Impact of many factors on the stock prices makes the stock prediction a difficult and highly complicated task. In this paper, machine learning techniques have been applied for the stock price prediction in order to overcome such difficulties. In the implemented work, five models have been developed and their performances are compared in predicting the stock market trends.** We evaluate Nike prediction models with Supervised Machine Learning (ML) and Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the NKE stock is predictable in the short/long term. **

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold NKE stock.**

**NKE, Nike, 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 know when a stock will go up or down?
- Understanding Buy, Sell, and Hold Ratings
- How do you know when a stock will go up or down?

## NKE Target Price Prediction Modeling Methodology

The prediction of a stock market direction may serve as an early recommendation system for short-term investors and as an early financial distress warning system for long-term shareholders. We consider Nike Stock Decision Process with Wilcoxon Sign-Rank Test where A is the set of discrete actions of NKE 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(Wilcoxon Sign-Rank Test)

^{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(Supervised Machine Learning (ML)) X S(n):→ (n+8 weeks) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of NKE 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?

## NKE Stock Forecast (Buy or Sell) for (n+8 weeks)

**Sample Set:**Neural Network

**Stock/Index:**NKE Nike

**Time series to forecast n: 24 Sep 2022**for (n+8 weeks)

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold NKE 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

Nike assigned short-term Baa2 & long-term B2 forecasted stock rating.** We evaluate the prediction models Supervised Machine Learning (ML) with Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the NKE stock is predictable in the short/long term.**

**According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold NKE stock.**

### Financial State Forecast for NKE Stock Options & Futures

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

Outlook* | Baa2 | B2 |

Operational Risk | 79 | 36 |

Market Risk | 57 | 38 |

Technical Analysis | 66 | 90 |

Fundamental Analysis | 80 | 56 |

Risk Unsystematic | 80 | 42 |

### Prediction Confidence Score

## References

- Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
- Hastie T, Tibshirani R, Tibshirani RJ. 2017. Extended comparisons of best subset selection, forward stepwise selection, and the lasso. arXiv:1707.08692 [stat.ME]
- M. Babes, E. M. de Cote, and M. L. Littman. Social reward shaping in the prisoner's dilemma. In 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 3, pages 1389–1392, 2008.
- Harris ZS. 1954. Distributional structure. Word 10:146–62
- Bierens HJ. 1987. Kernel estimators of regression functions. In Advances in Econometrics: Fifth World Congress, Vol. 1, ed. TF Bewley, pp. 99–144. Cambridge, UK: Cambridge Univ. Press
- Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
- Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]

## Frequently Asked Questions

Q: What is the prediction methodology for NKE stock?A: NKE stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Wilcoxon Sign-Rank Test

Q: Is NKE stock a buy or sell?

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

Q: Is Nike stock a good investment?

A: The consensus rating for Nike is Hold and assigned short-term Baa2 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of NKE stock?

A: The consensus rating for NKE is Hold.

Q: What is the prediction period for NKE stock?

A: The prediction period for NKE is (n+8 weeks)

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