Iridium Communications Stock Forecast

Outlook: Iridium Communications is assigned short-term Ba3 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-term Tactic1 :
Dominant Strategy :
Time series to forecast n: for Weeks2
ML Model Testing : Modular Neural Network (DNN Layer)
Hypothesis Testing : Pearson Correlation
Surveillance : Major exchange and OTC

1Short-term revised.

2Time series is updated based on short-term trends.


Key Points

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About Iridium Communications

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IRDM
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ML Model Testing

F(Pearson Correlation)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))3,4,5 X S(n):→ 3 Month i = 1 n r i

n:Time series to forecast

p:Price signals of Iridium Communications stock

j:Nash equilibria (Neural Network)

k:Dominated move of Iridium Communications stock holders

a:Best response for Iridium Communications target price

 

For further technical information as per how our model work we invite you to visit the article below: 

How do KappaSignal algorithms actually work?

Iridium Communications Stock Forecast (Buy or Sell) Strategic Interaction Table

Strategic Interaction Table Legend:

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%

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Rating Short-Term Long-Term Senior
OutlookBa3Ba3
Income StatementBa2Baa2
Balance SheetB2Ba2
Leverage RatiosCB3
Cash FlowBaa2Caa2
Rates of Return and ProfitabilityBaa2Baa2

*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?

References

  1. Bewley, R. M. Yang (1998), "On the size and power of system tests for cointegration," Review of Economics and Statistics, 80, 675–679.
  2. Athey S, Blei D, Donnelly R, Ruiz F. 2017b. Counterfactual inference for consumer choice across many prod- uct categories. AEA Pap. Proc. 108:64–67
  3. Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
  4. Athey S, Blei D, Donnelly R, Ruiz F. 2017b. Counterfactual inference for consumer choice across many prod- uct categories. AEA Pap. Proc. 108:64–67
  5. Lai TL, Robbins H. 1985. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22
  6. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Google's Stock Price Set to Soar in the Next 3 Months. AC Investment Research Journal, 220(44).
  7. Athey S, Bayati M, Doudchenko N, Imbens G, Khosravi K. 2017a. Matrix completion methods for causal panel data models. arXiv:1710.10251 [math.ST]

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