Modelling A.I. in Economics

SOLO Electrameccanica Vehicles Corp. Ltd. Common Stock

Outlook: Electrameccanica Vehicles Corp. Ltd. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 23 Apr 2023 for (n+8 weeks)
Methodology : Modular Neural Network (News Feed Sentiment Analysis)

Abstract

Electrameccanica Vehicles Corp. Ltd. Common Stock prediction model is evaluated with Modular Neural Network (News Feed Sentiment Analysis) and Ridge Regression1,2,3,4 and it is concluded that the SOLO stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

Key Points

  1. How do predictive algorithms actually work?
  2. What is the use of Markov decision process?
  3. How do you pick a stock?

SOLO Target Price Prediction Modeling Methodology

We consider Electrameccanica Vehicles Corp. Ltd. Common Stock Decision Process with Modular Neural Network (News Feed Sentiment Analysis) where A is the set of discrete actions of SOLO 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(Ridge 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 (News Feed Sentiment Analysis)) X S(n):→ (n+8 weeks) e x rx

n:Time series to forecast

p:Price signals of SOLO 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?

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

Sample Set: Neural Network
Stock/Index: SOLO Electrameccanica Vehicles Corp. Ltd. Common Stock
Time series to forecast n: 23 Apr 2023 for (n+8 weeks)

According to price forecasts for (n+8 weeks) 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 Electrameccanica Vehicles Corp. Ltd. Common Stock

  1. 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).
  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. Compared to a business model whose objective is to hold financial assets to collect contractual cash flows, this business model will typically involve greater frequency and value of sales. This is because selling financial assets is integral to achieving the business model's objective instead of being only incidental to it. However, there is no threshold for the frequency or value of sales that must occur in this business model because both collecting contractual cash flows and selling financial assets are integral to achieving its objective.
  4. Sales that occur for other reasons, such as sales made to manage credit concentration risk (without an increase in the assets' credit risk), may also be consistent with a business model whose objective is to hold financial assets in order to collect contractual cash flows. In particular, such sales may be consistent with a business model whose objective is to hold financial assets in order to collect contractual cash flows if those sales are infrequent (even if significant in value) or insignificant in value both individually and in aggregate (even if frequent). If more than an infrequent number of such sales are made out of a portfolio and those sales are more than insignificant in value (either individually or in aggregate), the entity needs to assess whether and how such sales are consistent with an objective of collecting contractual cash flows. Whether a third party imposes the requirement to sell the financial assets, or that activity is at the entity's discretion, is not relevant to this assessment. An increase in the frequency or value of sales in a particular period is not necessarily inconsistent with an objective to hold financial assets in order to collect contractual cash flows, if an entity can explain the reasons for those sales and demonstrate why those sales do not reflect a change in the entity's business model. In addition, sales may be consistent with the objective of holding financial assets in order to collect contractual cash flows if the sales are made close to the maturity of the financial assets and the proceeds from the sales approximate the collection of the remaining contractual cash flows.

*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

Electrameccanica Vehicles Corp. Ltd. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Electrameccanica Vehicles Corp. Ltd. Common Stock prediction model is evaluated with Modular Neural Network (News Feed Sentiment Analysis) and Ridge Regression1,2,3,4 and it is concluded that the SOLO stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

SOLO Electrameccanica Vehicles Corp. Ltd. Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2Baa2
Balance SheetBaa2Caa2
Leverage RatiosCB2
Cash FlowCB3
Rates of Return and ProfitabilityCC

*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: 76 out of 100 with 581 signals.

References

  1. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market? (No. Stock Analysis). AC Investment Research.
  2. Matzkin RL. 2007. Nonparametric identification. In Handbook of Econometrics, Vol. 6B, ed. J Heckman, E Learner, pp. 5307–68. Amsterdam: Elsevier
  3. LeCun Y, Bengio Y, Hinton G. 2015. Deep learning. Nature 521:436–44
  4. Imbens GW, Rubin DB. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge, UK: Cambridge Univ. Press
  5. Bottou L. 1998. Online learning and stochastic approximations. In On-Line Learning in Neural Networks, ed. D Saad, pp. 9–42. New York: ACM
  6. Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
  7. M. L. Littman. Friend-or-foe q-learning in general-sum games. In Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001, pages 322–328, 2001
Frequently Asked QuestionsQ: What is the prediction methodology for SOLO stock?
A: SOLO stock prediction methodology: We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) and Ridge Regression
Q: Is SOLO stock a buy or sell?
A: The dominant strategy among neural network is to Hold SOLO Stock.
Q: Is Electrameccanica Vehicles Corp. Ltd. Common Stock stock a good investment?
A: The consensus rating for Electrameccanica Vehicles Corp. Ltd. Common Stock is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of SOLO stock?
A: The consensus rating for SOLO is Hold.
Q: What is the prediction period for SOLO stock?
A: The prediction period for SOLO is (n+8 weeks)



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