Modelling A.I. in Economics

GUT^C Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares

Outlook: Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 31 Jan 2023 for (n+4 weeks)
Methodology : Modular Neural Network (DNN Layer)

Abstract

Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares prediction model is evaluated with Modular Neural Network (DNN Layer) and Lasso Regression1,2,3,4 and it is concluded that the GUT^C stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Hold

Key Points

  1. Trust metric by Neural Network
  2. What is a prediction confidence?
  3. What are buy sell or hold recommendations?

GUT^C Target Price Prediction Modeling Methodology

We consider Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of GUT^C 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(Lasso 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 (DNN Layer)) X S(n):→ (n+4 weeks) R = r 1 r 2 r 3

n:Time series to forecast

p:Price signals of GUT^C 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?

GUT^C Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: GUT^C Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares
Time series to forecast n: 31 Jan 2023 for (n+4 weeks)

According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Hold

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%

IFRS Reconciliation Adjustments for Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares

  1. 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.
  2. Measurement of a financial asset or financial liability and classification of recognised changes in its value are determined by the item's classification and whether the item is part of a designated hedging relationship. Those requirements can create a measurement or recognition inconsistency (sometimes referred to as an 'accounting mismatch') when, for example, in the absence of designation as at fair value through profit or loss, a financial asset would be classified as subsequently measured at fair value through profit or loss and a liability the entity considers related would be subsequently measured at amortised cost (with changes in fair value not recognised). In such circumstances, an entity may conclude that its financial statements would provide more relevant information if both the asset and the liability were measured as at fair value through profit or loss.
  3. At the date of initial application, an entity is permitted to make the designation in paragraph 2.5 for contracts that already exist on the date but only if it designates all similar contracts. The change in the net assets resulting from such designations shall be recognised in retained earnings at the date of initial application.
  4. If a put option obligation written by an entity or call option right held by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at amortised cost, the associated liability is measured at its cost (ie the consideration received) adjusted for the amortisation of any difference between that cost and the gross carrying amount of the transferred asset at the expiration date of the option. For example, assume that the gross carrying amount of the asset on the date of the transfer is CU98 and that the consideration received is CU95. The gross carrying amount of the asset on the option exercise date will be CU100. The initial carrying amount of the associated liability is CU95 and the difference between CU95 and CU100 is recognised in profit or loss using the effective interest method. If the option is exercised, any difference between the carrying amount of the associated liability and the exercise price is recognised in profit or loss.

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

Conclusions

Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares prediction model is evaluated with Modular Neural Network (DNN Layer) and Lasso Regression1,2,3,4 and it is concluded that the GUT^C stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Hold

GUT^C Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBa2Baa2
Balance SheetBa1Ba3
Leverage RatiosCaa2Ba1
Cash FlowBa1B1
Rates of Return and ProfitabilityB1C

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?

Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 874 signals.

References

  1. Mazumder R, Hastie T, Tibshirani R. 2010. Spectral regularization algorithms for learning large incomplete matrices. J. Mach. Learn. Res. 11:2287–322
  2. Künzel S, Sekhon J, Bickel P, Yu B. 2017. Meta-learners for estimating heterogeneous treatment effects using machine learning. arXiv:1706.03461 [math.ST]
  3. Mnih A, Kavukcuoglu K. 2013. Learning word embeddings efficiently with noise-contrastive estimation. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 2265–73. San Diego, CA: Neural Inf. Process. Syst. Found.
  4. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Trading Signals (WTS Stock Forecast). AC Investment Research Journal, 101(3).
  5. Barrett, C. B. (1997), "Heteroscedastic price forecasting for food security management in developing countries," Oxford Development Studies, 25, 225–236.
  6. Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
  7. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Can neural networks predict stock market?(ATVI Stock Forecast). AC Investment Research Journal, 101(3).
Frequently Asked QuestionsQ: What is the prediction methodology for GUT^C stock?
A: GUT^C stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Lasso Regression
Q: Is GUT^C stock a buy or sell?
A: The dominant strategy among neural network is to Hold GUT^C Stock.
Q: Is Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares stock a good investment?
A: The consensus rating for Gabelli Utility Trust (The) 5.375% Series C Cumulative Preferred Shares is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of GUT^C stock?
A: The consensus rating for GUT^C is Hold.
Q: What is the prediction period for GUT^C stock?
A: The prediction period for GUT^C is (n+4 weeks)

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