WKHS Workhorse Group Inc. Common Stock (Forecast)

Outlook: Workhorse Group Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 04 May 2023 for (n+16 weeks)
Methodology : Reinforcement Machine Learning (ML)

Abstract

Workhorse Group Inc. Common Stock prediction model is evaluated with Reinforcement Machine Learning (ML) and Independent T-Test^1,2,3,4 and it is concluded that the WKHS stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

Key Points

1. How do you know when a stock will go up or down?
2. What is a prediction confidence?
3. Stock Forecast Based On a Predictive Algorithm

WKHS Target Price Prediction Modeling Methodology

We consider Workhorse Group Inc. Common Stock Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of WKHS 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(Independent T-Test)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Reinforcement Machine Learning (ML)) X S(n):→ (n+16 weeks) $\begin{array}{l}\int e^x\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of WKHS 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?

WKHS Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: WKHS Workhorse Group Inc. Common Stock
Time series to forecast n: 04 May 2023 for (n+16 weeks)

According to price forecasts for (n+16 weeks) 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 Workhorse Group Inc. Common Stock

1. Expected credit losses shall be discounted to the reporting date, not to the expected default or some other date, using the effective interest rate determined at initial recognition or an approximation thereof. If a financial instrument has a variable interest rate, expected credit losses shall be discounted using the current effective interest rate determined in accordance with paragraph B5.4.5.
2. An entity that first applies IFRS 17 as amended in June 2020 after it first applies this Standard shall apply paragraphs 7.2.39–7.2.42. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).
3. For the purpose of applying paragraphs B4.1.11(b) and B4.1.12(b), irrespective of the event or circumstance that causes the early termination of the contract, a party may pay or receive reasonable compensation for that early termination. For example, a party may pay or receive reasonable compensation when it chooses to terminate the contract early (or otherwise causes the early termination to occur).
4. Paragraph 4.1.1(a) requires an entity to classify financial assets on the basis of the entity's business model for managing the financial assets, unless paragraph 4.1.5 applies. An entity assesses whether its financial assets meet the condition in paragraph 4.1.2(a) or the condition in paragraph 4.1.2A(a) on the basis of the business model as determined by the entity's key management personnel (as defined in IAS 24 Related Party Disclosures).

*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

Workhorse Group Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Workhorse Group Inc. Common Stock prediction model is evaluated with Reinforcement Machine Learning (ML) and Independent T-Test^1,2,3,4 and it is concluded that the WKHS stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

WKHS Workhorse Group Inc. Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Baa2	Caa2
Balance Sheet	C	C
Leverage Ratios	B2	B2
Cash Flow	C	Caa2
Rates of Return and Profitability	B1	Ba1

*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: 89 out of 100 with 670 signals.

References

1. Belloni A, Chernozhukov V, Hansen C. 2014. High-dimensional methods and inference on structural and treatment effects. J. Econ. Perspect. 28:29–50
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. Thomas P, Brunskill E. 2016. Data-efficient off-policy policy evaluation for reinforcement learning. In Pro- ceedings of the International Conference on Machine Learning, pp. 2139–48. La Jolla, CA: Int. Mach. Learn. Soc.
4. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
5. A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
6. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
7. Lai TL, Robbins H. 1985. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22

Frequently Asked Questions

Q: What is the prediction methodology for WKHS stock?
A: WKHS stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Independent T-Test
Q: Is WKHS stock a buy or sell?
A: The dominant strategy among neural network is to Buy WKHS Stock.
Q: Is Workhorse Group Inc. Common Stock stock a good investment?
A: The consensus rating for Workhorse Group Inc. Common Stock is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of WKHS stock?
A: The consensus rating for WKHS is Buy.
Q: What is the prediction period for WKHS stock?
A: The prediction period for WKHS is (n+16 weeks)

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