Outlook: Power Nickel Inc. is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 30 Jan 2023 for (n+3 month)
Methodology : Transfer Learning (ML)

Abstract

Power Nickel Inc. prediction model is evaluated with Transfer Learning (ML) and Ridge Regression1,2,3,4 and it is concluded that the PNPN:TSXV stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

Key Points

1. Can stock prices be predicted?
2. Operational Risk
3. What is a prediction confidence?

PNPN:TSXV Target Price Prediction Modeling Methodology

We consider Power Nickel Inc. Decision Process with Transfer Learning (ML) where A is the set of discrete actions of PNPN:TSXV 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= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Transfer Learning (ML)) X S(n):→ (n+3 month) $\stackrel{\to }{R}=\left({r}_{1},{r}_{2},{r}_{3}\right)$

n:Time series to forecast

p:Price signals of PNPN:TSXV 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?

PNPN:TSXV Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: PNPN:TSXV Power Nickel Inc.
Time series to forecast n: 30 Jan 2023 for (n+3 month)

According to price forecasts for (n+3 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 Power Nickel Inc.

1. A layer component that includes a prepayment option is not eligible to be designated as a hedged item in a fair value hedge if the prepayment option's fair value is affected by changes in the hedged risk, unless the designated layer includes the effect of the related prepayment option when determining the change in the fair value of the hedged item.
2. An entity applies IAS 21 to financial assets and financial liabilities that are monetary items in accordance with IAS 21 and denominated in a foreign currency. IAS 21 requires any foreign exchange gains and losses on monetary assets and monetary liabilities to be recognised in profit or loss. An exception is a monetary item that is designated as a hedging instrument in a cash flow hedge (see paragraph 6.5.11), a hedge of a net investment (see paragraph 6.5.13) or a fair value hedge of an equity instrument for which an entity has elected to present changes in fair value in other comprehensive income in accordance with paragraph 5.7.5 (see paragraph 6.5.8).
3. When an entity, consistent with its hedge documentation, frequently resets (ie discontinues and restarts) a hedging relationship because both the hedging instrument and the hedged item frequently change (ie the entity uses a dynamic process in which both the hedged items and the hedging instruments used to manage that exposure do not remain the same for long), the entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component is separately identifiable—only when it initially designates a hedged item in that hedging relationship. A hedged item that has been assessed at the time of its initial designation in the hedging relationship, whether it was at the time of the hedge inception or subsequently, is not reassessed at any subsequent redesignation in the same hedging relationship.
4. For lifetime expected credit losses, an entity shall estimate the risk of a default occurring on the financial instrument during its expected life. 12-month expected credit losses are a portion of the lifetime expected credit losses and represent the lifetime cash shortfalls that will result if a default occurs in the 12 months after the reporting date (or a shorter period if the expected life of a financial instrument is less than 12 months), weighted by the probability of that default occurring. Thus, 12-month expected credit losses are neither the lifetime expected credit losses that an entity will incur on financial instruments that it predicts will default in the next 12 months nor the cash shortfalls that are predicted over the next 12 months.

*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

Power Nickel Inc. is assigned short-term Ba1 & long-term Ba1 estimated rating. Power Nickel Inc. prediction model is evaluated with Transfer Learning (ML) and Ridge Regression1,2,3,4 and it is concluded that the PNPN:TSXV stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

PNPN:TSXV Power Nickel Inc. Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBa3C
Balance SheetBaa2C
Leverage RatiosBaa2B2
Cash FlowCBaa2
Rates of Return and ProfitabilityBa1Baa2

*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 806 signals.

References

1. N. B ̈auerle and J. Ott. Markov decision processes with average-value-at-risk criteria. Mathematical Methods of Operations Research, 74(3):361–379, 2011
2. Bai J, Ng S. 2017. Principal components and regularized estimation of factor models. arXiv:1708.08137 [stat.ME]
3. G. J. Laurent, L. Matignon, and N. L. Fort-Piat. The world of independent learners is not Markovian. Int. J. Know.-Based Intell. Eng. Syst., 15(1):55–64, 2011
4. Chernozhukov V, Newey W, Robins J. 2018c. Double/de-biased machine learning using regularized Riesz representers. arXiv:1802.08667 [stat.ML]
5. M. Colby, T. Duchow-Pressley, J. J. Chung, and K. Tumer. Local approximation of difference evaluation functions. In Proceedings of the Fifteenth International Joint Conference on Autonomous Agents and Multiagent Systems, Singapore, May 2016
6. Jacobs B, Donkers B, Fok D. 2014. Product Recommendations Based on Latent Purchase Motivations. Rotterdam, Neth.: ERIM
7. Krizhevsky A, Sutskever I, Hinton GE. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems, Vol. 25, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 1097–105. San Diego, CA: Neural Inf. Process. Syst. Found.
Frequently Asked QuestionsQ: What is the prediction methodology for PNPN:TSXV stock?
A: PNPN:TSXV stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Ridge Regression
Q: Is PNPN:TSXV stock a buy or sell?
A: The dominant strategy among neural network is to Sell PNPN:TSXV Stock.
Q: Is Power Nickel Inc. stock a good investment?
A: The consensus rating for Power Nickel Inc. is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of PNPN:TSXV stock?
A: The consensus rating for PNPN:TSXV is Sell.
Q: What is the prediction period for PNPN:TSXV stock?
A: The prediction period for PNPN:TSXV is (n+3 month)