One decision in Stock Market can make huge impact on an investor's life. The stock market is a complex system and often covered in mystery, it is therefore, very difficult to analyze all the impacting factors before making a decision. In this research, we have tried to design a stock market prediction model which is based on different factors. ** We evaluate ZAMBEEF PRODUCTS PLC prediction models with Modular Neural Network (Social Media Sentiment Analysis) and Multiple Regression ^{1,2,3,4} and conclude that the LON:ZAM stock is predictable in the short/long term. **

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy LON:ZAM stock.**

**LON:ZAM, ZAMBEEF PRODUCTS PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- What is neural prediction?
- Decision Making
- How do predictive algorithms actually work?

## LON:ZAM Target Price Prediction Modeling Methodology

Accurate prediction of stock price movements is highly challenging and significant topic for investors. Investors need to understand that stock price data is the most essential information which is highly volatile, non-linear, and non-parametric and are affected by many uncertainties and interrelated economic and political factors across the globe. Artificial Neural Networks (ANN) have been found to be an efficient tool in modeling stock prices and quite a large number of studies have been done on it. We consider ZAMBEEF PRODUCTS PLC Stock Decision Process with Multiple Regression where A is the set of discrete actions of LON:ZAM 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 (Social Media Sentiment Analysis)) X S(n):→ (n+4 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:ZAM 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?

## LON:ZAM Stock Forecast (Buy or Sell) for (n+4 weeks)

**Sample Set:**Neural Network

**Stock/Index:**LON:ZAM ZAMBEEF PRODUCTS PLC

**Time series to forecast n: 24 Sep 2022**for (n+4 weeks)

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy LON:ZAM 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

ZAMBEEF PRODUCTS PLC assigned short-term Ba1 & long-term B2 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) with Multiple Regression ^{1,2,3,4} and conclude that the LON:ZAM stock is predictable in the short/long term.**

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy LON:ZAM stock.**

### Financial State Forecast for LON:ZAM Stock Options & Futures

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

Outlook* | Ba1 | B2 |

Operational Risk | 72 | 57 |

Market Risk | 88 | 42 |

Technical Analysis | 69 | 74 |

Fundamental Analysis | 61 | 68 |

Risk Unsystematic | 71 | 33 |

### Prediction Confidence Score

## References

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- Hastie T, Tibshirani R, Friedman J. 2009. The Elements of Statistical Learning. Berlin: Springer
- Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
- Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221
- Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]
- Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press
- Chernozhukov V, Newey W, Robins J. 2018c. Double/de-biased machine learning using regularized Riesz representers. arXiv:1802.08667 [stat.ML]

## Frequently Asked Questions

Q: What is the prediction methodology for LON:ZAM stock?A: LON:ZAM stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Multiple Regression

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

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

Q: Is ZAMBEEF PRODUCTS PLC stock a good investment?

A: The consensus rating for ZAMBEEF PRODUCTS PLC is Buy and assigned short-term Ba1 & long-term B2 forecasted stock rating.

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

A: The consensus rating for LON:ZAM is Buy.

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

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

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