This paper tries to address the problem of stock market prediction leveraging artificial intelligence (AI) strategies. The stock market prediction can be modeled based on two principal analyses called technical and fundamental. In the technical analysis approach, the regression machine learning (ML) algorithms are employed to predict the stock price trend at the end of a business day based on the historical price data. In contrast, in the fundamental analysis, the classification ML algorithms are applied to classify the public sentiment based on news and social media.** We evaluate ALFA FINANCIAL SOFTWARE HOLDINGS PLC prediction models with Modular Neural Network (DNN Layer) and Polynomial Regression ^{1,2,3,4} and conclude that the LON:ALFA 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 Hold LON:ALFA stock.**

**LON:ALFA, ALFA FINANCIAL SOFTWARE HOLDINGS PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Can neural networks predict stock market?
- Trust metric by Neural Network
- Decision Making

## LON:ALFA Target Price Prediction Modeling Methodology

Time series forecasting has been widely used to determine the future prices of stock, and the analysis and modeling of finance time series importantly guide investors' decisions and trades. In addition, in a dynamic environment such as the stock market, the nonlinearity of the time series is pronounced, immediately affecting the efficacy of stock price forecasts. Thus, this paper proposes an intelligent time series prediction system that uses sliding-window metaheuristic optimization for the purpose of predicting the stock prices. We consider ALFA FINANCIAL SOFTWARE HOLDINGS PLC Stock Decision Process with Polynomial Regression where A is the set of discrete actions of LON:ALFA 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(Polynomial 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 (DNN Layer)) X S(n):→ (n+6 month) $\sum _{i=1}^{n}\left({s}_{i}\right)$

n:Time series to forecast

p:Price signals of LON:ALFA 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:ALFA Stock Forecast (Buy or Sell) for (n+6 month)

**Sample Set:**Neural Network

**Stock/Index:**LON:ALFA ALFA FINANCIAL SOFTWARE HOLDINGS PLC

**Time series to forecast n: 04 Oct 2022**for (n+6 month)

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:ALFA 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

ALFA FINANCIAL SOFTWARE HOLDINGS PLC assigned short-term Ba3 & long-term Ba3 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (DNN Layer) with Polynomial Regression ^{1,2,3,4} and conclude that the LON:ALFA 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 Hold LON:ALFA stock.**

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

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

Outlook* | Ba3 | Ba3 |

Operational Risk | 72 | 60 |

Market Risk | 48 | 84 |

Technical Analysis | 62 | 67 |

Fundamental Analysis | 84 | 60 |

Risk Unsystematic | 63 | 42 |

### Prediction Confidence Score

## References

- Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
- Dimakopoulou M, Athey S, Imbens G. 2017. Estimation considerations in contextual bandits. arXiv:1711.07077 [stat.ML]
- A. Eck, L. Soh, S. Devlin, and D. Kudenko. Potential-based reward shaping for finite horizon online POMDP planning. Autonomous Agents and Multi-Agent Systems, 30(3):403–445, 2016
- Athey S, Mobius MM, Pál J. 2017c. The impact of aggregators on internet news consumption. Unpublished manuscript, Grad. School Bus., Stanford Univ., Stanford, CA
- Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]
- A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
- Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press

## Frequently Asked Questions

Q: What is the prediction methodology for LON:ALFA stock?A: LON:ALFA stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Polynomial Regression

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

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

Q: Is ALFA FINANCIAL SOFTWARE HOLDINGS PLC stock a good investment?

A: The consensus rating for ALFA FINANCIAL SOFTWARE HOLDINGS PLC is Hold and assigned short-term Ba3 & long-term Ba3 forecasted stock rating.

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

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

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

A: The prediction period for LON:ALFA is (n+6 month)

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