Predicting the future price of financial assets has always been an important research topic in the field of quantitative finance. This paper attempts to use the latest artificial intelligence technologies to design and implement a framework for financial asset price prediction.** We evaluate News Corp (Class B) prediction models with Ensemble Learning (ML) and Logistic Regression ^{1,2,3,4} and conclude that the NWS 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 NWS stock.**

**NWS, News Corp (Class B), stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Game Theory
- Trading Interaction
- Fundemental Analysis with Algorithmic Trading

## NWS Target Price Prediction Modeling Methodology

In recent years there has been a significant growth of interest in the incorporation of historical series of variables related to stock prediction into mathematical models or computational algorithms in order to generate predictions or indications about expected price movements. We consider News Corp (Class B) Stock Decision Process with Logistic Regression where A is the set of discrete actions of NWS 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(Logistic 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(Ensemble Learning (ML)) X S(n):→ (n+16 weeks) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of NWS 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?

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

**Sample Set:**Neural Network

**Stock/Index:**NWS News Corp (Class B)

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

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

News Corp (Class B) assigned short-term B1 & long-term B2 forecasted stock rating.** We evaluate the prediction models Ensemble Learning (ML) with Logistic Regression ^{1,2,3,4} and conclude that the NWS 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 NWS stock.**

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

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

Outlook* | B1 | B2 |

Operational Risk | 87 | 75 |

Market Risk | 47 | 32 |

Technical Analysis | 84 | 44 |

Fundamental Analysis | 56 | 58 |

Risk Unsystematic | 33 | 37 |

### Prediction Confidence Score

## References

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- Breusch, T. S. A. R. Pagan (1979), "A simple test for heteroskedasticity and random coefficient variation," Econometrica, 47, 1287–1294.
- Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
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- J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
- S. Devlin, L. Yliniemi, D. Kudenko, and K. Tumer. Potential-based difference rewards for multiagent reinforcement learning. In Proceedings of the Thirteenth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2014

## Frequently Asked Questions

Q: What is the prediction methodology for NWS stock?A: NWS stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Logistic Regression

Q: Is NWS stock a buy or sell?

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

Q: Is News Corp (Class B) stock a good investment?

A: The consensus rating for News Corp (Class B) is Hold and assigned short-term B1 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of NWS stock?

A: The consensus rating for NWS is Hold.

Q: What is the prediction period for NWS stock?

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

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