Investors raise profit from stock market by maximising gains and minimising loses. The profit is difficult to raise because of the volatile nature of stock market prices. Predictive modelling allows investors to make informed decisions. ** We evaluate United Rentals prediction models with Statistical Inference (ML) and Independent T-Test ^{1,2,3,4} and conclude that the URI 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 HoldBuy URI stock.**

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

*Keywords:*## Key Points

- Is now good time to invest?
- Why do we need predictive models?
- What is prediction in deep learning?

## URI Target Price Prediction Modeling Methodology

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on a financial exchange. The successful prediction of a stock's future price will maximize investor's gains. This paper proposes a machine learning model to predict stock market price. We consider United Rentals Stock Decision Process with Independent T-Test where A is the set of discrete actions of URI 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(Independent T-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(Statistical Inference (ML)) X S(n):→ (n+16 weeks) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of URI 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?

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

**Sample Set:**Neural Network

**Stock/Index:**URI United Rentals

**Time series to forecast n: 18 Sep 2022**for (n+16 weeks)

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

United Rentals assigned short-term B3 & long-term B2 forecasted stock rating.** We evaluate the prediction models Statistical Inference (ML) with Independent T-Test ^{1,2,3,4} and conclude that the URI 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 HoldBuy URI stock.**

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

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

Outlook* | B3 | B2 |

Operational Risk | 36 | 80 |

Market Risk | 74 | 52 |

Technical Analysis | 76 | 37 |

Fundamental Analysis | 32 | 41 |

Risk Unsystematic | 32 | 56 |

### Prediction Confidence Score

## References

- Matzkin RL. 1994. Restrictions of economic theory in nonparametric methods. In Handbook of Econometrics, Vol. 4, ed. R Engle, D McFadden, pp. 2523–58. Amsterdam: Elsevier
- L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
- Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
- 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
- G. J. Laurent, L. Matignon, and N. L. Fort-Piat. The world of independent learners is not Markovian. Int. J. Know.-Based Intell. Eng. Syst., 15(1):55–64, 2011
- Clements, M. P. D. F. Hendry (1997), "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, 13, 341–355.
- N. B ̈auerle and J. Ott. Markov decision processes with average-value-at-risk criteria. Mathematical Methods of Operations Research, 74(3):361–379, 2011

## Frequently Asked Questions

Q: What is the prediction methodology for URI stock?A: URI stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Independent T-Test

Q: Is URI stock a buy or sell?

A: The dominant strategy among neural network is to HoldBuy URI Stock.

Q: Is United Rentals stock a good investment?

A: The consensus rating for United Rentals is HoldBuy and assigned short-term B3 & long-term B2 forecasted stock rating.

Q: What is the consensus rating of URI stock?

A: The consensus rating for URI is HoldBuy.

Q: What is the prediction period for URI stock?

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