Stocks are possibly the most popular financial instrument invented for building wealth and are the centerpiece of any investment portfolio. The advances in trading technology has opened up the markets so that nowadays nearly anybody can own stocks. From last few decades, there seen explosive increase in the average person's interest for stock market. In a financially explosive market, as the stock market, it is important to have a very accurate prediction of a future trend. Because of the financial crisis and recording profits, it is compulsory to have a secure prediction of the values of the stocks. Predicting a non-linear signal requires progressive algorithms of machine learning with help of Artificial Intelligence (AI).** We evaluate Jakarta Stock Exchange Composite Index prediction models with Deductive Inference (ML) and Multiple Regression ^{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+6 month) period: The dominant strategy among neural network is to Buy 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

- Should I buy stocks now or wait amid such uncertainty?
- How do you know when a stock will go up or down?
- Which neural network is best for prediction?

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

Several intelligent data mining approaches, including neural networks, have been widely employed by academics during the last decade. In today's rapidly evolving economy, stock market data prediction and analysis play a significant role. Several non-linear models like neural network, generalized autoregressive conditional heteroskedasticity (GARCH) and autoregressive conditional heteroscedasticity (ARCH) as well as linear models like Auto- Regressive Integrated Moving Average (ARIMA), Moving Average (MA) and Auto Regressive (AR) may be used for stock forecasting. We consider Jakarta Stock Exchange Composite Index Stock Decision Process with Multiple Regression 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(Multiple 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(Deductive Inference (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 Jakarta Stock Exchange Composite Index 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?

## Jakarta Stock Exchange Composite Index Stock Forecast (Buy or Sell) for (n+6 month)

**Sample Set:**Neural Network

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

**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 Buy 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 B1 & long-term B1 forecasted stock rating.** We evaluate the prediction models Deductive Inference (ML) with Multiple Regression ^{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+6 month) period: The dominant strategy among neural network is to Buy 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* | B1 | B1 |

Operational Risk | 51 | 44 |

Market Risk | 36 | 72 |

Technical Analysis | 66 | 42 |

Fundamental Analysis | 80 | 65 |

Risk Unsystematic | 74 | 72 |

### Prediction Confidence Score

## References

- Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
- Clements, M. P. D. F. Hendry (1997), "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, 13, 341–355.
- Scholkopf B, Smola AJ. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press
- Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
- V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001
- Challen, D. W. A. J. Hagger (1983), Macroeconomic Systems: Construction, Validation and Applications. New York: St. Martin's Press.
- Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.

## 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 Deductive Inference (ML) and Multiple Regression

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

A: The dominant strategy among neural network is to Buy 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 Buy and assigned short-term B1 & long-term B1 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 Buy.

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+6 month)

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