AC Investment Research Journal

INSG Inseego Corp. Common Stock Research Report

Outlook: Inseego Corp. 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+6 month)
Methodology : Inductive Learning (ML)

Abstract

Inseego Corp. Common Stock prediction model is evaluated with Inductive Learning (ML) and Factor1,2,3,4 and it is concluded that the INSG stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell

Key Points

  1. How do you know when a stock will go up or down?
  2. What is prediction in deep learning?
  3. Stock Rating

INSG Target Price Prediction Modeling Methodology

We consider Inseego Corp. Common Stock Decision Process with Inductive Learning (ML) where A is the set of discrete actions of INSG 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(Factor)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(Inductive Learning (ML)) X S(n):→ (n+6 month) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of INSG 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?

INSG Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: INSG Inseego Corp. Common Stock
Time series to forecast n: 20 Jan 2023 for (n+6 month)

According to price forecasts for (n+6 month) 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 Inseego Corp. Common Stock

  1. For the purpose of recognising foreign exchange gains and losses under IAS 21, a financial asset measured at fair value through other comprehensive income in accordance with paragraph 4.1.2A is treated as a monetary item. Accordingly, such a financial asset is treated as an asset measured at amortised cost in the foreign currency. Exchange differences on the amortised cost are recognised in profit or loss and other changes in the carrying amount are recognised in accordance with paragraph 5.7.10.
  2. The definition of a derivative in this Standard includes contracts that are settled gross by delivery of the underlying item (eg a forward contract to purchase a fixed rate debt instrument). An entity may have a contract to buy or sell a non-financial item that can be settled net in cash or another financial instrument or by exchanging financial instruments (eg a contract to buy or sell a commodity at a fixed price at a future date). Such a contract is within the scope of this Standard unless it was entered into and continues to be held for the purpose of delivery of a non-financial item in accordance with the entity's expected purchase, sale or usage requirements. However, this Standard applies to such contracts for an entity's expected purchase, sale or usage requirements if the entity makes a designation in accordance with paragraph 2.5 (see paragraphs 2.4–2.7).
  3. An entity shall assess at the inception of the hedging relationship, and on an ongoing basis, whether a hedging relationship meets the hedge effectiveness requirements. At a minimum, an entity shall perform the ongoing assessment at each reporting date or upon a significant change in the circumstances affecting the hedge effectiveness requirements, whichever comes first. The assessment relates to expectations about hedge effectiveness and is therefore only forward-looking.
  4. Interest Rate Benchmark Reform, which amended IFRS 9, IAS 39 and IFRS 7, issued in September 2019, added Section 6.8 and amended paragraph 7.2.26. An entity shall apply these amendments for annual periods beginning on or after 1 January 2020. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.

*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

Inseego Corp. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Inseego Corp. Common Stock prediction model is evaluated with Inductive Learning (ML) and Factor1,2,3,4 and it is concluded that the INSG stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell

INSG Inseego Corp. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB2Caa2
Balance SheetBa3Baa2
Leverage RatiosB3Baa2
Cash FlowB3Caa2
Rates of Return and ProfitabilityBa3B1

*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: 93 out of 100 with 563 signals.

References

  1. Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
  2. M. Benaim, J. Hofbauer, and S. Sorin. Stochastic approximations and differential inclusions, Part II: Appli- cations. Mathematics of Operations Research, 31(4):673–695, 2006
  3. Ashley, R. (1983), "On the usefulness of macroeconomic forecasts as inputs to forecasting models," Journal of Forecasting, 2, 211–223.
  4. Scott SL. 2010. A modern Bayesian look at the multi-armed bandit. Appl. Stoch. Models Bus. Ind. 26:639–58
  5. Bewley, R. M. Yang (1998), "On the size and power of system tests for cointegration," Review of Economics and Statistics, 80, 675–679.
  6. Akgiray, V. (1989), "Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts," Journal of Business, 62, 55–80.
  7. Zubizarreta JR. 2015. Stable weights that balance covariates for estimation with incomplete outcome data. J. Am. Stat. Assoc. 110:910–22
Frequently Asked QuestionsQ: What is the prediction methodology for INSG stock?
A: INSG stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Factor
Q: Is INSG stock a buy or sell?
A: The dominant strategy among neural network is to Sell INSG Stock.
Q: Is Inseego Corp. Common Stock stock a good investment?
A: The consensus rating for Inseego Corp. Common Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of INSG stock?
A: The consensus rating for INSG is Sell.
Q: What is the prediction period for INSG stock?
A: The prediction period for INSG is (n+6 month)

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