Modelling A.I. in Economics

AMSC American Superconductor Corporation Common Stock

Outlook: American Superconductor Corporation Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 14 Feb 2023 for (n+1 year)
Methodology : Modular Neural Network (Market Direction Analysis)

Abstract

American Superconductor Corporation Common Stock prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Pearson Correlation1,2,3,4 and it is concluded that the AMSC stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

Key Points

  1. What are the most successful trading algorithms?
  2. What are buy sell or hold recommendations?
  3. How do predictive algorithms actually work?

AMSC Target Price Prediction Modeling Methodology

We consider American Superconductor Corporation Common Stock Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of AMSC 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(Pearson 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 (Market Direction Analysis)) X S(n):→ (n+1 year) i = 1 n s i

n:Time series to forecast

p:Price signals of AMSC 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?

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

Sample Set: Neural Network
Stock/Index: AMSC American Superconductor Corporation Common Stock
Time series to forecast n: 14 Feb 2023 for (n+1 year)

According to price forecasts for (n+1 year) 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 American Superconductor Corporation Common Stock

  1. If a component of the cash flows of a financial or a non-financial item is designated as the hedged item, that component must be less than or equal to the total cash flows of the entire item. However, all of the cash flows of the entire item may be designated as the hedged item and hedged for only one particular risk (for example, only for those changes that are attributable to changes in LIBOR or a benchmark commodity price).
  2. If, at the date of initial application, determining whether there has been a significant increase in credit risk since initial recognition would require undue cost or effort, an entity shall recognise a loss allowance at an amount equal to lifetime expected credit losses at each reporting date until that financial instrument is derecognised (unless that financial instrument is low credit risk at a reporting date, in which case paragraph 7.2.19(a) applies).
  3. Time value of money is the element of interest that provides consideration for only the passage of time. That is, the time value of money element does not provide consideration for other risks or costs associated with holding the financial asset. In order to assess whether the element provides consideration for only the passage of time, an entity applies judgement and considers relevant factors such as the currency in which the financial asset is denominated and the period for which the interest rate is set.
  4. At the date of initial application, an entity shall use reasonable and supportable information that is available without undue cost or effort to determine the credit risk at the date that a financial instrument was initially recognised (or for loan commitments and financial guarantee contracts at the date that the entity became a party to the irrevocable commitment in accordance with paragraph 5.5.6) and compare that to the credit risk at the date of initial application of this Standard.

*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

American Superconductor Corporation Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. American Superconductor Corporation Common Stock prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Pearson Correlation1,2,3,4 and it is concluded that the AMSC stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

AMSC American Superconductor Corporation Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2Baa2
Balance SheetBaa2C
Leverage RatiosCBaa2
Cash FlowB3Ba1
Rates of Return and ProfitabilityCBa3

*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: 80 out of 100 with 658 signals.

References

  1. Breiman L. 2001b. Statistical modeling: the two cultures (with comments and a rejoinder by the author). Stat. Sci. 16:199–231
  2. L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
  3. Bertsimas D, King A, Mazumder R. 2016. Best subset selection via a modern optimization lens. Ann. Stat. 44:813–52
  4. Banerjee, A., J. J. Dolado, J. W. Galbraith, D. F. Hendry (1993), Co-integration, Error-correction, and the Econometric Analysis of Non-stationary Data. Oxford: Oxford University Press.
  5. Bierens HJ. 1987. Kernel estimators of regression functions. In Advances in Econometrics: Fifth World Congress, Vol. 1, ed. TF Bewley, pp. 99–144. Cambridge, UK: Cambridge Univ. Press
  6. A. Tamar, D. Di Castro, and S. Mannor. Policy gradients with variance related risk criteria. In Proceedings of the Twenty-Ninth International Conference on Machine Learning, pages 387–396, 2012.
  7. C. Szepesvári. Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2010
Frequently Asked QuestionsQ: What is the prediction methodology for AMSC stock?
A: AMSC stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Pearson Correlation
Q: Is AMSC stock a buy or sell?
A: The dominant strategy among neural network is to Hold AMSC Stock.
Q: Is American Superconductor Corporation Common Stock stock a good investment?
A: The consensus rating for American Superconductor Corporation Common Stock is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of AMSC stock?
A: The consensus rating for AMSC is Hold.
Q: What is the prediction period for AMSC stock?
A: The prediction period for AMSC is (n+1 year)

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