Stock market is a promising financial investment that can generate great wealth. However, the volatile nature of the stock market makes it a very high risk investment. Thus, a lot of researchers have contributed their efforts to forecast the stock market pricing and average movement. Researchers have used various methods in computer science and economics in their quests to gain a piece of this volatile information and make great fortune out of the stock market investment. This paper investigates various techniques for the stock market prediction using artificial neural network (ANN).** We evaluate Jakarta Stock Exchange Composite Index prediction models with Modular Neural Network (Financial Sentiment Analysis) and Pearson Correlation ^{1,2,3,4} and conclude that the Jakarta Stock Exchange Composite Index stock is predictable in the short/long term. **

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold Jakarta Stock Exchange Composite Index stock.**

**Jakarta Stock Exchange Composite Index, Jakarta Stock Exchange Composite Index, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Dominated Move
- What is the use of Markov decision process?
- What is the best way to predict stock prices?

## Jakarta Stock Exchange Composite Index Target Price Prediction Modeling Methodology

Short - term price movements, contribute a considerable measure to the unpredictability of the securities exchanges. Accurately predicting the price fluctuations in stock market is a huge economical advantage. The aforementioned task is generally achieved by analyzing the company, this is called as fundamental analysis. Another method, which is undergoing a lot of research work recently, is to create a predictive algorithmic model using machine learning. To train machines to take trading decisions in such short - period of time, the latter method needs to be adopted. Deep Neural Networks, being the most exceptional innovation in Machine Learning, have been utilized to develop a short-term prediction model. We consider Jakarta Stock Exchange Composite Index Stock Decision Process with Pearson Correlation where A is the set of discrete actions of Jakarta Stock Exchange Composite Index 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(Pearson Correlation)

^{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 (Financial Sentiment Analysis)) X S(n):→ (n+4 weeks) $\sum _{i=1}^{n}\left({r}_{i}\right)$

n:Time series to forecast

p:Price signals of Jakarta Stock Exchange Composite Index stock

j:Nash equilibria

k:Dominated move

a:Best response for target price

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How do AC Investment Research machine learning (predictive) algorithms actually work?

## Jakarta Stock Exchange Composite Index Stock Forecast (Buy or Sell) for (n+4 weeks)

**Sample Set:**Neural Network

**Stock/Index:**Jakarta Stock Exchange Composite Index Jakarta Stock Exchange Composite Index

**Time series to forecast n: 18 Sep 2022**for (n+4 weeks)

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold Jakarta Stock Exchange Composite Index 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

Jakarta Stock Exchange Composite Index assigned short-term B3 & long-term B3 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) with Pearson Correlation ^{1,2,3,4} and conclude that the Jakarta Stock Exchange Composite Index stock is predictable in the short/long term.**

**According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold Jakarta Stock Exchange Composite Index stock.**

### Financial State Forecast for Jakarta Stock Exchange Composite Index Stock Options & Futures

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

Outlook* | B3 | B3 |

Operational Risk | 33 | 48 |

Market Risk | 51 | 33 |

Technical Analysis | 55 | 30 |

Fundamental Analysis | 36 | 84 |

Risk Unsystematic | 75 | 37 |

### Prediction Confidence Score

## References

- Breiman L. 2001b. Statistical modeling: the two cultures (with comments and a rejoinder by the author). Stat. Sci. 16:199–231
- Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
- Bottou L. 1998. Online learning and stochastic approximations. In On-Line Learning in Neural Networks, ed. D Saad, pp. 9–42. New York: ACM
- Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
- Holland PW. 1986. Statistics and causal inference. J. Am. Stat. Assoc. 81:945–60
- Y. Le Tallec. Robust, risk-sensitive, and data-driven control of Markov decision processes. PhD thesis, Massachusetts Institute of Technology, 2007.
- Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]

## Frequently Asked Questions

Q: What is the prediction methodology for Jakarta Stock Exchange Composite Index stock?A: Jakarta Stock Exchange Composite Index stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Pearson Correlation

Q: Is Jakarta Stock Exchange Composite Index stock a buy or sell?

A: The dominant strategy among neural network is to Hold Jakarta Stock Exchange Composite Index Stock.

Q: Is Jakarta Stock Exchange Composite Index stock a good investment?

A: The consensus rating for Jakarta Stock Exchange Composite Index is Hold and assigned short-term B3 & long-term B3 forecasted stock rating.

Q: What is the consensus rating of Jakarta Stock Exchange Composite Index stock?

A: The consensus rating for Jakarta Stock Exchange Composite Index is Hold.

Q: What is the prediction period for Jakarta Stock Exchange Composite Index stock?

A: The prediction period for Jakarta Stock Exchange Composite Index is (n+4 weeks)

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