In modern financial market, the most crucial problem is to find essential approach to outline and visualizing the predictions in stock-markets to be made by individuals in order to attain maximum profit by investments. The stock market is a transformative, non-straight dynamical and complex system. Long term investment is one of the major investment decisions. Though, evaluating shares and calculating elementary values for companies for long term investment is difficult. In this paper we are going to present comparison of machine learning aided algorithms to evaluate the stock prices in the future to analyze market behaviour.** We evaluate Shanghai Composite Index prediction models with Modular Neural Network (Emotional Trigger/Responses Analysis) and Chi-Square ^{1,2,3,4} and conclude that the Shanghai Composite Index stock is predictable in the short/long term. **

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold Shanghai Composite Index stock.**

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

*Keywords:*## Key Points

- How do you decide buy or sell a stock?
- Can statistics predict the future?
- Trading Interaction

## Shanghai Composite Index Target Price Prediction Modeling Methodology

Stock index price prediction is prevalent in both academic and economic fields. The index price is hard to forecast due to its uncertain noise. With the development of computer science, neural networks are applied in kinds of industrial fields. In this paper, we introduce four different methods in machine learning including three typical machine learning models: Multilayer Perceptron (MLP), Long Short Term Memory (LSTM) and Convolutional Neural Network (CNN) and one attention-based neural network. We consider Shanghai Composite Index Stock Decision Process with Chi-Square where A is the set of discrete actions of Shanghai 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(Chi-Square)

^{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 (Emotional Trigger/Responses Analysis)) X S(n):→ (n+16 weeks) $\sum _{i=1}^{n}\left({a}_{i}\right)$

n:Time series to forecast

p:Price signals of Shanghai 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?

## Shanghai Composite Index Stock Forecast (Buy or Sell) for (n+16 weeks)

**Sample Set:**Neural Network

**Stock/Index:**Shanghai Composite Index Shanghai Composite Index

**Time series to forecast n: 19 Oct 2022**for (n+16 weeks)

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold Shanghai 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

Shanghai Composite Index assigned short-term B2 & long-term B1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) with Chi-Square ^{1,2,3,4} and conclude that the Shanghai Composite Index stock is predictable in the short/long term.**

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold Shanghai Composite Index stock.**

### Financial State Forecast for Shanghai Composite Index Stock Options & Futures

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

Outlook* | B2 | B1 |

Operational Risk | 76 | 39 |

Market Risk | 48 | 78 |

Technical Analysis | 50 | 72 |

Fundamental Analysis | 51 | 45 |

Risk Unsystematic | 58 | 56 |

### Prediction Confidence Score

## References

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- Bessler, D. A. T. Covey (1991), "Cointegration: Some results on U.S. cattle prices," Journal of Futures Markets, 11, 461–474.

## Frequently Asked Questions

Q: What is the prediction methodology for Shanghai Composite Index stock?A: Shanghai Composite Index stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Chi-Square

Q: Is Shanghai Composite Index stock a buy or sell?

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

Q: Is Shanghai Composite Index stock a good investment?

A: The consensus rating for Shanghai Composite Index is Hold and assigned short-term B2 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of Shanghai Composite Index stock?

A: The consensus rating for Shanghai Composite Index is Hold.

Q: What is the prediction period for Shanghai Composite Index stock?

A: The prediction period for Shanghai Composite Index is (n+16 weeks)