## Abstract

**We evaluate SMI Index prediction models with Running Moving Average (RMA) and Stepwise Regression ^{1,2,3,4} and conclude that the SMI 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 SMI Index stock.**

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

*Keywords:*## Key Points

- Short/Long Term Stocks
- How do you decide buy or sell a stock?
- How do you pick a stock?

## SMI Index Target Price Prediction Modeling Methodology

We consider SMI Index Stock Decision Process with Stepwise Regression where A is the set of discrete actions of SMI 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(Stepwise 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(Running Moving Average (RMA)) X S(n):→ (n+16 weeks) $\sum _{i=1}^{n}\left({a}_{i}\right)$

n:Time series to forecast

p:Price signals of SMI 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?

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

**Sample Set:**Neural Network

**Stock/Index:**SMI Index SMI Index

**Time series to forecast n: 01 Sep 2022**for (n+16 weeks)

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

SMI Index assigned short-term B2 & long-term Ba3 forecasted stock rating.** We evaluate the prediction models Running Moving Average (RMA) with Stepwise Regression ^{1,2,3,4} and conclude that the SMI 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 SMI Index stock.**

### Financial State Forecast for SMI Index Stock Options & Futures

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

Outlook* | B2 | Ba3 |

Operational Risk | 77 | 51 |

Market Risk | 50 | 52 |

Technical Analysis | 76 | 74 |

Fundamental Analysis | 38 | 65 |

Risk Unsystematic | 46 | 80 |

### Prediction Confidence Score

## References

- Athey S, Imbens G. 2016. Recursive partitioning for heterogeneous causal effects. PNAS 113:7353–60
- Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
- M. Colby, T. Duchow-Pressley, J. J. Chung, and K. Tumer. Local approximation of difference evaluation functions. In Proceedings of the Fifteenth International Joint Conference on Autonomous Agents and Multiagent Systems, Singapore, May 2016
- Andrews, D. W. K. W. Ploberger (1994), "Optimal tests when a nuisance parameter is present only under the alternative," Econometrica, 62, 1383–1414.
- Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
- S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs, NJ, 3nd edition, 2010
- Dudik M, Langford J, Li L. 2011. Doubly robust policy evaluation and learning. In Proceedings of the 28th International Conference on Machine Learning, pp. 1097–104. La Jolla, CA: Int. Mach. Learn. Soc.

## Frequently Asked Questions

Q: What is the prediction methodology for SMI Index stock?A: SMI Index stock prediction methodology: We evaluate the prediction models Running Moving Average (RMA) and Stepwise Regression

Q: Is SMI Index stock a buy or sell?

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

Q: Is SMI Index stock a good investment?

A: The consensus rating for SMI Index is Hold and assigned short-term B2 & long-term Ba3 forecasted stock rating.

Q: What is the consensus rating of SMI Index stock?

A: The consensus rating for SMI Index is Hold.

Q: What is the prediction period for SMI Index stock?

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

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