Modelling A.I. in Economics

NXP Nuveen Select Tax Free Income Portfolio Common Stock

Outlook: Nuveen Select Tax Free Income Portfolio Common Stock assigned short-term B1 & long-term Ba3 forecasted stock rating.
Dominant Strategy : Sell
Time series to forecast n: 13 Dec 2022 for (n+16 weeks)
Methodology : Modular Neural Network (CNN Layer)

Abstract

In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. (Chaigusin, S., Chirathamjaree, C. and Clayden, J., 2008, September. Soft computing in the forecasting of the stock exchange of Thailand (SET). In 2008 4th IEEE International Conference on Management of Innovation and Technology (pp. 1277-1281). IEEE.) We evaluate Nuveen Select Tax Free Income Portfolio Common Stock prediction models with Modular Neural Network (CNN Layer) and Multiple Regression1,2,3,4 and conclude that the NXP stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell

Key Points

  1. What is a prediction confidence?
  2. What are buy sell or hold recommendations?
  3. Stock Rating

NXP Target Price Prediction Modeling Methodology

We consider Nuveen Select Tax Free Income Portfolio Common Stock Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of NXP 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(Modular Neural Network (CNN Layer)) X S(n):→ (n+16 weeks) i = 1 n a i

n:Time series to forecast

p:Price signals of NXP 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?

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

Sample Set: Neural Network
Stock/Index: NXP Nuveen Select Tax Free Income Portfolio Common Stock
Time series to forecast n: 13 Dec 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell

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 (Grey to Black): *Technical Analysis%

Adjusted IFRS* Prediction Methods for Nuveen Select Tax Free Income Portfolio Common Stock

  1. Unless paragraph 6.8.8 applies, for a hedge of a non-contractually specified benchmark component of interest rate risk, an entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component shall be separately identifiable—only at the inception of the hedging relationship.
  2. When a group of items that constitute a net position is designated as a hedged item, an entity shall designate the overall group of items that includes the items that can make up the net position. An entity is not permitted to designate a non-specific abstract amount of a net position. For example, an entity has a group of firm sale commitments in nine months' time for FC100 and a group of firm purchase commitments in 18 months' time for FC120. The entity cannot designate an abstract amount of a net position up to FC20. Instead, it must designate a gross amount of purchases and a gross amount of sales that together give rise to the hedged net position. An entity shall designate gross positions that give rise to the net position so that the entity is able to comply with the requirements for the accounting for qualifying hedging relationships.
  3. 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.
  4. If, in applying paragraph 7.2.44, an entity reinstates a discontinued hedging relationship, the entity shall read references in paragraphs 6.9.11 and 6.9.12 to the date the alternative benchmark rate is designated as a noncontractually specified risk component for the first time as referring to the date of initial application of these amendments (ie the 24-month period for that alternative benchmark rate designated as a non-contractually specified risk component begins from the date of initial application of these amendments).

*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

Nuveen Select Tax Free Income Portfolio Common Stock assigned short-term B1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (CNN Layer) with Multiple Regression1,2,3,4 and conclude that the NXP stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Sell

Financial State Forecast for NXP Nuveen Select Tax Free Income Portfolio Common Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1Ba3
Operational Risk 5480
Market Risk5472
Technical Analysis8764
Fundamental Analysis3252
Risk Unsystematic6547

Prediction Confidence Score

Trust metric by Neural Network: 74 out of 100 with 866 signals.

References

  1. Farrell MH, Liang T, Misra S. 2018. Deep neural networks for estimation and inference: application to causal effects and other semiparametric estimands. arXiv:1809.09953 [econ.EM]
  2. Bengio Y, Schwenk H, Senécal JS, Morin F, Gauvain JL. 2006. Neural probabilistic language models. In Innovations in Machine Learning: Theory and Applications, ed. DE Holmes, pp. 137–86. Berlin: Springer
  3. S. Bhatnagar and K. Lakshmanan. An online actor-critic algorithm with function approximation for con- strained Markov decision processes. Journal of Optimization Theory and Applications, 153(3):688–708, 2012.
  4. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
  5. Bai J, Ng S. 2017. Principal components and regularized estimation of factor models. arXiv:1708.08137 [stat.ME]
  6. Mazumder R, Hastie T, Tibshirani R. 2010. Spectral regularization algorithms for learning large incomplete matrices. J. Mach. Learn. Res. 11:2287–322
  7. Bai J, Ng S. 2017. Principal components and regularized estimation of factor models. arXiv:1708.08137 [stat.ME]
Frequently Asked QuestionsQ: What is the prediction methodology for NXP stock?
A: NXP stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Multiple Regression
Q: Is NXP stock a buy or sell?
A: The dominant strategy among neural network is to Sell NXP Stock.
Q: Is Nuveen Select Tax Free Income Portfolio Common Stock stock a good investment?
A: The consensus rating for Nuveen Select Tax Free Income Portfolio Common Stock is Sell and assigned short-term B1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of NXP stock?
A: The consensus rating for NXP is Sell.
Q: What is the prediction period for NXP stock?
A: The prediction period for NXP is (n+16 weeks)

Premium

  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

Login
This project is licensed under the license; additional terms may apply.