Modelling A.I. in Economics

TTP Tortoise Pipeline & Energy Fund Inc. Common Stock (Forecast)

Outlook: Tortoise Pipeline & Energy Fund Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 20 Jan 2023 for (n+8 weeks)
Methodology : Modular Neural Network (Financial Sentiment Analysis)

Abstract

Tortoise Pipeline & Energy Fund Inc. Common Stock prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Spearman Correlation1,2,3,4 and it is concluded that the TTP stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell

Key Points

  1. Is now good time to invest?
  2. Can stock prices be predicted?
  3. Is it better to buy and sell or hold?

TTP Target Price Prediction Modeling Methodology

We consider Tortoise Pipeline & Energy Fund Inc. Common Stock Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of TTP 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(Spearman Correlation)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 (Financial Sentiment Analysis)) X S(n):→ (n+8 weeks) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of TTP 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?

TTP Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: TTP Tortoise Pipeline & Energy Fund Inc. Common Stock
Time series to forecast n: 20 Jan 2023 for (n+8 weeks)

According to price forecasts for (n+8 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%

IFRS Reconciliation Adjustments for Tortoise Pipeline & Energy Fund Inc. Common Stock

  1. When measuring a loss allowance for a lease receivable, the cash flows used for determining the expected credit losses should be consistent with the cash flows used in measuring the lease receivable in accordance with IFRS 16 Leases.
  2. A single hedging instrument may be designated as a hedging instrument of more than one type of risk, provided that there is a specific designation of the hedging instrument and of the different risk positions as hedged items. Those hedged items can be in different hedging relationships.
  3. 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).
  4. To make that determination, an entity must assess whether it expects that the effects of changes in the liability's credit risk will be offset in profit or loss by a change in the fair value of another financial instrument measured at fair value through profit or loss. Such an expectation must be based on an economic relationship between the characteristics of the liability and the characteristics of the other financial instrument.

*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

Tortoise Pipeline & Energy Fund Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Tortoise Pipeline & Energy Fund Inc. Common Stock prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Spearman Correlation1,2,3,4 and it is concluded that the TTP stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell

TTP Tortoise Pipeline & Energy Fund Inc. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCCaa2
Balance SheetCaa2Baa2
Leverage RatiosCaa2B3
Cash FlowCaa2B2
Rates of Return and ProfitabilityCaa2B1

*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: 84 out of 100 with 850 signals.

References

  1. Bai J, Ng S. 2017. Principal components and regularized estimation of factor models. arXiv:1708.08137 [stat.ME]
  2. J. N. Foerster, Y. M. Assael, N. de Freitas, and S. Whiteson. Learning to communicate with deep multi-agent reinforcement learning. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 2137–2145, 2016.
  3. Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press
  4. Byron, R. P. O. Ashenfelter (1995), "Predicting the quality of an unborn grange," Economic Record, 71, 40–53.
  5. 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
  6. Semenova V, Goldman M, Chernozhukov V, Taddy M. 2018. Orthogonal ML for demand estimation: high dimensional causal inference in dynamic panels. arXiv:1712.09988 [stat.ML]
  7. A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
Frequently Asked QuestionsQ: What is the prediction methodology for TTP stock?
A: TTP stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Spearman Correlation
Q: Is TTP stock a buy or sell?
A: The dominant strategy among neural network is to Sell TTP Stock.
Q: Is Tortoise Pipeline & Energy Fund Inc. Common Stock stock a good investment?
A: The consensus rating for Tortoise Pipeline & Energy Fund Inc. Common Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of TTP stock?
A: The consensus rating for TTP is Sell.
Q: What is the prediction period for TTP stock?
A: The prediction period for TTP is (n+8 weeks)

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