Modelling A.I. in Economics

WKSPW Worksport Ltd. Warrant

Outlook: Worksport Ltd. Warrant is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 29 Mar 2023 for (n+3 month)
Methodology : Active Learning (ML)

Abstract

Worksport Ltd. Warrant prediction model is evaluated with Active Learning (ML) and Factor1,2,3,4 and it is concluded that the WKSPW stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

Key Points

  1. Market Risk
  2. Trust metric by Neural Network
  3. What is statistical models in machine learning?

WKSPW Target Price Prediction Modeling Methodology

We consider Worksport Ltd. Warrant Decision Process with Active Learning (ML) where A is the set of discrete actions of WKSPW 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(Active Learning (ML)) X S(n):→ (n+3 month) r s rs

n:Time series to forecast

p:Price signals of WKSPW 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?

WKSPW Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: WKSPW Worksport Ltd. Warrant
Time series to forecast n: 29 Mar 2023 for (n+3 month)

According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

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 Worksport Ltd. Warrant

  1. When applying the effective interest method, an entity generally amortises any fees, points paid or received, transaction costs and other premiums or discounts that are included in the calculation of the effective interest rate over the expected life of the financial instrument. However, a shorter period is used if this is the period to which the fees, points paid or received, transaction costs, premiums or discounts relate. This will be the case when the variable to which the fees, points paid or received, transaction costs, premiums or discounts relate is repriced to market rates before the expected maturity of the financial instrument. In such a case, the appropriate amortisation period is the period to the next such repricing date. For example, if a premium or discount on a floating-rate financial instrument reflects the interest that has accrued on that financial instrument since the interest was last paid, or changes in the market rates since the floating interest rate was reset to the market rates, it will be amortised to the next date when the floating interest is reset to market rates. This is because the premium or discount relates to the period to the next interest reset date because, at that date, the variable to which the premium or discount relates (ie interest rates) is reset to the market rates. If, however, the premium or discount results from a change in the credit spread over the floating rate specified in the financial instrument, or other variables that are not reset to the market rates, it is amortised over the expected life of the financial instrument.
  2. There are two types of components of nominal amounts that can be designated as the hedged item in a hedging relationship: a component that is a proportion of an entire item or a layer component. The type of component changes the accounting outcome. An entity shall designate the component for accounting purposes consistently with its risk management objective.
  3. For hedges other than hedges of foreign currency risk, when an entity designates a non-derivative financial asset or a non-derivative financial liability measured at fair value through profit or loss as a hedging instrument, it may only designate the non-derivative financial instrument in its entirety or a proportion of it.
  4. To the extent that a transfer of a financial asset does not qualify for derecognition, the transferee does not recognise the transferred asset as its asset. The transferee derecognises the cash or other consideration paid and recognises a receivable from the transferor. If the transferor has both a right and an obligation to reacquire control of the entire transferred asset for a fixed amount (such as under a repurchase agreement), the transferee may measure its receivable at amortised cost if it meets the criteria in paragraph 4.1.2.

*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

Worksport Ltd. Warrant is assigned short-term Ba1 & long-term Ba1 estimated rating. Worksport Ltd. Warrant prediction model is evaluated with Active Learning (ML) and Factor1,2,3,4 and it is concluded that the WKSPW stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

WKSPW Worksport Ltd. Warrant Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB2Caa2
Balance SheetB1C
Leverage RatiosCCaa2
Cash FlowB3Baa2
Rates of Return and ProfitabilityB1Ba2

*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: 83 out of 100 with 860 signals.

References

  1. Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
  2. 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
  3. Swaminathan A, Joachims T. 2015. Batch learning from logged bandit feedback through counterfactual risk minimization. J. Mach. Learn. Res. 16:1731–55
  4. P. Artzner, F. Delbaen, J. Eber, and D. Heath. Coherent measures of risk. Journal of Mathematical Finance, 9(3):203–228, 1999
  5. S. J. Russell and A. Zimdars. Q-decomposition for reinforcement learning agents. In Machine Learning, Proceedings of the Twentieth International Conference (ICML 2003), August 21-24, 2003, Washington, DC, USA, pages 656–663, 2003.
  6. Blei DM, Lafferty JD. 2009. Topic models. In Text Mining: Classification, Clustering, and Applications, ed. A Srivastava, M Sahami, pp. 101–24. Boca Raton, FL: CRC Press
  7. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
Frequently Asked QuestionsQ: What is the prediction methodology for WKSPW stock?
A: WKSPW stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Factor
Q: Is WKSPW stock a buy or sell?
A: The dominant strategy among neural network is to Buy WKSPW Stock.
Q: Is Worksport Ltd. Warrant stock a good investment?
A: The consensus rating for Worksport Ltd. Warrant is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of WKSPW stock?
A: The consensus rating for WKSPW is Buy.
Q: What is the prediction period for WKSPW stock?
A: The prediction period for WKSPW is (n+3 month)



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