This paper studies the possibilities of making prediction of stock market prices using historical data and machine learning algorithms.** We evaluate NB PRIVATE EQUITY PARTNERS LIMITED prediction models with Modular Neural Network (CNN Layer) and Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the LON:NBPU stock is predictable in the short/long term. **

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold LON:NBPU stock.**

**LON:NBPU, NB PRIVATE EQUITY PARTNERS LIMITED, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Dominated Move
- Probability Distribution
- Is Target price a good indicator?

## LON:NBPU Target Price Prediction Modeling Methodology

In this paper, we propose a robust and novel hybrid model for prediction of stock returns. The proposed model is constituted of two linear models: autoregressive moving average model, exponential smoothing model and a non-linear model: recurrent neural network. Training data for recurrent neural network is generated by a new regression model. Recurrent neural network produces satisfactory predictions as compared to linear models. With the goal to further improve the accuracy of predictions, the proposed hybrid prediction model merges predictions obtained from these three prediction based models. We consider NB PRIVATE EQUITY PARTNERS LIMITED Stock Decision Process with Wilcoxon Sign-Rank Test where A is the set of discrete actions of LON:NBPU 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(Wilcoxon Sign-Rank 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(Modular Neural Network (CNN Layer)) X S(n):→ (n+3 month) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of LON:NBPU 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:NBPU Stock Forecast (Buy or Sell) for (n+3 month)

**Sample Set:**Neural Network

**Stock/Index:**LON:NBPU NB PRIVATE EQUITY PARTNERS LIMITED

**Time series to forecast n: 04 Oct 2022**for (n+3 month)

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold LON:NBPU 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

NB PRIVATE EQUITY PARTNERS LIMITED assigned short-term B2 & long-term Baa2 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (CNN Layer) with Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the LON:NBPU stock is predictable in the short/long term.**

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold LON:NBPU stock.**

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

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

Outlook* | B2 | Baa2 |

Operational Risk | 47 | 89 |

Market Risk | 74 | 84 |

Technical Analysis | 53 | 64 |

Fundamental Analysis | 77 | 47 |

Risk Unsystematic | 32 | 90 |

### Prediction Confidence Score

## References

- D. Bertsekas and J. Tsitsiklis. Neuro-dynamic programming. Athena Scientific, 1996.
- Robins J, Rotnitzky A. 1995. Semiparametric efficiency in multivariate regression models with missing data. J. Am. Stat. Assoc. 90:122–29
- Pennington J, Socher R, Manning CD. 2014. GloVe: global vectors for word representation. In Proceedings of the 2014 Conference on Empirical Methods on Natural Language Processing, pp. 1532–43. New York: Assoc. Comput. Linguist.
- T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010
- Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
- Zeileis A, Hothorn T, Hornik K. 2008. Model-based recursive partitioning. J. Comput. Graph. Stat. 17:492–514 Zhou Z, Athey S, Wager S. 2018. Offline multi-action policy learning: generalization and optimization. arXiv:1810.04778 [stat.ML]
- V. Konda and J. Tsitsiklis. Actor-Critic algorithms. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1008–1014, 2000

## Frequently Asked Questions

Q: What is the prediction methodology for LON:NBPU stock?A: LON:NBPU stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Wilcoxon Sign-Rank Test

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

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

Q: Is NB PRIVATE EQUITY PARTNERS LIMITED stock a good investment?

A: The consensus rating for NB PRIVATE EQUITY PARTNERS LIMITED is Hold and assigned short-term B2 & long-term Baa2 forecasted stock rating.

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

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

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

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