Modelling A.I. in Economics

PNI PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED

Outlook: PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 23 May 2023 for (n+16 weeks)
Methodology : Modular Neural Network (Market News Sentiment Analysis)

Abstract

PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Sign Test1,2,3,4 and it is concluded that the PNI 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. Technical Analysis with Algorithmic Trading
  2. Can stock prices be predicted?
  3. Operational Risk

PNI Target Price Prediction Modeling Methodology

We consider PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of PNI 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(Sign 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(Modular Neural Network (Market News Sentiment Analysis)) X S(n):→ (n+16 weeks) i = 1 n s i

n:Time series to forecast

p:Price signals of PNI 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?

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

Sample Set: Neural Network
Stock/Index: PNI PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED
Time series to forecast n: 23 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 PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED

  1. Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.
  2. A contractual cash flow characteristic does not affect the classification of the financial asset if it could have only a de minimis effect on the contractual cash flows of the financial asset. To make this determination, an entity must consider the possible effect of the contractual cash flow characteristic in each reporting period and cumulatively over the life of the financial instrument. In addition, if a contractual cash flow characteristic could have an effect on the contractual cash flows that is more than de minimis (either in a single reporting period or cumulatively) but that cash flow characteristic is not genuine, it does not affect the classification of a financial asset. A cash flow characteristic is not genuine if it affects the instrument's contractual cash flows only on the occurrence of an event that is extremely rare, highly abnormal and very unlikely to occur.
  3. 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.
  4. If the group of items does have offsetting risk positions (for example, a group of sales and expenses denominated in a foreign currency hedged together for foreign currency risk) then an entity shall present the hedging gains or losses in a separate line item in the statement of profit or loss and other comprehensive income. Consider, for example, a hedge of the foreign currency risk of a net position of foreign currency sales of FC100 and foreign currency expenses of FC80 using a forward exchange contract for FC20. The gain or loss on the forward exchange contract that is reclassified from the cash flow hedge reserve to profit or loss (when the net position affects profit or loss) shall be presented in a separate line item from the hedged sales and expenses. Moreover, if the sales occur in an earlier period than the expenses, the sales revenue is still measured at the spot exchange rate in accordance with IAS 21. The related hedging gain or loss is presented in a separate line item, so that profit or loss reflects the effect of hedging the net position, with a corresponding adjustment to the cash flow hedge reserve. When the hedged expenses affect profit or loss in a later period, the hedging gain or loss previously recognised in the cash flow hedge reserve on the sales is reclassified to profit or loss and presented as a separate line item from those that include the hedged expenses, which are measured at the spot exchange rate in accordance with IAS 21.

*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

PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED prediction model is evaluated with Modular Neural Network (Market News Sentiment Analysis) and Sign Test1,2,3,4 and it is concluded that the PNI 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

PNI PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCCaa2
Balance SheetBa3B3
Leverage RatiosCBaa2
Cash FlowBa2Baa2
Rates of Return and ProfitabilityBa2Ba1

*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 842 signals.

References

  1. J. Z. Leibo, V. Zambaldi, M. Lanctot, J. Marecki, and T. Graepel. Multi-agent Reinforcement Learning in Sequential Social Dilemmas. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 2017
  2. J. N. Foerster, Y. M. Assael, N. de Freitas, and S. Whiteson. Learning to communicate with deep multi-agent reinforcement learning. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 2137–2145, 2016.
  3. Breiman L. 2001b. Statistical modeling: the two cultures (with comments and a rejoinder by the author). Stat. Sci. 16:199–231
  4. V. Konda and J. Tsitsiklis. Actor-Critic algorithms. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1008–1014, 2000
  5. J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
  6. P. Milgrom and I. Segal. Envelope theorems for arbitrary choice sets. Econometrica, 70(2):583–601, 2002
  7. Semenova V, Goldman M, Chernozhukov V, Taddy M. 2018. Orthogonal ML for demand estimation: high dimensional causal inference in dynamic panels. arXiv:1712.09988 [stat.ML]
Frequently Asked QuestionsQ: What is the prediction methodology for PNI stock?
A: PNI stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Sign Test
Q: Is PNI stock a buy or sell?
A: The dominant strategy among neural network is to Buy PNI Stock.
Q: Is PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED stock a good investment?
A: The consensus rating for PINNACLE INVESTMENT MANAGEMENT GROUP LIMITED is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of PNI stock?
A: The consensus rating for PNI is Buy.
Q: What is the prediction period for PNI stock?
A: The prediction period for PNI is (n+16 weeks)



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