Modelling A.I. in Economics

CW Curtiss-Wright Corporation Common Stock (Forecast)

Curtiss-Wright Corporation Common Stock Research Report

Summary

The research reported in the paper focuses on the stock market prediction problem, the main aim being the development of a methodology to forecast the stock closing price. The methodology is based on some novel variable selection methods and an analysis of neural network and support vector machines based prediction models. Also, a hybrid approach which combines the use of the variables derived from technical and fundamental analysis of stock market indicators in order to improve prediction results of the proposed approaches is reported in this paper. We evaluate Curtiss-Wright Corporation Common Stock prediction models with Transductive Learning (ML) and Multiple Regression1,2,3,4 and conclude that the CW 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 CW stock.

Key Points

  1. Prediction Modeling
  2. What is a prediction confidence?
  3. Probability Distribution

CW Target Price Prediction Modeling Methodology

We consider Curtiss-Wright Corporation Common Stock Stock Decision Process with Transductive Learning (ML) where A is the set of discrete actions of CW 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(Multiple 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 = r 1 r 2 r 3

n:Time series to forecast

p:Price signals of CW 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?

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

Sample Set: Neural Network
Stock/Index: CW Curtiss-Wright Corporation Common Stock
Time series to forecast n: 28 Nov 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold CW 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 Curtiss-Wright Corporation Common Stock

  1. There are two types of components of nominal amounts that can be designated as the hedged item in a hedging relationship: a component that is a proportion of an entire item or a layer component. The type of component changes the accounting outcome. An entity shall designate the component for accounting purposes consistently with its risk management objective.
  2. An entity may manage and evaluate the performance of a group of financial liabilities or financial assets and financial liabilities in such a way that measuring that group at fair value through profit or loss results in more relevant information. The focus in this instance is on the way the entity manages and evaluates performance, instead of on the nature of its financial instruments.
  3. However, depending on the nature of the financial instruments and the credit risk information available for particular groups of financial instruments, an entity may not be able to identify significant changes in credit risk for individual financial instruments before the financial instrument becomes past due. This may be the case for financial instruments such as retail loans for which there is little or no updated credit risk information that is routinely obtained and monitored on an individual instrument until a customer breaches the contractual terms. If changes in the credit risk for individual financial instruments are not captured before they become past due, a loss allowance based only on credit information at an individual financial instrument level would not faithfully represent the changes in credit risk since initial recognition.
  4. In some circumstances an entity does not have reasonable and supportable information that is available without undue cost or effort to measure lifetime expected credit losses on an individual instrument basis. In that case, lifetime expected credit losses shall be recognised on a collective basis that considers comprehensive credit risk information. This comprehensive credit risk information must incorporate not only past due information but also all relevant credit information, including forward-looking macroeconomic information, in order to approximate the result of recognising lifetime expected credit losses when there has been a significant increase in credit risk since initial recognition on an individual instrument level.

*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

Curtiss-Wright Corporation Common Stock assigned short-term Ba3 & long-term B1 forecasted stock rating. We evaluate the prediction models Transductive Learning (ML) with Multiple Regression1,2,3,4 and conclude that the CW 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 CW stock.

Financial State Forecast for CW Curtiss-Wright Corporation Common Stock Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3B1
Operational Risk 8650
Market Risk3888
Technical Analysis7530
Fundamental Analysis9062
Risk Unsystematic4263

Prediction Confidence Score

Trust metric by Neural Network: 84 out of 100 with 630 signals.

References

  1. D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
  2. Burkov A. 2019. The Hundred-Page Machine Learning Book. Quebec City, Can.: Andriy Burkov
  3. Hastie T, Tibshirani R, Wainwright M. 2015. Statistical Learning with Sparsity: The Lasso and Generalizations. New York: CRC Press
  4. Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
  5. Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]
  6. Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
  7. Abadie A, Diamond A, Hainmueller J. 2015. Comparative politics and the synthetic control method. Am. J. Political Sci. 59:495–510
Frequently Asked QuestionsQ: What is the prediction methodology for CW stock?
A: CW stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and Multiple Regression
Q: Is CW stock a buy or sell?
A: The dominant strategy among neural network is to Hold CW Stock.
Q: Is Curtiss-Wright Corporation Common Stock stock a good investment?
A: The consensus rating for Curtiss-Wright Corporation Common Stock is Hold and assigned short-term Ba3 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of CW stock?
A: The consensus rating for CW is Hold.
Q: What is the prediction period for CW stock?
A: The prediction period for CW is (n+6 month)

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