## Abstract

**We evaluate Crane prediction models with Modular Neural Network (Financial Sentiment Analysis) and Pearson Correlation ^{1,2,3,4} and conclude that the CR 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 CR stock.**

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

*Keywords:*## Key Points

- Game Theory
- How do you know when a stock will go up or down?
- How useful are statistical predictions?

## CR Target Price Prediction Modeling Methodology

We consider Crane Stock Decision Process with Pearson Correlation where A is the set of discrete actions of CR 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(Pearson Correlation)

^{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 (Financial Sentiment Analysis)) X S(n):→ (n+16 weeks) $\overrightarrow{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of CR 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?

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

**Sample Set:**Neural Network

**Stock/Index:**CR Crane

**Time series to forecast n: 08 Sep 2022**for (n+16 weeks)

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

Crane assigned short-term B2 & long-term B2 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) with Pearson Correlation ^{1,2,3,4} and conclude that the CR 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 CR stock.**

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

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

Outlook* | B2 | B2 |

Operational Risk | 35 | 67 |

Market Risk | 89 | 31 |

Technical Analysis | 56 | 59 |

Fundamental Analysis | 33 | 61 |

Risk Unsystematic | 57 | 37 |

### Prediction Confidence Score

## References

- S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
- Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
- J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
- S. Proper and K. Tumer. Modeling difference rewards for multiagent learning (extended abstract). In Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, June 2012
- V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001
- V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008
- Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]

## Frequently Asked Questions

Q: What is the prediction methodology for CR stock?A: CR stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Pearson Correlation

Q: Is CR stock a buy or sell?

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

Q: Is Crane stock a good investment?

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

Q: What is the consensus rating of CR stock?

A: The consensus rating for CR is Hold.

Q: What is the prediction period for CR stock?

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