**EDV, Endeavour Mining, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Fundemental Analysis with Algorithmic Trading
- Trust metric by Neural Network
- How do you decide buy or sell a stock?

## EDV Target Price Prediction Modeling Methodology

Stock prediction is a very hot topic in our life. However, in the early time, because of some reasons and the limitation of the device, only a few people had the access to the study. Thanks to the rapid development of science and technology, in recent years more and more people are devoted to the study of the prediction and it becomes easier and easier for us to make stock prediction by using different ways now, including machine learning, deep learning and so on. We consider Endeavour Mining Stock Decision Process with Spearman Correlation where A is the set of discrete actions of EDV 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(Spearman 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(Modular Neural Network (CNN Layer)) X S(n):→ (n+8 weeks) $\sum _{i=1}^{n}\left({r}_{i}\right)$

n:Time series to forecast

p:Price signals of EDV stock

j:Nash equilibria

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?

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

**Sample Set:**Neural Network

**Stock/Index:**EDV Endeavour Mining

**Time series to forecast n: 20 Oct 2022**for (n+8 weeks)

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold EDV 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%**

## Conclusions

Endeavour Mining assigned short-term Baa2 & long-term Ba1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (CNN Layer) with Spearman Correlation ^{1,2,3,4} and conclude that the EDV 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 EDV stock.**

### Financial State Forecast for EDV Stock Options & Futures

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

Outlook* | Baa2 | Ba1 |

Operational Risk | 83 | 88 |

Market Risk | 89 | 78 |

Technical Analysis | 54 | 71 |

Fundamental Analysis | 89 | 71 |

Risk Unsystematic | 68 | 47 |

### Prediction Confidence Score

## References

- M. L. Littman. Friend-or-foe q-learning in general-sum games. In Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001, pages 322–328, 2001
- Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
- A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
- Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]
- S. Bhatnagar and K. Lakshmanan. An online actor-critic algorithm with function approximation for con- strained Markov decision processes. Journal of Optimization Theory and Applications, 153(3):688–708, 2012.
- P. Marbach. Simulated-Based Methods for Markov Decision Processes. PhD thesis, Massachusetts Institute of Technology, 1998
- Chen, C. L. Liu (1993), "Joint estimation of model parameters and outlier effects in time series," Journal of the American Statistical Association, 88, 284–297.

## Frequently Asked Questions

Q: What is the prediction methodology for EDV stock?A: EDV stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Spearman Correlation

Q: Is EDV stock a buy or sell?

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

Q: Is Endeavour Mining stock a good investment?

A: The consensus rating for Endeavour Mining is Hold and assigned short-term Baa2 & long-term Ba1 forecasted stock rating.

Q: What is the consensus rating of EDV stock?

A: The consensus rating for EDV is Hold.

Q: What is the prediction period for EDV stock?

A: The prediction period for EDV is (n+8 weeks)

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