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 PREMIER AFRICAN MINERALS LIMITED prediction models with Reinforcement Machine Learning (ML) and Stepwise Regression1,2,3,4 and conclude that the LON:PREM stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold LON:PREM stock.

Keywords: LON:PREM, PREMIER AFRICAN MINERALS LIMITED, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. Technical Analysis with Algorithmic Trading
2. Market Risk
3. Stock Rating

## LON:PREM Target Price Prediction Modeling Methodology

Accurate stock market prediction is of great interest to investors; however, stock markets are driven by volatile factors such as microblogs and news that make it hard to predict stock market index based on merely the historical data. The enormous stock market volatility emphasizes the need to effectively assess the role of external factors in stock prediction. Stock markets can be predicted using machine learning algorithms on information contained in social media and financial news, as this data can change investors' behavior. We consider PREMIER AFRICAN MINERALS LIMITED Stock Decision Process with Stepwise Regression where A is the set of discrete actions of LON:PREM 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(Stepwise 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(Reinforcement Machine Learning (ML)) X S(n):→ (n+1 year) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of LON:PREM 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:PREM Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: LON:PREM PREMIER AFRICAN MINERALS LIMITED
Time series to forecast n: 19 Sep 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold LON:PREM 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

PREMIER AFRICAN MINERALS LIMITED assigned short-term B1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Reinforcement Machine Learning (ML) with Stepwise Regression1,2,3,4 and conclude that the LON:PREM stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold LON:PREM stock.

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

Rating Short-Term Long-Term Senior
Outlook*B1Ba3
Operational Risk 6183
Market Risk5172
Technical Analysis7669
Fundamental Analysis7254
Risk Unsystematic3154

### Prediction Confidence Score

Trust metric by Neural Network: 85 out of 100 with 734 signals.

## References

1. Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
2. Thomas P, Brunskill E. 2016. Data-efficient off-policy policy evaluation for reinforcement learning. In Pro- ceedings of the International Conference on Machine Learning, pp. 2139–48. La Jolla, CA: Int. Mach. Learn. Soc.
3. E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004
4. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
5. Chen X. 2007. Large sample sieve estimation of semi-nonparametric models. In Handbook of Econometrics, Vol. 6B, ed. JJ Heckman, EE Learner, pp. 5549–632. Amsterdam: Elsevier
6. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99
7. L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:PREM stock?
A: LON:PREM stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Stepwise Regression
Q: Is LON:PREM stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:PREM Stock.
Q: Is PREMIER AFRICAN MINERALS LIMITED stock a good investment?
A: The consensus rating for PREMIER AFRICAN MINERALS LIMITED is Hold and assigned short-term B1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of LON:PREM stock?
A: The consensus rating for LON:PREM is Hold.
Q: What is the prediction period for LON:PREM stock?
A: The prediction period for LON:PREM is (n+1 year)