Sentiment Analysis is new way of machine learning to extract opinion orientation (positive, negative, neutral) from a text segment written for any product, organization, person or any other entity. Sentiment Analysis can be used to predict the mood of people that have impact on stock prices, therefore it can help in prediction of actual stock movement. ** We evaluate PURE GOLD MINING INC. prediction models with Inductive Learning (ML) and Paired T-Test ^{1,2,3,4} and conclude that the LON:PUR 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:PUR stock.**

**LON:PUR, PURE GOLD MINING INC., stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- What is prediction model?
- Decision Making
- How can neural networks improve predictions?

## LON:PUR Target Price Prediction Modeling Methodology

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 consider PURE GOLD MINING INC. Stock Decision Process with Paired T-Test where A is the set of discrete actions of LON:PUR 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(Paired T-Test)

^{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(Inductive Learning (ML)) X S(n):→ (n+16 weeks) $\sum _{i=1}^{n}\left({r}_{i}\right)$

n:Time series to forecast

p:Price signals of LON:PUR 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:PUR Stock Forecast (Buy or Sell) for (n+16 weeks)

**Sample Set:**Neural Network

**Stock/Index:**LON:PUR PURE GOLD MINING INC.

**Time series to forecast n: 15 Sep 2022**for (n+16 weeks)

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

PURE GOLD MINING INC. assigned short-term B1 & long-term Ba2 forecasted stock rating.** We evaluate the prediction models Inductive Learning (ML) with Paired T-Test ^{1,2,3,4} and conclude that the LON:PUR 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:PUR stock.**

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

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

Outlook* | B1 | Ba2 |

Operational Risk | 36 | 46 |

Market Risk | 57 | 53 |

Technical Analysis | 70 | 79 |

Fundamental Analysis | 74 | 87 |

Risk Unsystematic | 53 | 72 |

### Prediction Confidence Score

## References

- Clements, M. P. D. F. Hendry (1997), "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, 13, 341–355.
- 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.
- Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
- Holland PW. 1986. Statistics and causal inference. J. Am. Stat. Assoc. 81:945–60
- Athey S, Imbens G. 2016. Recursive partitioning for heterogeneous causal effects. PNAS 113:7353–60
- Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
- D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009

## Frequently Asked Questions

Q: What is the prediction methodology for LON:PUR stock?A: LON:PUR stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Paired T-Test

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

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

Q: Is PURE GOLD MINING INC. stock a good investment?

A: The consensus rating for PURE GOLD MINING INC. is Hold and assigned short-term B1 & long-term Ba2 forecasted stock rating.

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

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

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

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

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