Modelling A.I. in Economics

PUR PURSUIT MINERALS LTD (Forecast)

Outlook: PURSUIT MINERALS LTD assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 03 Jan 2023 for (n+16 weeks)
Methodology : Inductive Learning (ML)

Abstract

This paper studies the possibilities of making prediction of stock market prices using historical data and machine learning algorithms.(Singh, R. and Srivastava, S., 2017. Stock prediction using deep learning. Multimedia Tools and Applications, 76(18), pp.18569-18584.) We evaluate PURSUIT MINERALS LTD prediction models with Inductive Learning (ML) and Wilcoxon Rank-Sum Test1,2,3,4 and conclude that the PUR 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. Operational Risk
  2. What are the most successful trading algorithms?
  3. How can neural networks improve predictions?

PUR Target Price Prediction Modeling Methodology

We consider PURSUIT MINERALS LTD Decision Process with Inductive Learning (ML) where A is the set of discrete actions of PUR 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 Rank-Sum 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(Inductive Learning (ML)) X S(n):→ (n+16 weeks) e x rx

n:Time series to forecast

p:Price signals of PUR 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?

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

Sample Set: Neural Network
Stock/Index: PUR PURSUIT MINERALS LTD
Time series to forecast n: 03 Jan 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 PURSUIT MINERALS LTD

  1. If a put option obligation written by an entity or call option right held by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at amortised cost, the associated liability is measured at its cost (ie the consideration received) adjusted for the amortisation of any difference between that cost and the gross carrying amount of the transferred asset at the expiration date of the option. For example, assume that the gross carrying amount of the asset on the date of the transfer is CU98 and that the consideration received is CU95. The gross carrying amount of the asset on the option exercise date will be CU100. The initial carrying amount of the associated liability is CU95 and the difference between CU95 and CU100 is recognised in profit or loss using the effective interest method. If the option is exercised, any difference between the carrying amount of the associated liability and the exercise price is recognised in profit or loss.
  2. An entity shall assess at the inception of the hedging relationship, and on an ongoing basis, whether a hedging relationship meets the hedge effectiveness requirements. At a minimum, an entity shall perform the ongoing assessment at each reporting date or upon a significant change in the circumstances affecting the hedge effectiveness requirements, whichever comes first. The assessment relates to expectations about hedge effectiveness and is therefore only forward-looking.
  3. Expected credit losses reflect an entity's own expectations of credit losses. However, when considering all reasonable and supportable information that is available without undue cost or effort in estimating expected credit losses, an entity should also consider observable market information about the credit risk of the particular financial instrument or similar financial instruments.
  4. Paragraph 5.5.4 requires that lifetime expected credit losses are recognised on all financial instruments for which there has been significant increases in credit risk since initial recognition. In order to meet this objective, if an entity is not able to group financial instruments for which the credit risk is considered to have increased significantly since initial recognition based on shared credit risk characteristics, the entity should recognise lifetime expected credit losses on a portion of the financial assets for which credit risk is deemed to have increased significantly. The aggregation of financial instruments to assess whether there are changes in credit risk on a collective basis may change over time as new information becomes available on groups of, or individual, financial instruments.

*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

PURSUIT MINERALS LTD assigned short-term Ba1 & long-term Ba1 estimated rating. We evaluate the prediction models Inductive Learning (ML) with Wilcoxon Rank-Sum Test1,2,3,4 and conclude that the PUR 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

PUR PURSUIT MINERALS LTD Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB2Baa2
Balance SheetBa2B1
Leverage RatiosCaa2B2
Cash FlowBaa2Caa2
Rates of Return and ProfitabilityCBaa2

*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: 72 out of 100 with 735 signals.

References

  1. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
  2. Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
  3. S. Devlin, L. Yliniemi, D. Kudenko, and K. Tumer. Potential-based difference rewards for multiagent reinforcement learning. In Proceedings of the Thirteenth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2014
  4. S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
  5. Nie X, Wager S. 2019. Quasi-oracle estimation of heterogeneous treatment effects. arXiv:1712.04912 [stat.ML]
  6. Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
  7. C. Szepesvári. Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2010
Frequently Asked QuestionsQ: What is the prediction methodology for PUR stock?
A: PUR stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Wilcoxon Rank-Sum Test
Q: Is PUR stock a buy or sell?
A: The dominant strategy among neural network is to Buy PUR Stock.
Q: Is PURSUIT MINERALS LTD stock a good investment?
A: The consensus rating for PURSUIT MINERALS LTD is Buy and assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of PUR stock?
A: The consensus rating for PUR is Buy.
Q: What is the prediction period for PUR stock?
A: The prediction period for PUR is (n+16 weeks)

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