Modelling A.I. in Economics

PLL PIEDMONT LITHIUM INC.

Outlook: PIEDMONT LITHIUM INC. is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 25 Jan 2023 for (n+16 weeks)
Methodology : Transfer Learning (ML)

Abstract

PIEDMONT LITHIUM INC. prediction model is evaluated with Transfer Learning (ML) and Wilcoxon Sign-Rank Test1,2,3,4 and it is concluded that the PLL stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Hold

Key Points

  1. Fundemental Analysis with Algorithmic Trading
  2. Can stock prices be predicted?
  3. Probability Distribution

PLL Target Price Prediction Modeling Methodology

We consider PIEDMONT LITHIUM INC. Decision Process with Transfer Learning (ML) where A is the set of discrete actions of PLL 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(Wilcoxon Sign-Rank Test)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(Transfer Learning (ML)) X S(n):→ (n+16 weeks) S = s 1 s 2 s 3

n:Time series to forecast

p:Price signals of PLL 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?

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

Sample Set: Neural Network
Stock/Index: PLL PIEDMONT LITHIUM INC.
Time series to forecast n: 25 Jan 2023 for (n+16 weeks)

According to price forecasts for (n+16 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 PIEDMONT LITHIUM INC.

  1. A portfolio of financial assets that is managed and whose performance is evaluated on a fair value basis (as described in paragraph 4.2.2(b)) is neither held to collect contractual cash flows nor held both to collect contractual cash flows and to sell financial assets. The entity is primarily focused on fair value information and uses that information to assess the assets' performance and to make decisions. In addition, a portfolio of financial assets that meets the definition of held for trading is not held to collect contractual cash flows or held both to collect contractual cash flows and to sell financial assets. For such portfolios, the collection of contractual cash flows is only incidental to achieving the business model's objective. Consequently, such portfolios of financial assets must be measured at fair value through profit or loss.
  2. The expected credit losses on a loan commitment shall be discounted using the effective interest rate, or an approximation thereof, that will be applied when recognising the financial asset resulting from the loan commitment. This is because for the purpose of applying the impairment requirements, a financial asset that is recognised following a draw down on a loan commitment shall be treated as a continuation of that commitment instead of as a new financial instrument. The expected credit losses on the financial asset shall therefore be measured considering the initial credit risk of the loan commitment from the date that the entity became a party to the irrevocable commitment.
  3. 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).
  4. In accordance with paragraph 4.1.3(a), principal is the fair value of the financial asset at initial recognition. However that principal amount may change over the life of the financial asset (for example, if there are repayments of principal).

*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

PIEDMONT LITHIUM INC. is assigned short-term Ba1 & long-term Ba1 estimated rating. PIEDMONT LITHIUM INC. prediction model is evaluated with Transfer Learning (ML) and Wilcoxon Sign-Rank Test1,2,3,4 and it is concluded that the PLL stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Hold

PLL PIEDMONT LITHIUM INC. Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB2Caa2
Balance SheetCaa2C
Leverage RatiosBaa2Baa2
Cash FlowBa3Baa2
Rates of Return and ProfitabilityCaa2Baa2

*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: 77 out of 100 with 708 signals.

References

  1. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
  2. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Can stock prices be predicted?(SMI Index Stock Forecast). AC Investment Research Journal, 101(3).
  3. D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
  4. Wager S, Athey S. 2017. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. 113:1228–42
  5. Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
  6. Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
  7. Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
Frequently Asked QuestionsQ: What is the prediction methodology for PLL stock?
A: PLL stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Wilcoxon Sign-Rank Test
Q: Is PLL stock a buy or sell?
A: The dominant strategy among neural network is to Hold PLL Stock.
Q: Is PIEDMONT LITHIUM INC. stock a good investment?
A: The consensus rating for PIEDMONT LITHIUM INC. is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of PLL stock?
A: The consensus rating for PLL is Hold.
Q: What is the prediction period for PLL stock?
A: The prediction period for PLL is (n+16 weeks)

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