Modelling A.I. in Economics

IMPPP Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares (Forecast)

Outlook: Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 14 May 2023 for (n+1 year)
Methodology : Modular Neural Network (Speculative Sentiment Analysis)

Abstract

Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and Multiple Regression1,2,3,4 and it is concluded that the IMPPP stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

Key Points

  1. Investment Risk
  2. What is the use of Markov decision process?
  3. Reaction Function

IMPPP Target Price Prediction Modeling Methodology

We consider Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares Decision Process with Modular Neural Network (Speculative Sentiment Analysis) where A is the set of discrete actions of IMPPP 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 (Speculative Sentiment Analysis)) X S(n):→ (n+1 year) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of IMPPP 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?

IMPPP Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: IMPPP Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares
Time series to forecast n: 14 May 2023 for (n+1 year)

According to price forecasts for (n+1 year) 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 Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares

  1. It would not be acceptable to designate only some of the financial assets and financial liabilities giving rise to the inconsistency as at fair value through profit or loss if to do so would not eliminate or significantly reduce the inconsistency and would therefore not result in more relevant information. However, it would be acceptable to designate only some of a number of similar financial assets or similar financial liabilities if doing so achieves a significant reduction (and possibly a greater reduction than other allowable designations) in the inconsistency. For example, assume an entity has a number of similar financial liabilities that sum to CU100 and a number of similar financial assets that sum to CU50 but are measured on a different basis. The entity may significantly reduce the measurement inconsistency by designating at initial recognition all of the assets but only some of the liabilities (for example, individual liabilities with a combined total of CU45) as at fair value through profit or loss. However, because designation as at fair value through profit or loss can be applied only to the whole of a financial instrument, the entity in this example must designate one or more liabilities in their entirety. It could not designate either a component of a liability (eg changes in value attributable to only one risk, such as changes in a benchmark interest rate) or a proportion (ie percentage) of a liability.
  2. Expected credit losses reflect an entity's own expectations of credit losses. However, when considering all reasonable and supportable information that is available without undue cost or effort in estimating expected credit losses, an entity should also consider observable market information about the credit risk of the particular financial instrument or similar financial instruments.
  3. An entity is not required to incorporate forecasts of future conditions over the entire expected life of a financial instrument. The degree of judgement that is required to estimate expected credit losses depends on the availability of detailed information. As the forecast horizon increases, the availability of detailed information decreases and the degree of judgement required to estimate expected credit losses increases. The estimate of expected credit losses does not require a detailed estimate for periods that are far in the future—for such periods, an entity may extrapolate projections from available, detailed information.
  4. It would not be acceptable to designate only some of the financial assets and financial liabilities giving rise to the inconsistency as at fair value through profit or loss if to do so would not eliminate or significantly reduce the inconsistency and would therefore not result in more relevant information. However, it would be acceptable to designate only some of a number of similar financial assets or similar financial liabilities if doing so achieves a significant reduction (and possibly a greater reduction than other allowable designations) in the inconsistency. For example, assume an entity has a number of similar financial liabilities that sum to CU100 and a number of similar financial assets that sum to CU50 but are measured on a different basis. The entity may significantly reduce the measurement inconsistency by designating at initial recognition all of the assets but only some of the liabilities (for example, individual liabilities with a combined total of CU45) as at fair value through profit or loss. However, because designation as at fair value through profit or loss can be applied only to the whole of a financial instrument, the entity in this example must designate one or more liabilities in their entirety. It could not designate either a component of a liability (eg changes in value attributable to only one risk, such as changes in a benchmark interest rate) or a proportion (ie percentage) of a liability.

*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

Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and Multiple Regression1,2,3,4 and it is concluded that the IMPPP stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

IMPPP Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2Baa2
Balance SheetBaa2Ba3
Leverage RatiosB2Caa2
Cash FlowBaa2Ba3
Rates of Return and ProfitabilityCB2

*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: 81 out of 100 with 555 signals.

References

  1. Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
  2. F. A. Oliehoek, M. T. J. Spaan, and N. A. Vlassis. Optimal and approximate q-value functions for decentralized pomdps. J. Artif. Intell. Res. (JAIR), 32:289–353, 2008
  3. R. Howard and J. Matheson. Risk sensitive Markov decision processes. Management Science, 18(7):356– 369, 1972
  4. R. Howard and J. Matheson. Risk sensitive Markov decision processes. Management Science, 18(7):356– 369, 1972
  5. O. Bardou, N. Frikha, and G. Pag`es. Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling. Monte Carlo Methods and Applications, 15(3):173–210, 2009.
  6. Swaminathan A, Joachims T. 2015. Batch learning from logged bandit feedback through counterfactual risk minimization. J. Mach. Learn. Res. 16:1731–55
  7. Firth JR. 1957. A synopsis of linguistic theory 1930–1955. In Studies in Linguistic Analysis (Special Volume of the Philological Society), ed. JR Firth, pp. 1–32. Oxford, UK: Blackwell
Frequently Asked QuestionsQ: What is the prediction methodology for IMPPP stock?
A: IMPPP stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Multiple Regression
Q: Is IMPPP stock a buy or sell?
A: The dominant strategy among neural network is to Sell IMPPP Stock.
Q: Is Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares stock a good investment?
A: The consensus rating for Imperial Petroleum Inc. 8.75% Series A Cumulative Redeemable Perpetual Preferred Shares is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of IMPPP stock?
A: The consensus rating for IMPPP is Sell.
Q: What is the prediction period for IMPPP stock?
A: The prediction period for IMPPP is (n+1 year)

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