## Abstract

**We evaluate Range Resources prediction models with Ensemble Learning (ML) and Stepwise Regression ^{1,2,3,4} and conclude that the RRC stock is predictable in the short/long term. **

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy RRC stock.**

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

*Keywords:*## Key Points

- Why do we need predictive models?
- Buy, Sell and Hold Signals
- How do you decide buy or sell a stock?

## RRC Target Price Prediction Modeling Methodology

We consider Range Resources Stock Decision Process with Stepwise Regression where A is the set of discrete actions of RRC 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(Ensemble Learning (ML)) X S(n):→ (n+6 month) $\overrightarrow{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of RRC 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?

## RRC Stock Forecast (Buy or Sell) for (n+6 month)

**Sample Set:**Neural Network

**Stock/Index:**RRC Range Resources

**Time series to forecast n: 04 Sep 2022**for (n+6 month)

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy RRC 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

Range Resources assigned short-term B1 & long-term B1 forecasted stock rating.** We evaluate the prediction models Ensemble Learning (ML) with Stepwise Regression ^{1,2,3,4} and conclude that the RRC stock is predictable in the short/long term.**

**According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy RRC stock.**

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

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

Outlook* | B1 | B1 |

Operational Risk | 81 | 73 |

Market Risk | 71 | 59 |

Technical Analysis | 33 | 41 |

Fundamental Analysis | 65 | 70 |

Risk Unsystematic | 50 | 46 |

### Prediction Confidence Score

## References

- 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.
- H. Khalil and J. Grizzle. Nonlinear systems, volume 3. Prentice hall Upper Saddle River, 2002.
- Scholkopf B, Smola AJ. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press
- Wan M, Wang D, Goldman M, Taddy M, Rao J, et al. 2017. Modeling consumer preferences and price sensitiv- ities from large-scale grocery shopping transaction logs. In Proceedings of the 26th International Conference on the World Wide Web, pp. 1103–12. New York: ACM
- F. A. Oliehoek, M. T. J. Spaan, and N. A. Vlassis. Optimal and approximate q-value functions for decentralized pomdps. J. Artif. Intell. Res. (JAIR), 32:289–353, 2008
- M. Benaim, J. Hofbauer, and S. Sorin. Stochastic approximations and differential inclusions, Part II: Appli- cations. Mathematics of Operations Research, 31(4):673–695, 2006
- Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221

## Frequently Asked Questions

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

Q: Is RRC stock a buy or sell?

A: The dominant strategy among neural network is to Buy RRC Stock.

Q: Is Range Resources stock a good investment?

A: The consensus rating for Range Resources is Buy and assigned short-term B1 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of RRC stock?

A: The consensus rating for RRC is Buy.

Q: What is the prediction period for RRC stock?

A: The prediction period for RRC is (n+6 month)