The stock market prediction has attracted much attention from academia as well as business. Due to the non-linear, volatile and complex nature of the market, it is quite difficult to predict. As the stock markets grow bigger, more investors pay attention to develop a systematic approach to predict the stock market. We evaluate NB PRIVATE EQUITY PARTNERS LIMITED prediction models with Active Learning (ML) and Multiple Regression1,2,3,4 and conclude that the LON:NBPU stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Sell LON:NBPU stock.

Keywords: 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.

## Key Points

1. Stock Forecast Based On a Predictive Algorithm
2. Stock Forecast Based On a Predictive Algorithm

## LON:NBPU Target Price Prediction Modeling Methodology

Prediction of stock market is a long-time attractive topic to researchers from different fields. In particular, numerous studies have been conducted to predict the movement of stock market using machine learning algorithms such as support vector machine (SVM) and reinforcement learning. In this project, we propose a new prediction algorithm that exploits the temporal correlation among global stock markets and various financial products to predict the next-day stock trend. We consider NB PRIVATE EQUITY PARTNERS LIMITED Stock Decision Process with Multiple Regression 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(Multiple Regression)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Active Learning (ML)) X S(n):→ (n+6 month) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of LON: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+6 month)

Sample Set: Neural Network
Stock/Index: LON:NBPU NB PRIVATE EQUITY PARTNERS LIMITED
Time series to forecast n: 15 Sep 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Sell 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 B1 forecasted stock rating. We evaluate the prediction models Active Learning (ML) with Multiple Regression1,2,3,4 and conclude that the LON:NBPU stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Sell LON:NBPU stock.

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

Rating Short-Term Long-Term Senior
Outlook*B2B1
Operational Risk 8142
Market Risk6668
Technical Analysis4039
Fundamental Analysis3153
Risk Unsystematic5976

### Prediction Confidence Score

Trust metric by Neural Network: 76 out of 100 with 822 signals.

## References

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2. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
3. M. L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Ma- chine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994, pages 157–163, 1994
4. Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
5. D. S. Bernstein, S. Zilberstein, and N. Immerman. The complexity of decentralized control of Markov Decision Processes. In UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30 - July 3, 2000, pages 32–37, 2000.
6. Bewley, R. M. Yang (1998), "On the size and power of system tests for cointegration," Review of Economics and Statistics, 80, 675–679.
7. Breiman L. 1993. Better subset selection using the non-negative garotte. Tech. Rep., Univ. Calif., Berkeley
Frequently Asked QuestionsQ: What is the prediction methodology for LON:NBPU stock?
A: LON:NBPU stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Multiple Regression
Q: Is LON:NBPU stock a buy or sell?
A: The dominant strategy among neural network is to Sell 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 Sell and assigned short-term B2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of LON:NBPU stock?
A: The consensus rating for LON:NBPU is Sell.
Q: What is the prediction period for LON:NBPU stock?
A: The prediction period for LON:NBPU is (n+6 month)