URI Stock Price Prediction

United Rentals Research Report

Summary

Recently, a lot of interesting work has been done in the area of applying Machine Learning Algorithms for analyzing price patterns and predicting stock prices and index changes. Most stock traders nowadays depend on Intelligent Trading Systems which help them in predicting prices based on various situations and conditions, thereby helping them in making instantaneous investment decisions. We evaluate United Rentals prediction models with Transductive Learning (ML) and Polynomial Regression1,2,3,4 and conclude that the URI 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 Hold URI stock.

Key Points

  1. Reaction Function
  2. How do you know when a stock will go up or down?
  3. Decision Making

URI Target Price Prediction Modeling Methodology

We consider United Rentals Stock Decision Process with Transductive Learning (ML) 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(Polynomial Regression)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Transductive Learning (ML)) X S(n):→ (n+6 month) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of URI stock

j:Nash equilibria (Neural Network)

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+6 month)

Sample Set: Neural Network
Stock/Index: URI United Rentals
Time series to forecast n: 19 Nov 2022 for (n+6 month)

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

Adjusted IFRS* Prediction Methods for United Rentals

  1. The significance of a change in the credit risk since initial recognition depends on the risk of a default occurring as at initial recognition. Thus, a given change, in absolute terms, in the risk of a default occurring will be more significant for a financial instrument with a lower initial risk of a default occurring compared to a financial instrument with a higher initial risk of a default occurring.
  2. An entity that first applies these amendments after it first applies this Standard shall apply paragraphs 7.2.32–7.2.34. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).
  3. If a call option right retained by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at fair value, the asset continues to be measured at its fair value. The associated liability is measured at (i) the option exercise price less the time value of the option if the option is in or at the money, or (ii) the fair value of the transferred asset less the time value of the option if the option is out of the money. The adjustment to the measurement of the associated liability ensures that the net carrying amount of the asset and the associated liability is the fair value of the call option right. For example, if the fair value of the underlying asset is CU80, the option exercise price is CU95 and the time value of the option is CU5, the carrying amount of the associated liability is CU75 (CU80 – CU5) and the carrying amount of the transferred asset is CU80 (ie its fair value)
  4. A layer component that includes a prepayment option is not eligible to be designated as a hedged item in a fair value hedge if the prepayment option's fair value is affected by changes in the hedged risk, unless the designated layer includes the effect of the related prepayment option when determining the change in the fair value of the hedged item.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

United Rentals assigned short-term Ba3 & long-term B3 forecasted stock rating. We evaluate the prediction models Transductive Learning (ML) with Polynomial Regression1,2,3,4 and conclude that the URI 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 Hold URI stock.

Financial State Forecast for URI United Rentals Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3B3
Operational Risk 4563
Market Risk7045
Technical Analysis5061
Fundamental Analysis8630
Risk Unsystematic7430

Prediction Confidence Score

Trust metric by Neural Network: 84 out of 100 with 693 signals.

References

  1. J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
  2. R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.
  3. Dimakopoulou M, Athey S, Imbens G. 2017. Estimation considerations in contextual bandits. arXiv:1711.07077 [stat.ML]
  4. Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press
  5. Athey S, Blei D, Donnelly R, Ruiz F. 2017b. Counterfactual inference for consumer choice across many prod- uct categories. AEA Pap. Proc. 108:64–67
  6. M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
  7. R. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1057–1063, 2000
Frequently Asked QuestionsQ: What is the prediction methodology for URI stock?
A: URI stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and Polynomial Regression
Q: Is URI stock a buy or sell?
A: The dominant strategy among neural network is to Hold URI Stock.
Q: Is United Rentals stock a good investment?
A: The consensus rating for United Rentals is Hold and assigned short-term Ba3 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of URI stock?
A: The consensus rating for URI is Hold.
Q: What is the prediction period for URI stock?
A: The prediction period for URI is (n+6 month)

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